Science Tech News

The instrument, which operates near absolute zero for hours, will soon ship to a few labs. Researchers are thrilled.

That author's affiliation: University of British Columbia Institution (first & last author): Shanghai University of Engineering Science

arXiv: https://arxiv.org/abs/2512.09547

In cuprate superconductors, the overdoped regime has received comparatively limited attention. Here, broadband optical spectroscopy and DQMC calculations reveal an electronic reconstruction in LSCO beyond x > 0.2, consistent with a checkerboard Zhang–Rice configuration hosting coexisting localized and itinerant carriers.

arXiv: https://arxiv.org/abs/2510.26801

Whether superconductivity in twisted bilayer graphene emerges from small or large Fermi surfaces remains debated. Here, the authors propose a symmetric pseudogap metal with small hole pockets, showing that local-moment pairing can transfer to mobile carriers and yield two-gap nematic superconductivity

That author's affiliation: Max Planck Institute for Chemical Physics of Solids Institution (first & last author): Weizmann Institute of Science

Surface deformation of the kagome lattice in <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><mrow><msub><mtext>Co</mtext><mn>3</mn></msub><msub><mtext>Sn</mtext><mn>2</mn></msub><msub><mtext>S</mtext><mn>2</mn></msub></mrow></math> flattens saddle points into a higher-order Van Hove singularity, triggering a <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><mi>d</mi></math>-wave Pomeranchuk instability and nematic states.

That author's affiliation: Wenzhou University Institution (first & last author): Wenzhou University

arXiv: https://arxiv.org/abs/2512.02401

Quantum Coulomb drag signatures of Majorana bound states

arXiv: https://arxiv.org/abs/2503.17362

Criteria for unbiased estimation: applications to noise-agnostic sensing and quantum channel estimation

Conformal field theories describe universal physics at quantum critical points, but it is hard to find microscopic models that realize particular field theories. Studying competing boundary conditions of topological phases provides a systematic way to build such models.

A semiclassical framework models quantum quadrupoles as biaxial tensors, showing how angular-momentum-dependent geometries dictate generalized nematic phases and quadrupolar spin liquids in frustrated magnets.

A theoretical surface spin-group framework demonstrates that surface symmetry breaking in conventional antiferromagnets naturally induces two-dimensional altermagnetism across more than 150 candidate materials.

arXiv: https://arxiv.org/abs/2505.03111

Quantum simulations of field-theory scattering require preparing particles and following their collision dynamics. A digital quantum simulation now reveals the inelastic production of particles in one-dimensional Ising field theory.

That author's affiliation: University of California, Santa Barbara Institution (first & last author): Shanghai Jiao Tong University

Revealing concealed ionic local moments in kagome superconductors reflects strong local correlations.

Higher-order nonlinear Hall responses can reveal Berry-curvature multipoles associated with electronic nematicity. Here, the authors identify a vortex-enhanced third-order Hall response in CsV3Sb5 and uncover a Berry-curvature quadrupole associated with chiral loop-current order

That author's affiliation: École Normale Supérieure de Lyon First author institution: ETH Zurich Last author institution: École Normale Supérieure de Lyon

arXiv: https://arxiv.org/abs/2209.09281

Researchers develop a quantum circuit framework for extended Wigner’s friend scenarios, resolving logical paradoxes by tracking Heisenberg cuts.

That author's affiliation: The Nature Conservancy Institution (first & last author): The Nature Conservancy

Monolayer superconductors enter the circuit

arXiv: https://arxiv.org/abs/2511.11008

The authors introduce a practical game that distinguishes quantum from classical behaviour without relying on unproven assumptions. Quantum computers achieve exponentially larger scores than any classical strategy, a result confirmed in experiments.

Single-operation Rydberg phase gates via dynamic population suppression

Attaining quantum sensing enhancement from monitored dissipative time crystals

That author's affiliation: Southern University of Science and Technology Institution (first & last author): Southern University of Science and Technology

This work reports the observation of antichiral hinge states in a 3D gyromagnetic photonic crystal. Extending antichirality to higher-order topology, it reveals a topological semimetal with co-propagating transport along parallel hinges.

Non-Hermitian band structures enable unusual phenomena but remain difficult to map beyond one dimension. Here, the authors develop a general non-Bloch supercell framework to resolve complex momentum, energy, eigenstates, and topology, demonstrated in one- and two-dimensional acoustic crystals.

Quantum oscillation measurements map the g-wave altermagnetic order parameter in CrSb, establishing it as a prototypical unconventional magnet with momentum-dependent spin splitting.

Quantum quenches from the critical point: theory and experimental validation in a trapped-ion quantum simulator

Transition metal dichalcogenide twisted structures are known to exhibit strongly correlated phenomena. Here, the authors demonstrate a range of correlated insulating states at integer and fractional fillings in twisted MoSe2 homobilayers arising from the Γ-valley moire flat bands.

A transport technique that allows the measurement of the effective charge of fractional quantum Hall states as they tunnel through a controlled impurity is demonstrated.

A high-quality, pristine monolayer cuprate superconductor with a single CuO2 plane is fabricated and used to identify two quantum critical phenomena emerging between the Mott insulating phase and the superconducting phase.

A unitary encoder for surface codes

Using Brillouin-based phonon spectroscopy, surface interactions have been identified as the dominant source of phonon decoherence in crystalline media. When these interactions are reduced through chemical mechanical polishing, high-frequency bulk acoustic wave oscillators can be realized with record Q-factors and coherence times, suitable for use as long-lived solid-state quantum memories.

Heavy-fermion superconductivity has now been observed under pressure in the van der Waals metal CeSiI. This material will provide a new platform for studying the interplay of dimensionality and Kondo physics.

CeSiI is a two-dimensional heavy-fermion metal. Now, the interplay between antiferromagnetism, Kondo coherence and unconventional superconductivity is observed by applying pressure to this material.

That author's affiliation: Harvard University Institution (first & last author): Harvard University

Topological phases can be hard to distinguish with local measurements. Now, a transition between two such phases has been revealed in ultracold erbium atoms, and shown to disappear when two systems are stacked or information about disorder is lost.

The role of magnetic impurities in shaping superconductivity and electronic order in kagome metals remains unresolved. Now, a study reveals anisotropic Kondo resonances intertwined with the superconducting gap in a magnetically doped kagome superconductor.

The first holes doped into a cuprate create atomic-scale electronic states that combine into larger motifs, offering a bottom-up view of the emergence of charge order and superconducting phenomena.

Single-atom measurements show non-Gaussian order-parameter fluctuations and critical scaling across a continuous phase transition, highlighting the importance of full statistical distributions in understanding universality.

On-chip generation of single-photon skyrmions is challenging due to the nanoscale confinement of quantum emitters. Here the authors demonstrate a metasurface-integrated quantum emitter platform enabling room-temperature on-chip generation of single-photon skyrmions without requiring magnetic fields.

Variational Gibbs state preparation on trapped-ion devices

Adiabatic preparation of thermal states and entropy-noise relation on noisy quantum computers

Publisher Correction: A 98-qubit trapped-ion quantum computer with all-to-all connectivity

That author's affiliation: Karlsruhe Institute of Technology First author institution: Karlsruhe Institute of Technology Last author institution: Unknown

Gradiometric, fully tunable C-shunted flux qubits

Single molecules that host isolated spins are promising candidates for applications in quantum technologies. Now it is shown that exchange interactions enable electric control of spins in two different molecular species.

By integrating miniaturized cameras with stretchable interconnects, this skin-conformal rigid-in-soft system endows dynamic surfaces with high-fidelity visual capabilities, augmenting perception for wearables and embodied artificial intelligence.

Electrocatalytic NO reduction to NH3 is hindered by insufficient NO activation. Here, the authors report Cu1−Ti pairs that integrate the N affinity of Ti and O affinity of Cu to efficiently activate NO via bidirectional electron donation, thus achieving a high NH3 yield and Faradaic efficiency.

That author's affiliation: The Nature Conservancy Institution (first & last author): The Nature Conservancy

The device has helped a man with motor neuron disease communicate and control his computer for nearly two years.

That author's affiliation: National Institutes of Health Institution (first & last author): National Institutes of Health

Mechanisms underlying effective immune escape in HPV-associated oropharyngeal cancers despite the presence of immune cells are incompletely understood. Here, authors use single-cell spatial analysis to show that tumors form distinct local immune niches, including hypoxic regions and chemokine foci, that shape immune cell composition and support cancer cell states able to evade HPV-specific T cell responses.

The evolutionary changes in cancer genomes under treatment are not fully understood. Here, whole-genome sequencing of 58 single-cell tumoroids and 18 matched bulk tumours from 6 metastatic colorectal cancer patients reveals clonal structures and mutation patterns under therapy.

Spatial and single-cell transcriptomics of patient-derived brain organoids reveal disrupted progenitor–neuron organization and local neuronal disarray, implicating spatially mosaic pathogenesis in autism heterogeneity.

Inhibition of PLK4 is synthetic lethal in cancers with chromosome 17q TRIM37 copy number gain. Here, the authors show that while RP-1664 (PLK4 inhibitor) causes centrosome depletion in a TRIM37-dependent manner as high doses, low dose causes cell death in a TRIM37-independent manner via centrosome amplification and demonstrate its efficacy in preclinical models of neuroblastoma with TRIM37 gain.

That author's affiliation: Fujian University of Traditional Chinese Medicine Institution (first & last author): Nanjing University of Chinese Medicine

Bone metastases derived from lung cancer typically exhibit an immunosuppressive microenvironment. This study identifies a YBX1 glycosylation–dependent mechanism that drives both metastasis and immunosuppression, and proposes the small molecule Icaritin as a potential therapeutic strategy through YBX1 degradation.

Three-outcome multipartite Bell inequalities: applications to dimension witnessing and spin-nematic squeezing in many-body systems

That author's affiliation: Yale University Institution (first & last author): Yale University

The neural principles underlying flexible social gaze communication remain unknown. Here the authors show that social gaze follows a compositional code in the primate brain, with the basolateral amygdala and anterior cingulate gyrus representing its primitives in abstract, orthogonal formats.

This study is on accelerating k-nearest neighbors classification. Here, authors introduce an adaptive graph based kNN framework using HNSW and precomputed voting to shift computation to training time, enabling real-time inference without sacrificing classification accuracy.

That author's affiliation: University of Minnesota Institution (first & last author): University of Minnesota

The basolateral amygdala dopamine system has received little attention. Here, authors show that BLA dopamine plays a unique role in learning, by encoding the emotional salience of sensory cues to support dynamic disambiguation of affective states.

After years of effort, two research teams have developed ‘laser phase plate’ systems that could help cryo-electron-microscopy users to generate high-quality structures for a broad range of proteins.

Softening of the cells on the outermost surface of the trap lets the plant move at a breakneck pace.

This study introduces MMKD-CLIP, a generalist biomedical vision-language model trained with multi-teacher knowledge distillation to improve performance across heterogeneous medical imaging modalities and tasks.

The high multimodal processing capability is constrained by the physical separation of sensors and processors. Luo et al. proposed a machine learning-aided framework for carbon nanotube circuit design. Its feasibility is validated via a flexible edge computing system that integrates sensing and processing.

Towards practical quantum neural network diagnostics with neural tangent kernels

Efficient blue perovskite light-emitting diodes with an external quantum efficiency of 21.8% are achieved through in situ polymerization-driven nanocrystal confinement.

A co-optimized AI hardware–software system using resistive-memory computing improves energy efficiency and parallelism for sparse signal reconstruction in imaging and three-dimensional vision applications.

Near-infrared fluorescent carbon nanotubes exhibit light-induced quantum friction in water, in which exciton interactions slow nanoscale motion and enable optical control of diffusion and fluid dynamics.

Ischemic stroke treatment can be complicated by brain edema if thrombolytic drugs are given too late. Here, the authors show that anisodine hydrobromide mitigates this dangerous edema in mice by targeting the Matk-Src pathway to protect blood vessels in the brain

The non-invasive assessment of renal masses remains a critical challenge in urologic oncology. Here, the authors develop RenalCLIP, a vision-language foundation model for renal mass assessment and classification using CT scans from 8,809 patients across Chinese and international cohorts, outperforming other models in diagnostic classification at even 20% of the training data.

That author's affiliation: Harvard University First author institution: Harvard University Last author institution: Boston Children's Hospital

Distributed control circuits across a brain-and-cord connectome

The snowballing ability of artificial intelligence to trawl open data sets has some scientists worried about losing control of their information.

Experimental demonstration of a two-voter quantum anonymous voting prototype with continuous variables

Integrated high-quality multi-wavelength quantum light source compatible with ITU Channel Grid

That author's affiliation: Council of Scientific and Industrial Research Institution (first & last author): Council of Scientific and Industrial Research

This review outlines the evolution of timekeeping, focusing on atomic clocks and time dissemination methods, underpinning modern technologies such as GNSS and communication networks and enabling emerging applications such as quantum communication, while addressing future directions in global synchronization and SI second redefinition.

That author's affiliation: National Taiwan University Institution (first & last author): National Taiwan University

Cancer-associated fibroblasts can induce immune tolerance in mesenchymal colorectal cancer through fibrosis. This study identifies TXNDC5 as a TGFβ-dependent regulator of fibrosis whose targeting remodels the tumor stroma and sensitizes tumors to immunotherapy.

Mutations that cause antibiotic resistance in bacteria can have collateral effects that increase the vulnerability of other pathways to inhibition. Here, Wang et al. use genome-scale CRISPR interference to identify shared and strain-specific vulnerabilities associated with different drug-resistant genotypes in Mycobacterium tuberculosis.

That author's affiliation: University of Veterinary Medicine Vienna Institution (first & last author): University of Veterinary Medicine Vienna

In this study, the authors identify an avian pegivirus that is associated with brain inflammation in red-legged partridges and using experimental infection in different avian species they demonstrate viral neurotropism, revealing a potential role of pegiviruses in neurological disease.

This study is on algorithm discovery for approximate Nash equilibria. Here, authors developed LegoNE, a framework combining symbolic proof encoding with LLMs to automatically certify worst-case guarantees, discovering new equilibrium algorithms surpassing previous multi-player design paradigms.

The cognitive processes driving social media use could be key to understanding social media’s impact. Here, the authors develop a computational model of real-world social media behaviour, identifying multiple cognitive processes underlying posting.

The heavy use of platinum catalysts limits the large-scale deployment of proton exchange membrane fuel cells. Here, the authors report a carbon support design with small mesopore-dominated structures and moderate pore depth that improves performance at low platinum loading.

GSA-YOLO enables high-efficiency real-time X-ray security inspection via structured sparsity and adaptive knowledge distillation

That author's affiliation: Marmara University Institution (first & last author): Marmara University

A passive islanding detection method using deep neural bidirectional LSTM-CNN

Longitudinal transcriptomic, chromatin and genomic analyses of the two types of IDH-mutant glioma reveal in detail how disease progression is influenced by interdependent genetic, epigenetic and microenvironmental factors.

That author's affiliation: Cambridge University Hospitals NHS Foundation Trust First author institution: European Bioinformatics Institute Last author institution: Wellcome Sanger Institute

Single-cell mapping of cis-expression quantitative trait loci in inflammatory bowel disease revealed distal, enhancer-enriched variants detected at the cell-type level more frequently co-localize with genome-wide association study loci than those identified at the tissue level.

That author's affiliation: George Washington University First author institution: Thomas Jefferson National Accelerator Facility Last author institution: William & Mary

The scattering of high-energy electrons from three different nuclei demonstrated that short-range-correlated pairing depends far more on the specific quantum orbitals occupied by nucleons than predicted by theoretical models.

Adaptive nanopore sequencing enables targeted enrichment, but current methods rely on training data. Here, the authors develop GANBase, a genome‑guided deep‑learning framework that achieves robust, data‑independent target enrichment and host depletion across diverse sequencing conditions.

It is challenging to balance molecular selectivity without compromising mechanical properties. Here, the authors introduce network completeness as a key descriptor to guide the design of subnanometer diffusion channels in hyper-crosslinked polymer membranes. By linking bridge connectivity to separation performance, the authors present an optimized balance of molecular selectivity and mechanical robustness.

That author's affiliation: University of Wisconsin–Madison Institution (first & last author): University of Wisconsin–Madison

Detecting multi-way genomic interactions to better understand genomic structure is challenging. Here, the authors address this challenge by introducing MINTsC, a method that detects multi-way genomic interactions from single-cell Hi-C data.

Researchers show how plants control the number of nuclear photobodies built by phytochrome B. Photobody number is set by phytochrome B’s activity state and by the strength of nuclear seeding sites, which change with temperature and cell type.

Phase transitions in cellular collectives are triggered by multiple control parameters. Independently tuning cell density and adhesion, both in silico and in vivo, reveals that adhesion dictates the tissue material state. Adhesion-driven solidification in unjammed pluripotent tissues is shown to drive epithelial organization — uncovering that phase transitions direct developmental programmes.

Publisher Correction: White matter micro- and macrostructure brain charts for the human lifespan

Simulations of biological systems could transform biomedical research, but researchers are still learning how to reproduce life’s complexity without drowning in data.

That author's affiliation: National University of Sciences and Technology First author institution: National University of Sciences and Technology Last author institution: King Khalid University

Multiobjective framework for hardware and quality aware approximate Gaussian filtering toward energy efficient ultrasound image denoising

A machine-learning model that uses smartphone cameras to measure heart rate in the background during normal daily phone use and subsequently estimate resting heart rate could make it easier for people to monitor heart health.

A machine-learning system has been developed that can monitor heart rate using facial video clips that are captured passively by the user-facing camera during everyday smartphone use. The system meets industry accuracy standards for heart-rate measurement and is as accurate as wearable technology for measuring daily resting heart rate.

Dynamic task offloading for sports training monitoring in MEC-assisted smart wearable device systems

PKM2-driven glycolysis mediates rotenone neurotoxicity via MG-Hs in Parkinson’s disease

Microbatteries are essential for miniaturized electronics, but it is currently difficult for scale-up fabrication with high efficiency and high consistency. Here, authors report a stack-punching method that enables high-throughput fabrication of microbatteries with high consistency, demonstrating their potential for wearable devices and biohybrid systems.

That author's affiliation: École Polytechnique Fédérale de Lausanne Institution (first & last author): École Polytechnique Fédérale de Lausanne

Cryo-EM faces a bottleneck in sample preparation. Here, the authors evaluated the cryoWriter, a robotic microfluidics device to prepare cryo-EM grids from nanoliters of sample. Multiple samples are written onto the same grid, enabling time-resolved exposure experiments.

That author's affiliation: Bioprocessing Technology Institute Institution (first & last author): Bioprocessing Technology Institute

PEG is an important component in lipid nanoparticles but can cause anti-PEG antibody responses. Here, the authors develop biodegradable poly-DL-serine lipids as PEG replacements and demonstrate mRNA delivery with limited immunogenicity, demonstrating improved safety.

That author's affiliation: Shenzhen University Institution (first & last author): Shenzhen University

Reliable sweat induction remains a challenge for wearable sweat biosensing. Here, the authors develop a skin-conformal wearable device that uses ultrasound to induce sweat under resting conditions for electrochemical biomarker tracking.

The ability to precisely tune light intensity within projected images can massively scale up sub-100 nm additive manufacturing. Kim and Saha show how optical diffraction can be leveraged to achieve this with a single pulse of femtosecond laser.

Computing efficiency and data security are two critical demands in the AI era. Han et al. report a ferroelectric transistor with controllable synaptic and secure functionalities. It physically hides stored data to block read attacks. Simulations show its array effectively reduces model inversion attacks.

Controlling unknown quantum states via data-driven state representations

For about ten years, the lifetime of a nuclear metastable state in singly charged thorium-229 ions has puzzled physicists, because it appeared to be shorter than theoretically expected. The solution provides a hint towards an uncommon decay channel.

That author's affiliation: Olivia Newton-John Cancer Wellness & Research Centre First author institution: Peter MacCallum Cancer Centre Last author institution: The University of Melbourne

Deep learning and radiomics models in patients with advanced non-small cell lung cancer treated with immunotherapy combined with stereotactic radiotherapy

The authors present ByteFF-Pol, a force field trained solely on quantum data to accurately predict liquid and electrolyte properties. It bridges the gap between microscopic calculations and materials design without experimental calibration.

Metabolic reprogramming and the tumor microenvironment (TME) shape pancreatic cancer progression and treatment response. Here, the authors map cell–type–specific metabolic and TME features to define three tumor subtypes with distinct immune profiles and differential responses to existing and proposed therapeutic strategies.

The miniaturized vacuum system for cold atom sensors based on the technology of passive vacuum

Highest h-index author on this paper: (h-index n/a) That author's affiliation: California Institute of Technology Institution (first & last author): California Institute of Technology

Learning to erase quantum states: thermodynamic implications of quantum learning theory

That author's affiliation: University of British Columbia First author institution: University of British Columbia Last author institution: Swansea University

A measurement of the hyperfine splitting energy of the ground state of antihydrogen at 4 ppm precision reaches a point at which this result is sensitive to the internal structure of the antiproton.

Integration of gene expression data from multiple tissues across four mammalian species reveals conserved transcriptomic signatures of mammalian ageing and mortality and uncovers the modular architecture of ageing and mortality hallmarks.

That author's affiliation: Peking University Institution (first & last author): Beijing Academy of Quantum Information Sciences

Dynamical freezing, a mechanism by which a driven quantum system may not thermalize to a featureless ‘infinite-temperature’ state at long times, is experimentally observed in an ensemble of interacting nitrogen-vacancy spins in diamond.

Uniformly doped, ultrathin single-crystalline silicon nanomembranes can be vertically stacked at low temperature using a roll-transfer-printing process that is scalable to wafer scale and tolerant to substrate topology and surface roughness for constructing high-performance monolithic three-dimensional integrated circuits.

That author's affiliation: Centre National de la Recherche Scientifique First author institution: University of Cambridge Last author institution: The University of Texas at Austin

A direct, dynamical black-hole mass measurement in a strongly lensed little red dot at high redshift indicates that it is a massive black-hole seed caught in its earliest accretion phase.

An investigation of the Estonian Biobank and the UK Biobank has identified more than 88,000 associations between more than 8,000 genomic regions and metabolic traits. The combined size of the sample enabled the detection of many more associations than in previous efforts.

Inflammatory stress is shown to reprogram a subset of human haematopoietic stem cells (HSCs). These inflammatory memory (HSC-iM) cells have reduced differentiation and pass on inflammation-related gene programs to their immune-cell progeny. HSC-iM cells accumulate with age, and cancer-associated mutations affect HSC-iM cells more than they do other HSCs in clonal blood disorders.

Sensory stimuli have different implications depending upon context. Here, the authors report prominent context-dependent integration of whisker sensation with auditory working memory cues in frontal cortex directly downstream of somatosensory cortex.

That author's affiliation: Shanghai Jiao Tong University Institution (first & last author): Shanghai Jiao Tong University

This work demonstrates a self-powered, event-nature artificial spherical compound eye that achieved ultrafast and panoramic motion sensing under 0 V, particularly suitable for resource-limited drones and robotics.

After a heart attack, fibroblasts help coordinate inflammation and repair, but the signals controlling this response are unclear. Here, the authors show that TAK1 drives an inflammatory fibroblast state that worsens remodeling after myocardial infarction in male mice.

That author's affiliation: Shenzhen University Institution (first & last author): Shenzhen University

Deep-blue emitting materials are essential for OLEDs. Here, the authors show how molecular topology in B,N-doped nanographenes controls conformation and excited-state properties, enabling efficient, narrowband deep-blue electroluminescence.

Off-target binding can result in kinetic traps reducing the efficiency of DNA origami assembly. Here, the authors develop a software tool to design scaffold & staples with chosen sequences to avoid unwanted molecular interactions, yielding stronger, more uniform nanostructures.

A novel intrusion detection system for IIoT in 5G networks using attention-augmented federated learning and lightweight transformer architectures

That author's affiliation: Tsinghua University Institution (first & last author): Tsinghua University

Tuning of the Stark effect in black phosphorus is used to build adjustable digital and analogue circuits including a high-performance transistor array for neural networks. It offers a promising opportunity for next-generation electronics.

That author's affiliation: Norcliffe Foundation Institution (first & last author): Norcliffe Foundation

The study shows that a subpopulation of brainstem astrocytes actively regulates breathing and brain states. Activating these cells alters respiratory patterns and increases sighing, revealing a key role in linking neural activity, arousal, and respiratory control.

That author's affiliation: First Affiliated Hospital of Jiangxi Medical College Institution (first & last author): First Affiliated Hospital of Jiangxi Medical College

Using cryo-EM, researchers solve the structure of the TRPC1/5 ion channel complex, revealing a unique drug-binding pocket. This enables design of JD03-02, a selective inhibitor with potential to treat anxiety and depression.

Programmed cell death receptor-1 (PD-1) has been implicated in thymic regulation of T cell development and function. Here, the authors characterize CD8⁺ T cell development in PD-1–deficient mice and show that PD-1 constrains the emergence of an effector-like program during thymic development, thereby shaping peripheral T cell responses and exhaustion in tumours.

Odor pleasantness shapes approach and avoidance. Here, the authors show that the piriform cortex and amygdala encode the pleasantness of appetitive and aversive odors separately, while ventral prefrontal cortex represents a continuous salience code.

Privacy in distributed quantum sensing with Gaussian quantum networks

James Webb Space Telescope reveals weather patterns from how planet WASP-94 A b filters the light of its parent star.

Over the next few decades, billions of autonomous, AI-powered robots will work alongside people in factories, perform tedious tasks in warehouses, care for the elderly, assist in unsafe disaster areas, deliver packages and food to our doorsteps, and eventually, help out in our homes. Some will look like us, and many won’t. What is certain is that regardless of form factor, robots will all rely heavily on AI in order to deliver real-world value.

In 2025, total investments in robotics companies reached a record $40.7 billion, accounting for 9 percent of all venture funding. The multibillion dollar question therefore is this: What will it take for AI-powered robots to begin to have a serious economic impact? Many of today’s robotics and AI companies are making bold claims, such as that humanoid robots will soon be coming into our homes, but there’s still a big gap between promise and reality.

The promise of robots that live and work alongside us has been the stuff of science fiction for a very long time. And while many programmers have tried to make that promise a reality, the physical world is just too complicated for traditional computer programs to handle the endless complexity it presents. Thanks to AI, robots are no longer being programmed—instead, they learn to operate in the real world. With enough practice, they can learn to perceive and understand the world around them, reason about that world, and use that reason and understanding to perform tasks that are useful, reliable, and safe.

The two of us have worked at the forefront of AI and robotics for the last decade, as a Professor in Robotics at Oregon State University and Co-Founder of Agility Robotics, and as former CEO of the Everyday Robots moonshot at Google X. Our experience deploying AI-powered robots in real-world settings has given us a perspective on where AI can be used to great benefit in complex robotic systems in the near term, and where we are still on the frontier of science fiction. We believe AI will enable an inflection point in robotics advances, but that it will be through the well-engineered application of coordinated systems of different AI tools rather than a single ChatGPT-style breakthrough.

As the excitement around AI is matched only by the uncertainty of what will be possible, here are five hard truths that will define AI in robotics.

1. The YouTube-to-Reality Gap Is Real

For years we have been seeing videos on YouTube with humanoid robots performing amazing moves on everything from a dance floor to an obstacle course. The inside knowledge in robotics is to “never trust a YouTube robot video.” The gap between real robots that can perform real work in unstructured human environments and carefully scripted and edited robot performances remains significant. The latest performance to get a lot of attention was a martial arts show featuring Unitree humanoid robots performing with children at the Chinese 2026 Spring Festival Gala. While impressive, this falls into a long lineage of tightly scripted robotic performances, where everything has been carefully choreographed and planned in advance. The low-level controls, synchronization, and choreography were stunning, yet the Spring Gala robot performance showed a level of autonomy and intelligence much closer to industrial robots building cars in a factory than something that will show up in your living room any time soon.

Seeing these kinds of demos nevertheless raises questions about where robotics really is. If robots can perform kung fu moves and do backflips and dance, why aren’t they also showing up on factory floors yet? And why can’t they do the dishes in my home after dinner? The simple answer is this: Making AI-powered robots capable of performing general tasks in varied human environments is still really hard. While impressive technological feats like those at the Spring Festival may make it look like we could be very close, the use of AI in these demos is only for low-level motor control (to keep the robots from falling over) and therefore is only a small part of the solution for robots to be general purpose in the real, unstructured spaces where we humans live and work.

2. Data Is An Unsolved Challenge

Large Language Models like OpenAI’s ChatGPT and Anthropic’s Claude were initially trained on an internet-scale database of text. The world woke up one day in late 2022 to ChatGPT demonstrating that AI computers could suddenly “speak” to us in prose or verse and about seemingly any topic. LLMs have turned out to generalize well and are now able to take multimodal input (text, images, video) and produce multimodal output. Importantly, the corpus of training data was both enormous and human-generated, which are characteristics that form the gold standard for AI training.

The fastest path to robots as part of everyday life may emerge through a range of robot forms performing increasingly sophisticated applications and employing a range of AI tools.Agility Robotics

Giving AI a body (in the form of a robot) so that it can engage with people in the physical world continues to be a very difficult and broadly unsolved problem. AI models for general-purpose robotics must simultaneously satisfy multiple, often conflicting, physical, geometric, and temporal limitations while operating in unstructured, dynamic environments. In order to generalize, robot models need to be trained on data gathered in a high-dimensional configuration space, where “dimensions” represent text, lighting conditions, degrees of freedom, joint limits, velocities, force, and safety boundaries, just to mention a few. Importantly, this must be good data—it must contain many examples from what amounts to an infinite number of possible configurations in the physical world.

Since there are very few existing sources of data like this, approaches like teleoperation, video analysis, motion capture of humans, and self-exploration in simulation and in the real world are all seen as important ways to collect data. It’s a Herculean task. For example, at Everyday Robots at Google X, we ran 240 million robot instances in our simulator over the course of 2022 to collect training data, mostly to train a trash-sorting model. Similar amounts of data will be needed for every skill, to get to a similar level of capability, which is not yet human level.

3. There Will Be No Single Robot AI

We are far away from a moment where a single AI model might allow general-purpose robots to live and work alongside us.

General-purpose robots can have wheels or legs. They can have one, two, three, or more arms. Some have propellers and can fly, while others may be designed to operate under water. Some will drive on busy roads. The physical world is infinitely varied and complex. And then there are all the people and other animals that will be surrounding the robots. How do you train a model to operate a robot safely and reliably in all of these settings? The simple answer is, You don’t. At least not for quite some time.

We believe the winning AI architecture leading to the next big breakthroughs in general-purpose robotics will be “agentic AI” for robots, which are high-level coordinating models that can reason, plan, use tools, and learn from outcomes to execute complex tasks with limited supervision. Agentic, high-level models running on robots will invoke a system of specialized ones for different types of tasks. We will likely soon see multiple robots collaborating and coordinating with each other through their on-board agentic AI models.

AI tools are unlocking new and powerful capabilities in robotics, which in turn will enable new solutions and new markets. It’s encouraging to see these new models being made broadly available, some even as open-source solutions. This availability is akin to what happened with the internet: Real progress occurred when it became ubiquitous. We anticipate an inevitable democratization of complex behaviors in robotics with wide access to these AI tools and technologies.

4. Hardware Is Still Very Hard

Robots are complex systems with many parts that all need to work together with great precision. For a robot to be useful and safe, every part of it must be coordinated, from its perception systems, to the computer controlling it, all the way down to its individual actuators.

Actuators—that is, the motors and gears—are a good example of an important part of the robot where what got us here won’t get us there. The actuators used at scale by most industrial robots will not work for robots that will operate in human environments. If these robots accidentally collide with an obstacle, the resulting impacts are harsh, forces are high, and things break. Humans don’t move in this way. We are far more compliant in how we interact with the world, and we’re constantly making contact with our environment and using that contact to help us accomplish things.

Consider the challenge of inserting a key in a lock: Humans typically don’t do this by aligning the key perfectly with the keyhole. Instead, we just feel for the edge of the keyhole and jiggle the key in. Robots need to be able to operate in novel ways to achieve comparable capabilities by using a new class of actuators that are sensitive to force and able to have a compliant interaction with the environment. While these kinds of actuators do exist, they are not yet generally available at scale for robot systems designed to operate around people.

5. Real Value Comes From “Easy” Tasks

There’s a big difference between tasks that look impressive and real-world tasks that provide value. Robotics is a perfect example of Moravec’s paradox, which states that tasks that are hard for humans are easy for computers (like multiplying two big numbers), and tasks easy for humans (like a toddler’s movements) are extremely difficult for computers and robots.

Serving customers is an unforgiving reality check, because customers only care about solving the real problems they have. If we are to deploy AI-based robot solutions, they must outperform the way things are currently done, while demonstrating reliable performance metrics and safety. Agility Robotics’ early work to deploy our humanoid robot Digit in customer locations led to the realization that our first obstacle was safety: Robots that balance and manipulate objects in human spaces bring new types of risk to the workplace. In the first humanoid deployments, physical barriers were necessary, and Agility kicked off a multi-year engineering effort to solve the safety challenge, touching nearly every aspect of robot design and relying heavily on new AI-based approaches to human detection and behavior control.

Everyday Robots at Google deployed robots in 2019 that worked autonomously in office buildings doing chores like cleaning cafe tables and sorting trash. We quickly learned how “messy” and difficult the real world is for a robot. This experience informed the architecture and deployment of our AI systems while also gathering real-world data that could be combined with simulation data for training and improving models.

This focus on creating a product to meet specific customer needs and deploying robots in real-world settings is the only way to inform the structure of the AI tools and infrastructure for near-term utility on a path towards long-term broader capability and generality. There will be no “aha” moment, no silver bullet algorithm, and no volume of data sufficient to produce a general-purpose robot without extensive real-world experience.

AI Robots Are Coming, One Step at a Time

Researchers achieve a high secret key rate for quantum communication over fiber optics. By combining advanced signal modulation with new security analysis tools, they have made highly secure, high-speed quantum networks closer to practical implementation.

Local quantum nondemolition measurements and optical manipulation of long-lived circular Rydberg atoms are demonstrated by coupling them to an auxiliary array of low-angular-momentum Rydberg atoms.

The study builds a digital twin of a power substation and combines topology, alarms, waveforms, and measurements using attention-based graph models to diagnose fault location, fault type, and protection failures with robust performance under noise and missing data.

PDS5B, a cohesin regulatory protein, is shown to bind DNA and enhance the RAD51 recombinase in the promotion of DNA strand exchange and protection of DNA from MRE11 RAD50-NBS1. Here the authors use biochemical and cellular analyses to reveal that DNA binding by PDS5B is essential for DNA damage repair and the preservation of stressed DNA replication forks.

The authors report a resonant inelastic x-ray scattering study of superconducting Sm-based infinite-layer nickelate thin films. Despite the two-fold enhancement of Tc in the Sm-based nickelates compared to their Pr-based counterparts, they find that the effective in-plane exchange coupling strength is reduced by approximately 20%.

That author's affiliation: Karlsruhe Institute of Technology Institution (first & last author): Karlsruhe Institute of Technology

Mapping the positions of Two-Level-Systems on the surface of a superconducting transmon qubit

That author's affiliation: Hunan Institute of Technology First author institution: Hunan Institute of Technology Last author institution: Unknown

GNN enhanced reinforcement learning for robot navigation in complex topological networks

By using singularity physics to enable cubic-root scaling of frequency and phase modulations induced by the Coriolis effect to enhance the performance of chip-scale Coriolis vibratory gyroscopes, substantial improvements in signal-to-noise ratio and precision are demonstrated.

A genome-wide association study combining data from the Estonian Biobank and the UK Biobank identifies many common and low-frequency locus–metabolic trait associations, enabling the identification of putative causal links with disease outcomes.

Bright squeezed vacuum light boosts nonlinear atomic tunnelling ionization more than 20-fold compared with coherent light, enabling quantum control of strong-field processes without increasing classical intensity.

A reconstruction method based on Gaussian-apodized single-sideband electron ptychography removes artefacts to enable the high-fidelity identification of guest species in porous materials.

A multimodal analysis reveals a ‘U-shaped’ association between sleep duration and biological ageing across various organ systems, with too much or not enough sleep being linked with accelerated organ ageing. The study also shows that biological ageing differentially mediates the relationship between extremes in sleep duration and late-life depression.

Ionization experiment shows that quantum light can behave like a conventional laser that has a higher intensity.

Quantum learning with tunable loss functions

That author's affiliation: Centre National de la Recherche Scientifique Institution (first & last author): Centre National de la Recherche Scientifique

Classical approaches to imaging through complex media do not account for the quantum nature of the incident field. Now, images encoded on an entangled two-photon state are shown to transmit through a scattering medium whereas scattered by classical light.

This presentation highlights recent efforts at the Johns Hopkins Applied Physics Laboratory to advance agentic AI for collaborative robotic teams. It begins by framing the core challenges of enabling autonomy, coordination, and adaptability across heterogeneous systems, then introduces a scalable architecture designed to support agentic behaviors in multi-robot environments. The talk concludes with key challenges encountered and practical lessons learned from ongoing research and development.

Key learnings

• Provides an introduction to LLM-based AI Agents
• Describes an approach to applying LLM-based AI Agents to robotic teams
• Provides demonstrations of the approach running in hardware with a heterogeneous team of robots
• Presents lessons learned and future work in this area

Clinical success of fecal microbiota transplantation depends on donor microbe engraftment. Here, the authors show that inorganic nitrogen utilization capacity drives gut microbiome remodeling and that boosting this function enhances donor microbe engraftment and improved colitis treatment in mice.

Single-atom catalysts offer high efficiency for hydrogen evolution, but control of metal–support interactions remains challenging. Here, the authors report a rhodium single-atom catalyst platform enabling continuous tuning of metal–support frontier orbital interactions via anion-engineered supports.

Decoherence is a central obstacle to scalable quantum technologies across diverse physical platforms. Here the authors develop an anticipatory framework for real-time evolution of decoherence in quantum systems, demonstrating its internal-prediction component using machine learning, and apply it to the problem of spectral diffusion in solid-state quantum emitters.

That author's affiliation: Zhejiang University First author institution: Southern University of Science and Technology Last author institution: Zhejiang University

Research on dualities is commonly restricted to one-to-one mappings. Here, by incorporating artificial gauge fields, the authors demonstrate 2D and 3D acoustic metamaterials enabling ℤ2 × ℤ2 and (ℤ2)6 duality groups, respectively, where distinct structures share identical band structures, and self-duality gives rise to symmetry-protected high-order degeneracies.

More spin current can be produced with less energy lost at the source, thanks to inter-magnet pumping that rebalances angular momentum dissipation between sublattices in a ferrimagnetic multilayer.

In neurons, the mapping from inputs to output involves complex biophysical processes. Despite this complexity, it is now shown that simple artificial models explain a large fraction of the variability in neuronal activity.

A miniature bio-inspired antenna for sub-6&#xa0;GHz consumer wireless and biomedical diagnostic applications

That author's affiliation: ETH Zurich Institution (first & last author): ETH Zurich

Combining high-throughput molecular simulations, machine learning, and mixed-integer linear programming, the authors design peptides that localize to condensate interfaces, revealing surfactant-like, charge-dependent sequence rules.

That author's affiliation: Southern University of Science and Technology Institution (first & last author): Southern University of Science and Technology

Fu and colleagues present LUNAR, a self-supervised neural-physics method that reconstructs 3D molecular positions and optical aberrations directly from raw microscopy data, enabling calibration-free super-resolution imaging in complex biological samples.

Here, the authors show that the interplay of oxygen vacancies and erbium emitters in bismuth oxyhalides enables reversible, high-contrast switching of upconversion emission, offering a new strategy for high-level anticounterfeiting.

Near-optimal discrimination of displaced squeezed binary signals using displacement, inverse-squeezing, and photon-number-resolving detection

Quantum-enhanced federated blockchain for privacy-preserving cardiovascular intelligence

That author's affiliation: National Taiwan University Institution (first & last author): National Taiwan University

Generalized Toffoli gates with customizable single-step multiple-qubit control

That author's affiliation: University of Lethbridge Institution (first & last author): University of Lethbridge

Max Planck introduced units of length, time and mass defined solely in terms of fundamental constants. As Saurya Das explains, these units define a system in which quantum mechanics, relativity, gravity and thermodynamics meet on equal footing.

That author's affiliation: Institut Català de Nanociència i Nanotecnologia First author institution: Eindhoven University of Technology Last author institution: Institut Català de Nanociència i Nanotecnologia

The combination of viscous heat flow and thermoelastic effects leads to a non-diffusive heat transport regime in MoSe2 and MoS2. Moreover, it can be controlled through the variation in sample thickness and by choosing between continuous and pulsed heating.

How magnetic impurities influence superconductivity and electronic order in kagome metals remains unclear. Now anisotropic Kondo resonances intertwined with the superconducting gap are observed in a magnetically doped kagome superconductor.

A comprehensive review of how spectrum congestion, dynamic sharing, and cognitive radio systems are reshaping RF coexistence testing for military and commercial applications.

What Attendees will Learn

1. Why spectrum congestion threatens wireless reliability — Explore how over 30 billion connected devices, more than 4,000 allocation changes worldwide, and the expansion from 11 to over 80 cellular bands are intensifying contention for finite RF spectrum resources.
   
2. How real-world coexistence failures affect safety-critical systems — Understand the interference risks between 5G C band transmitters and aircraft radar altimeters, and between terrestrial L band networks and GPS receivers that were not designed for adjacent high-power signals.
3. Why tiered spectrum sharing frameworks are essential — Examine how CBRS uses a cloud-based Spectrum Access System (SAS) and environmental sensing to dynamically protect incumbent Navy radar while enabling commercial cellular services across three priority tiers.
4. What coexistence test architectures look like in practice — Learn how controlled environment testing with anechoic chambers, over-the-air signal generation, and standards such as ANSI C63.27 enable repeatable evaluation of RF device performance under real-world interference conditions.

This sponsored article is brought to you by Applied Materials.

At pivotal moments in history, progress has required more than individual brilliance. The most consequential breakthroughs — such as those achieved under the Human Genome Project — required a new operating paradigm: Concentrate the world’s best talent around a single mission, establish a common platform, share critical infrastructure, and collapse feedback loops. When stakes are high and timelines are compressed, sequential and siloed innovation simply cannot keep pace.

Today’s AI era is creating an engineering race with similar demands. Every company is pushing to deliver higher-performance AI systems, faster. But performance is no longer defined by compute alone. AI workloads are increasingly dominated by the movement of data: In many cases, moving bits consumes as much — or more — energy than compute itself. As a result, reducing energy per bit can extend system‑level performance alongside gains in peak compute.

The path to energy‑efficient AI therefore runs through system‑level engineering, spanning three tightly interconnected domains:

• Logic, where performance per watt depends on efficient transistor switching, low‑loss power, and signal delivery through dense wiring stacks.
• Memory, where surging bandwidth and capacity demands expose the memory wall, with processor capability advancing faster than memory access.
• Advanced packaging, where 3D integration, chiplet architectures, and high‑density interconnects bring compute and memory closer together — enabling system designs monolithic scaling can no longer sustain.

These domains can no longer be optimized independently. Gains in logic efficiency stall without sufficient memory bandwidth. Advances in memory bandwidth fall short if packaging cannot deliver proximity within thermal and mechanical constraints. Packaging, in turn, is constrained by the precision of both front‑end device fabrication and back‑end integration processes.

In the angstrom era, the hardest problems arise at the boundaries — between compute and memory in the package, front‑end and back‑end integration, and the tightly coupled process steps needed for precise 3D fabrication. And it is precisely this boundary‑driven complexity where the traditional innovation model breaks down.

The Traditional R&D Workflow Is Too Slow for Angstrom‑Era AI

For decades, the semiconductor industry’s R&D model has resembled a relay race. Capabilities are developed in one part of the ecosystem, handed off downstream through integration and manufacturing, evaluated by chip and system designers, and only then fed back for the next iteration. That model worked when progress was dominated by relatively modular steps that could be scaled independently and simply dropped into the manufacturing flow.

But the AI timeline has upended these rules. At angstrom‑scale dimensions, the physics enforces inescapable coupling across the entire stack: materials choices shape integration schemes; integration defines design rules; design rules dictate power delivery; wiring sets thermal budgets; and thermals ultimately constrain packaging scaling. System architects simply cannot wait 10–15 years for each major semiconductor technology inflection to mature.

Representing a roughly $5 billion investment, EPIC is the largest commitment to advanced semiconductor equipment R&D in U.S. history.

A long‑term perspective is essential to align materials innovation with emerging device architectures — and to develop the tools and processes required to integrate both with manufacturable precision. At Applied Materials, together with our customers, we are charting a course across the next 3–4 generations, extending as far as 10 years down the roadmap.

The angstrom era demands that we break down silos and bring together the industry’s best minds — from leading companies to leading academic institutions. If the problem is coupled, the solution must be coupled. If the timeline is compressed, the learning loop must be compressed. It’s not enough to just innovate — we must innovate how we innovate.

EPIC: A Center and Platform for High‑Velocity Co‑Innovation

This is the challenge that Applied Materials EPIC Center is designed to solve.

Representing a roughly US $5 billion investment, EPIC is the largest commitment to advanced semiconductor equipment R&D in U.S. history. When it opens in 2026, it will deliver state‑of‑the‑art cleanroom capabilities built from the ground up to shorten the path from early‑stage research to full‑scale manufacturing. But the facilities are only one component of the model. EPIC is also a platform, an operating system for high-velocity co‑innovation that revolutionizes how ideas move from the lab to the fab.

EPIC is a platform, an operating system for high-velocity co‑innovation that revolutionizes how ideas move from the lab to the fab.Applied Materials

The EPIC model compresses the traditional workflow. Customer engineers work side‑by‑side with Applied technologists from day one — moving beyond isolated process optimization and downstream handoffs. Within a shared, secure environment, EPIC tightly integrates atomistic modeling, test vehicles, process development, validation, and metrology feedback. Constraints that once surfaced late in development are identified and addressed early.

The result is a potentially 2x faster path that benefits the entire ecosystem under one roof:

• Chipmakers gain earlier access to Applied’s R&D portfolio, faster learning cycles, and accelerated transfer of next‑generation technologies into high‑volume manufacturing.
• Ecosystem partners gain earlier access to advanced manufacturing technology and collaboration opportunities that expand what is possible through materials innovation.
• Academic institutions gain opportunities to strengthen the lab‑to‑fab pipeline and help develop future semiconductor talent.

Building on decades of co‑development, we are reinventing the innovation pipeline with our partners across logic, memory, and advanced packaging to deliver the next leap in energy‑efficient AI.

Accelerating Advanced Logic

Logic remains the engine of AI compute. In the angstrom era, however, system‑level gains are increasingly constrained by power and energy. Extending AI performance now depends on architectures that deliver more performance per watt — accelerating the move to 3D devices such as gate‑all‑around (GAA) transistors, which boost density within a compact footprint while preserving power efficiency.

These architectural shifts are unfolding at unprecedented scale, with the logic roadmap already extending beyond first‑generation GAA toward more advanced designs. One key example is GAA with backside power delivery, which relocates thick power lines to the backside of the wafer, reducing resistive losses and freeing front‑side routing for tighter logic cell integration. Another example brings adjacent GAA PMOS and NMOS transistors closer together while inserting a dielectric isolation wall between them to minimize electrical interference. Further out, complementary FETs (CFETs) push density scaling even more by stacking PMOS and NMOS devices directly atop one another.

While these architectures deliver compelling gains in performance per watt and logic density without relying solely on tighter lithography, they significantly raise integration complexity. Manufacturing a single GAA device today can involve more than 2,000 tightly interdependent process steps. At the same time, wiring stacks continue to grow taller and denser to connect these advanced logic devices. Modern leading‑edge GPUs now in development pack more than 300 billion transistors into an area little larger than a postage stamp, interconnected by over 2,000 miles of wiring.

At this level of complexity, the process steps used to create these precise 3D devices and wiring stacks cannot be optimized independently. Design and process must evolve in lockstep, and materials innovation and fabrication methods must advance alongside device architecture. EPIC’s co‑innovation model is designed to accelerate exactly this convergence — enabling logic compute to continue advancing the frontiers of AI at the pace the roadmap demands.

Powering the Memory Roadmap

At the same time, the AI computing era is fundamentally reshaping how data is generated, moved, and processed — making memory technologies, especially DRAM, central to delivering the energy‑efficient performance AI systems require. As models grow larger and more data‑hungry, the DRAM roadmap is shifting toward architectures that deliver higher density, greater bandwidth, and faster access per watt.

At the DRAM cell level, this shift is driving a transition from 6F² buried‑channel array transistors (BCAT) to more compact 4F² architectures, which orient the transistor vertically to boost density and reduce chip area. Looking beyond 4F², sustaining gains in performance per watt will require moving past what 2D scaling alone can deliver. The industry is therefore turning to 3D DRAM, stacking memory cells vertically to add capacity within a constrained footprint. As these structures grow taller and aspect ratios intensify, high-mobility materials engineering in three dimensions becomes increasingly critical to performance and reliability.

Beyond the memory cell array, another powerful lever for DRAM scaling is shrinking the peripheral circuitry, which includes logic transistors and interconnect wiring. One emerging approach places select periphery functions beneath the DRAM array by bonding two wafers — one optimized for the DRAM cells and the other for CMOS logic — using multiple wiring layers.

In parallel, DRAM performance is being extended by leveraging logic‑proven enhancers in the memory periphery. These include mobility boosters such as embedded silicon germanium and stress films, along with wiring upgrades like improved low‑k dielectrics and advanced copper interconnects. Memory manufacturers are also transitioning periphery transistors from planar devices to FinFET architectures, following the logic roadmap to further improve I/O speed. These valuable inflections are central to EPIC’s mission — where they can be co-developed and rapidly validated for next‑generation memory systems.

Driving System Scaling With Advanced Packaging

As data movement becomes the dominant energy cost in AI systems, advanced packaging has emerged as a critical lever for improving system‑level efficiency—shortening interconnect distances, increasing bandwidth density, and reducing the power required to move data between logic and memory.

High‑bandwidth memory (HBM) marks a major inflection along this path. By stacking DRAM dies — scaling to 16 layers and beyond — and placing memory much closer to the processor, HBM enables rapid access to ever‑larger working datasets. This delivers step‑function gains in both bandwidth and energy efficiency.

More broadly, the rise of 3D packages such as HBM underscores why advanced packaging is becoming central to the AI era. Packaging now addresses system‑level constraints that logic and memory device scaling alone can no longer overcome. It also enables a move away from monolithic systems‑on‑chip toward chiplet‑based architectures, as AI workloads increasingly demand flexible designs that combine logic, memory, and specialized accelerators optimized for specific tasks.

A vital technology powering this roadmap is hybrid bonding. With interconnect pitches approaching those of on‑chip wiring, conventional bumps and microbumps run into fundamental limits in density, power, and signal integrity. Hybrid bonding removes these barriers by allowing dramatically higher interconnect and I/O density, supporting a broad range of chiplet architectures — from memory stacking to tighter compute‑memory integration.

As bonded structures like HBM stacks grow larger and more complex, warpage control, die placement, stack alignment, and thermal management become first‑order challenges. EPIC tackles these and other high‑value advanced‑packaging challenges through early, parallel co‑innovation across materials, integration, and manufacturing.

Bringing It All Together

Across logic, memory, and advanced packaging, our industry faces an ambitious roadmap that promises significant gains in energy efficiency for AI systems. But realizing that potential demands breakthrough materials innovation at a time when feature sizes are shrinking, interfaces are multiplying, and process interdependencies are escalating. These challenges cannot be solved on 10–15‑year timelines under the traditional relay‑race model. We must break down silos, align earlier across the ecosystem, and parallelize learning to keep pace with AI’s demands.

In the AI era, progress will be defined by the speed at which lightbulb moments turn into manufacturing and commercialization reality. The only viable path forward is a new innovation model — and EPIC is how we are driving it.

Squeezed light can improve optical phase measurements but usually needs careful calibration. Here, authors demonstrate a self-calibrating adaptive method that jointly estimates phase and squeezing, achieving quantum-enhanced precision from scratch across the full phase range.

Quantum magic dynamics in random circuits

High-performance continuous-variable quantum secret sharing using a state-discrimination detector

Quantum computational sensing using quantum signal processing, quantum neural networks, and Hamiltonian engineering

Practical blueprint for low-depth photonic quantum computing with quantum dots

An ultrafast imaging technique captured the propagation of charge-decoupled excitations in twisted bilayer WSe2. Two spin–valley modes with distinct propagation behaviours were revealed, consistent with the phase and amplitude modes of a spin–valley superfluid.

That author's affiliation: New York University First author institution: University of Oregon Last author institution: New York University

Government-controlled media influences the output of large language models via their training data, and models queried in the languages of countries with lower media freedom show a stronger pro-regime valence than models queried in the languages of countries with higher media freedom.

That author's affiliation: The University of Texas MD Anderson Cancer Center Institution (first & last author): The University of Texas MD Anderson Cancer Center

Treatment data for triple-negative breast cancer show the importance of macrophage subtypes and cancer-cell metaprograms for interferon signalling, HLA expression and cell cycle activity that are associated with a good response to neoadjuvant chemotherapy.

That author's affiliation: University of Science and Technology of China Institution (first & last author): University of Science and Technology of China

A programmable photonic quantum processor, Jiuzhang 4.0, incorporates 1,024 high-efficiency squeezed states into a hybrid spatial–temporal encoded 8,176-mode circuit.

That author's affiliation: Massachusetts Institute of Technology Institution (first & last author): Massachusetts Institute of Technology

Electron-beam control enables deterministic placement of tens of thousands of atomic defects in three-dimensional crystals, creating stable, programmable artificial matter for scalable quantum and nanoscale technologies.

That author's affiliation: University of Geneva Institution (first & last author): University of Geneva

Machine learning analysis of cell-type-specific gene expression in mouse and human neocortex and human cortical organoids reveals human-specific cell-type and temporal variations in expression controlled by JUNB.

That author's affiliation: Duke University Institution (first & last author): Duke University

Combining a computational framework and optogenetic and chemogenetic manipulations within and downstream of the cortico-basal ganglia circuit identifies the specific cortico-basal ganglia synapses that drive the acquisition and expression of rapid vocal changes during juvenile song learning.

That author's affiliation: University of North Texas Institution (first & last author): Vanderbilt University

Integration of data representing 35,120 brain scans from diverse global studies enables construction of reference charts that define normative microstructural and macrostructural properties across the human lifespan for research and clinical diagnosis.

That author's affiliation: University of Vienna Institution (first & last author): University of Vienna

An electron-beam technique that can precisely create thousands of atomic defects in a crystal could be used to build quantum devices.

Deviations from the textbook current–phase relationship of a Josephson junction can arise from the intrinsic physics of the junction, but also from the inductance of metallic traces. Now a scheme has been developed to distinguish these cases.

Non-Hermitian systems support non-trivial topological effects, yet eigenvalue braiding remains difficult to control and observe. Now, active tuning of laser modes enables programmable and directly observable braiding on an integrated photonic chip.

How angular momentum is exchanged and conserved among lattice modes has been difficult to measure experimentally, but has now been observed via a coherent three-phonon scattering process in a topological insulator.

Fe-based polyanionic cathodes are promising for large-scale Na-ion batteries but are limited by incomplete Na utilization. Now, research shows that tuning the local Na coordination via V substitution in phosphate-based cathode allows additional Na sites to participate, enabling near-complete Na utilization, enhancing energy density and cycling stability.

Fe-based polyanionic cathodes are promising for Na-ion batteries but are limited by inactive Na sites and irreversible Na loss. Here the authors employ targeted V3+ substitution to tune the Na+ coordination environment, activate inert sites and stabilize high-voltage redox for high-performance Na-ion batteries.

Electrocatalytic CO2 reduction is often hindered by the competing hydrogen evolution reaction, reducing selectivity for the desired products. Here the authors demonstrate that helical chiral copper electrodes can suppress hydrogen evolution by generating spin-polarized carriers through the chiral-induced spin selectivity effect.

UK Biobank breach prompts the field of genomics to rethink open science

Genomics and experimental data suggest that an evolutionary arms race between cholera-causing bacteria and their viral predators shapes the disease in humans.

Trust is no longer enough: secure data sharing requires international collaboration across institutions and governments.

That author's affiliation: Simon Fraser University Institution (first & last author): Simon Fraser University

Ancestral state inference methods are used to reconstruct host species transmission histories over time; however, these methods are biased by uneven sampling. The authors develop SAASI, a new ancestral state inference method that accounts for sampling bias.

That author's affiliation: Newcastle University Institution (first & last author): Newcastle University

Human methionine synthase, a cobalamin-dependent enzyme linking the methionine and folate cycles, shows a flexible architecture by cryo-EM. Computational and biophysical data reveal partner interactions key for cofactor loading and activation.

That author's affiliation: Soochow University Institution (first & last author): Soochow University

Soft tactile chips embed in-situ sensing in pneumatic actuators, improving teleoperation via adaptive haptic feedback. Liquid-metal pressure and pectin temperature sensors enable precise manipulation and better human-robot interaction.

That author's affiliation: Southern University of Science and Technology Institution (first & last author): Southern University of Science and Technology

Massive spatial superpositions are a resource for quantum interferometry, but it has been hard to generate them beyond single atoms. Now spatially entangled massive states are realized through the tunnelling of atomic clusters in optical lattices.

That author's affiliation: UNSW Sydney First author institution: UNSW Sydney Last author institution: University of Canberra

A tunable artificial crystal in a shallow GaAs quantum well is shown to enable interaction-driven insulating behaviour. Electrostatic control tunes the band structure from graphene-like to kagome-like bands.

That author's affiliation: University of Washington First author institution: Tata Institute of Fundamental Research Last author institution: University of Washington

Multidimensional spectroscopy probes both the electronic and nuclear degrees of freedom during and following ultrafast proton transfer, revealing vibronic dynamics that govern reaction coordinates and intramolecular vibrational redistribution.

That author's affiliation: Department of Chemistry First author institution: Department of Chemistry Last author institution: Chemical Biology and Biological Chemistry

Graph neural networks can predict ketosynthase substrate specificity

Authors show how voltage-gated sodium channels influence each other’s gating kinetics when localized in sufficient proximity to each other as part of clusters in the membrane. These nanoscale effects critically shape macroscopic physiology and drug response.

That author's affiliation: Nanyang Technological University Institution (first & last author): Nanyang Technological University

Researchers demonstrate field-free magnetisation switching in perpendicular magnetic anisotropy systems using spin reorientation and orbital Hall effects. This approach enables low power operation and scalable spintronic memory devices.

That author's affiliation: University of Cambridge Institution (first & last author): University of Cambridge

Precise characterisation of short tandem repeat expansions remains technically challenging. Here, Patiño-Guillén and colleagues present a single-molecule nanopore-based strategy that enables direct quantification of tandem repeats in native RNA.

The authors report that maternal RSV vaccination induces robust affinity-matured neutralizing antibodies in mothers and infants. Antibody transfer increased after 36 weeks, supporting current vaccination recommendations, and suggesting that early vaccination may benefit preterm-risk pregnancies.

Non-Markovianity and memory enhancement in quantum reservoir computing

Publisher Correction: Lifetime of the singly charged ²²⁹Th nuclear isomer

Efficient simulation of low-entanglement bosonic Gaussian states in polynomial time

Transport of charges has been widely studied in two-dimensional moiré materials. However, charge-neutral collective excitations are difficult to access, especially when they are decoupled from charged quasiparticles. Now they are observed in a moiré homobilayer.

The post What Causes Lightning? The Answer Keeps Getting More Interesting. first appeared on Quanta Magazine

That author's affiliation: School of Astronomy and Space Science, Nanjing University, Nanjing, China First author institution: School of Astronomy and Space Science, Nanjing University, Nanjing, China Last author institution: Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai, China

Formation of the Solar System’s comet reservoirs remain uncertain. Here, the authors show that AI-based analysis of comet activity reveals a far more populated Oort Cloud than previously thought.

That author's affiliation: College of Chemistry, Zhengzhou University, Zhengzhou, Henan, 450001, China Institution (first & last author): College of Chemistry, Zhengzhou University, Zhengzhou, Henan, 450001, China

Traditional electrolytes are electrochemically unstable on the positive electrode surface. Here, the author designed a solvent locked electrolyte to form a stable boride/fluoride interface. The assembled Na||Na2.26Fe1.87(SO4)3 battery maintained 88.2% capacity after 16500 cycles at 1 A g-1.

That author's affiliation: Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences (CAS), Ningbo, China First author institution: Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences (CAS), Ningbo, China Last author institution: School of Materials Science and Engineering, Taizhou University, Taizhou, China

Self-assembled monolayers struggle to uniformly coat textured surfaces, limiting high-efficiency perovskite and silicon tandem solar cells. Du et al. increase surface hydroxyl groups by incorporating carbon into polysilicon, enabling stable monolayer attachment and record device efficiency.

That author's affiliation: Paderborn University, Integrated Quantum Optics, Institute for Photonic Quantum Systems (PhoQS), Paderborn, Germany Institution (first & last author): Paderborn University, Integrated Quantum Optics, Institute for Photonic Quantum Systems (PhoQS), Paderborn, Germany

Bridging chemistry and Gaussian boson sampling: a photonic hierarchy of approximations for molecular vibronic spectra

That author's affiliation: Shanghai Key Laboratory of Superconductor Integrated Circuit Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China First author institution: Shanghai Key Laboratory of Superconductor Integrated Circuit Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China Last author institution: Shanghai Research Center for Quantum Sciences, Shanghai, China

Multiuser entanglement distribution network across cryogenic nodes enabled by integrated photonic chips