Physics

SWI/SNF chromatin remodeling complexes are perturbed in 20% of all cancers and in several developmental disorders, yet the mechanisms by which these mutations dysregulate transcription and drive disease are poorly understood. To both elucidate these mechanisms and identify vulnerabilities caused by these mutations, we leverage genome-wide CRISPR-Cas9 screening in hundreds of cancer cell lines and identify the chromatin reader protein PHIP as a specific dependency in cancers with broadly disrupted SWI/SNF function. Mechanistically, we reveal that PHIP cooperates with SWI/SNF to facilitate transcriptional activation by ubiquitinating and suppressing subunits of the repressive Nucleosome Remodeling and Deacetylase (NuRD) complex. We demonstrate that loss of SWI/SNF results in NuRD complexes accumulating at promoters where they would otherwise cause widespread transcriptional silencing if not antagonized by PHIP. Collectively, we identify PHIP as a regulator of the interplay between distinct chromatin regulators that function in development and disease and as a targetable vulnerability in cancers with broad SWI/SNF inactivation.

The nature of the pseudogap state is widely believed as a key to understanding the pairing mechanism underlying unconventional superconductivity. Although pseudogap states have recently been realized in moiré systems with extensive gate tunability, their local electronic structure remains largely unexplored. Here we show gate-tunable spontaneous symmetry breaking and shifting behavior of the pseudogap state in magic-angle twisted bilayer graphene using spectroscopic imaging scanning tunneling microscopy. A pronounced pseudogap emerges over a broad doping range and exhibits strong spatial modulation at the moiré scale. Spectroscopic imaging highlights a gap size modulation at moiré scale that is sensitive to the filling, indicative of a wave-like pseudogap feature. At certain dopings, the pseudogap size distribution causes a clear nematic order, or an anisotropic gap distribution. Our results have shed light on the complex nature of this pseudogap state, revealing critical insights into the phase diagram of correlated electron systems.

CD8⁺ T stem cell memory (T_SCM) cells show clinical promise for cancer immunotherapy, but T_SCM cell generation in clinical settings requires further optimization. Ponatinib is a tyrosine kinase inhibitor primarily targeting BCR-ABL1 and used for the treatment of chronic myeloid leukemia. Here, we investigate the effect of ponatinib on T cell activation and differentiation. Acting off-target, ponatinib inhibits LCK and PI3K signaling to enhance the transcriptional functions of TCF7 and FOXO1, thereby promoting CD8⁺ T_SCM cell differentiation. Mechanistically, stable and sustained, but not intermittent, inhibition of the LCK and PI3K pathways is essential for CD8⁺ T_SCM cell induction. In mouse tumor models, ponatinib treatment exhibits antitumor efficacy alone and in combination with PD-1 blockade. Furthermore, ponatinib increases chimeric antigen receptor (CAR) T_SCM cells by reducing CAR T cell exhaustion, resulting in durable antitumor efficacy. Our results thus implicate ponatinib as therapeutic immunomodulator, inducing T_SCM cells for improved antitumor T cell activity.

Lactate significantly accumulates in intervertebral disc degeneration (IVDD) to promote inflammation storm and nucleus pulposus cells (NPCs) senescence. However, eliminating the lactate efficiently and inhibiting the inflammation storm and NPCs senescence stimulated by lactate remains a challenge. Here, we show a lactate metabolism reprogramming reactor, which converts lactate to the inhibitor of NPCs senescence (alanine) through orthogonal tandem catalysis (OTC) reaction, thereby guiding the lactate metabolism reprogramming. Enzymes and substrates are encapsulated to prepare OTC nanoparticles, which are embedded in hydrogel microspheres to form the reactors. The lactate metabolism reprogramming efficiently performs in vitro and sustainably conducts in vivo to down-regulate lactate to reduce NLRP3 activity and up-regulate alanine to decrease oxidative stress, significantly inhibiting the inflammatory storm and NPCs senescence. The biomechanical function of neo-generated tissues reaches 94% of that of normal tissues, showing clinical potentials in reversing the IVDD.

Fluorophosphates have garnered widespread attention in potassium-ion batteries due to their robust three-dimensional frameworks and high operating voltage. However, their practical implementation is restricted by inherent limitations, including low conductivity and an unstable cathode electrolyte interface. Herein, we propose an interfacial electric field regulating strategy to stabilize the cathode electrolyte interface of the KVPO₄F positive electrode material. Based on theoretical calculations and in situ characterization, we find that the enhanced interfacial electric field can simultaneously optimize the transport of electrons and K⁺, improve the stability of the crystal structure, and facilitate the formation of a thin (~2.7 nm), stable cathode electrolyte interface layer. The designed composite material of KVPO₄F and nitrogen-doped carbon nanotubes achieves a high specific energy of 454.8 Wh kg^-1 (based on the mass of the positive electrode) in the voltage window of 2.0-5.0 V at 0.5 C (1 C = 131 mA g^-1). The relevant full cell also exhibits good cycling stability, with a capacity retention of 80.6% after 2000 cycles at 1 C. Furthermore, this interfacial electric field regulation strategy can also be extended to other polyanionic systems such as KFeSO₄F and KTiPO₄F, demonstrating practical application potential. This study elucidates an interfacial electric field regulation approach and provides alternative insights for the development of high-energy-density and long-cycle-life potassium-ion batteries.

The selection and acquisition of suitable raw material constitute the first steps in stone tool technology. Previous ethnographical and archaeological research suggests that hominins in the Pleistocene primarily collected their stone materials while carrying out other activities. Direct provisioning for this purpose alone remains an outlier and is rarely demonstrated. Archaeological excavations coupled with multidisciplinary analyses at Jojosi in South Africa demonstrate that early modern humans undertook specific, repeated visits to a raw material source over tens of thousands of years for the exclusive purpose of obtaining hornfels. This rare, stratified, open-air locality features uniquely preserved lithic assemblages with abundant refits dating from ~220 ka to ~110 ka for the reduction and export of a single tool stone. The scope of these knapping activities is underscored by millions of Middle Stone Age hornfels artefacts paving the modern landscape. The consistent, specialised procurement of a single raw material at Jojosi already during the Middle Pleistocene challenges the standard model of embedded procurement for this period. These findings further show that key capacities of Homo sapiens, including increased long-term planning and behavioural plasticity in the interaction with the material world, emerged early in their evolutionary history.

The NAD⁺ cap has been discovered in RNAs across prokaryotes and eukaryotes, suggesting a possible role of NAD capping in gene regulation. Current NAD-capped RNA (NAD-RNA) profiling methods lack precision in 5'-end mapping or bias against small NAD-RNAs. Here, we introduce precision NAD-RNA sequencing (pNAD-seq), which combines a two-step enrichment strategy with high-throughput sequencing to achieve single-nucleotide resolution of 5'-ends and unprecedented sensitivity for identifying small NAD-RNAs. We further develop NAD-linkSeq to determine full-length NAD-RNA sequences. Applying these methods to E. coli, we uncover a vast repertoire of NAD-RNAs, including tRNAs, rRNAs, intragenic transcripts, and antisense RNAs, many of which are significantly shorter than regular mRNAs, implying specialized biogenesis. High-resolution mapping reveals conserved promoter architectures driving NAD-RNA production and condition-dependent initiation dynamics: under nitrogen limitation, some NAD-RNA undergo TSS switching, alternative promoter usage, and coordinated expression shifts, correlating with metabolic stress responses. This report presents findings that offer a comprehensive view of NAD-RNAs in E. coli and introduces reliable methods for genome-wide profiling of NAD-RNAs across different organisms, which will facilitate the functional characterization of NAD-capping.

Alterations in synaptic homeostasis are linked to cognitive and behavioural impairments in brain disorders. However, synaptic dysfunction in childhood dementia is poorly understood. Here, we generate human cortical circuits from induced pluripotent stem cells (iPSCs) derived from donors with Mucopolysaccharidosis Type IIIA (MPS IIIA), also known as Sanfilippo syndrome, a common form of childhood-onset dementia. Action potential firing capacity and morphology of MPS IIIA patient neurons in culture are similar to those of neurons from neurotypical donors. However, long-term neural maturation reveals excitation/inhibition imbalances caused by hyperactive excitatory synapses, disrupted network dynamics, and dysregulated gene expression linked to synaptic homeostasis. This study validates in vitro human neural models to detect neurophysiological phenotypes in childhood dementias and supports drug discovery strategies that target synaptic dysfunction to improve cognition in MPS IIIA and related brain disorders.

Implantable neurotechnologies are increasingly used to reduce seizure burden in pediatric epilepsy. Vagus nerve stimulation (VNS), the most common option, is effective for only half of patients, with no means to predict outcome prior to surgery. As a result, many children undergo invasive and costly procedures without benefit. Although T1-weighted magnetic resonance imaging (T1w) is routinely acquired presurgically and may capture structural brain differences relevant to treatment outcome, its high dimensionality relative to sample sizes has limited its utility in predictive modelling. To address this challenge, we present VQ-VNS, a deep representation learning model to predict VNS outcome based on preoperative T1w (n = 263). First, we present data from the largest paediatric VNS cohort (n = 1046), wherein presurgical clinical data could not predict response (AUC 0.54,p > 0.99). Next, VQ-VNS was pretrained on 7433 T1w images to learn compact anatomical representations enabling its classifier to predict VNS response (AUC = 0.73,p = 0.007). Model predictions localized to serotonin-rich brain regions and inferred large-scale disruptions in network connectivity among non-responders. This biologically interpretable predictor based on routine structural imaging improves upon current clinical decision-making.

Achieving superior tribo-negative performance beyond traditional fluorinated polymers (TFPs) is crucial for advancing triboelectric devices. In this work, we identified an approach to enhance the tribo-negative properties of TFPs via synergistic effects of C-F and C-Cl bonds, based on the significant tribo-differences observed in polyvinylidene fluoride (PVDF) based copolymers. Our findings indicate that the -CTFE unit, particularly its C-Cl bond, significantly lowers the LUMO of the copolymer system, resulting in PVDF-CTFE (PC) exhibiting the strongest tribo-negative properties. By controlling the surface Cl/F ratio via chlorine plasma treatment, it was demonstrated that a higher C-Cl content enhances electron acquisition, whereas a higher C-F content improves charge retention. The synergistic effect optimally balances triboelectric charge capture and losses, enabling PC-Cl to achieve the highest triboelectric charge density (310 µC cm^-2) among PVDF copolymers. Our results will provide a versatile strategy for enhancing a wide range of tribo-negative materials.

Deep learning has demonstrated remarkable success in augmenting fluorescence imaging under photon-limited conditions. However, existing restoration networks are typically devised for training with augmented patches far smaller than the full-view raw data, an overlooked aspect that compromises fidelity and noise-resistance due to the loss of global statistics. To address this limitation, we propose a large-patch network (LargePNet), which synergizes the large effective receptive field provided by shallow ultra-large-kernel convolutions and the nonlinear representation capabilities of deep networks through scale separation. It effectively and efficiently leverages large-view global information for restoration. Directly trained with large-view images, LargePNet shows contrasting advantages over state-of-the-art small-patch networks, with 0.5-2 dB higher peak signal-to-noise ratio across eight representative restoration tasks, involving implementations for single-image, video, and volumetric fluorescence data. For full-view processing, LargePNet generally holds around 4-fold and 20-fold higher computational efficiency compared to advanced convolution-based and Transformer-based networks, respectively. The assistance of LargePNet helps achieve 30-hour-long fluorescence imaging to monitor cytoskeleton dynamics, and hour-long tri-color super-resolution imaging to investigate organelle interaction, showcasing its advancement in live-cell imaging.

Oocyte-specific isoforms play crucial roles in oocyte maturation, while current understanding of the oocyte transcriptome is mainly focused on gene level. Here, we utilize single-cell full-length isoform sequencing to detect entire transcripts in human and mouse oocytes. Isoform diversity during oocyte maturation is systematically profiled, including 7154 and 4875 putative novel human and mouse transcripts, respectively. More than half of novel isoforms are categorized as novel-not-in-catalog (NNC) and may serve specific functions in oocytes. For example, ARHGAP18 mainly encoded by novel isoforms colocalizes with microtubules, and targeted knockdown of novel isoforms disrupts oocyte maturation. Moreover, approximately 30% of NNC isoforms are derived from transposable elements, and their incorporation within transcripts could enhance isoform stability during oocyte maturation. Altogether, our findings represent a valuable resource showcasing the complexity and diversity of RNA isoforms in oocytes, as well as transposable element co-option for novel isoform generation and isoform stability enhancement.

Organic electrode materials, despite their elemental abundance, environmental friendliness, and design flexibility, often suffer from limited electronic and ionic conductivities, which restrict their practical applications. Here, we present a universal thiourea coupling strategy that improves both electron and ion transport in quinone-based organic electrodes. Taking phenanthrenequinone as a representative example, thiourea incorporation increases the electron density of the quinones and improves the overall electronic conductivity of the electrode material. Meanwhile, thiourea establishes continuous proton-transport pathways, enabling proton-dominated redox reactions via a Grotthuss-type hopping mechanism. As a result, zinc batteries employing the coupled electrode exhibit stable cycling behavior over 6000 cycles at a low conductive carbon content (10 wt%) and maintain reliable operation in pouch-cell configurations under high mass loading conditions of 20 mg cm^-2. In addition, the applicability of this molecular coupling strategy is demonstrated across multiple quinone systems, paving that path towards practical organic electrode materials.

Organic-inorganic hybrid perovskites (OIHPs) offer a promising alternative, combining strong spin-orbit coupling, high carrier mobility, and tunable optoelectronic properties. However, their potential for spintronic applications has been constrained by rapid spin relaxation, often attributed solely to the inorganic sublattice. Here, we demonstrate room-temperature spin transport in hybrid perovskites enabled by isotope engineering. Substituting hydrogen with deuterium in methylammonium lead iodide effectively suppresses hyperfine interactions (HFI), leading to a 2.6-fold increase in spin lifetime. As a result, CD₃ND₃PbI₃ exhibits a magnetocurrent (MC) ratio of 17.5% at room temperature, whereas conventional CH₃NH₃PbI₃ spin-valve devices show negligible MC response. A spin photovoltaic effect is also observed under ambient conditions, revealing a coupling between optical excitation and spin-polarized transport, and pointing toward new opportunities for light-addressable spintronic functionality. These findings not only revise the fundamental understanding of spin relaxation in hybrid materials, but also establish isotope engineering as a powerful strategy to access room-temperature spin functionality.

Emergent topological spin textures, such as nanometric skyrmions and antiskyrmions, not only exhibit a wealth of novel physical phenomena but also represent promising candidates for next-generation spintronic devices due to their topological stability and low-current-driven dynamics. Investigating their responses to electric currents is essential for uncovering unique electromagnetic properties and advancing their integration into electronic technologies. While considerable progress has been made through extensive research over the past decade, key challenges still persist. In this study, we demonstrate the novel, current-driven oppositely rotating dynamics of skyrmion and antiskyrmion assemblies in terms of Lorentz transmission electron microscopy. Their senses of rotation are strongly dictated by their inherent topological charges and remain largely unaffected by current direction, showing consistent behavior observed across various sample geometries. Further experimental analyses have revealed a reduction in angular velocity as (anti)skyrmions move away from the sample edge. The theoretical analyses, combined with micromagnetic simulations, highlight the critical roles of boundary-induced confining potentials and gyrotropic forces in steering the rotational dynamics of (anti)skyrmions. These findings offer new insights into current-driven (anti)skyrmion dynamics and open promising avenues for advancing topological concepts in confined spintronic systems.

Developing additive manufacturing (AM) aluminum alloys with high temperature strength remains a formidable scientific challenge, primarily due to the strengthening precipitates coarsening above 200°C. Conventional heat-resistant alloy design strategies aim to hinder the precipitate coarsening by incorporating low diffusive alloying elements. However, such approaches remain ineffective against thermally driven defect mobilization, especially for vacancy diffusion and dislocation climbing, which are dominant drivers of high temperature weakening. As a result, most AM Al alloys exhibit a rapid decline in strength within this critical temperature range. Through reverse-engineering of intrinsic atom-defect/atom attraction, we employ an intrinsic attraction (IA) strategy to trigger multi-dimensional defect confinement mechanisms. This approach achieves: divacancy clusters anchoring free vacancies; solute atmospheres capturing mobile dislocations and suppressing creep deformation; specific segregation forming nanostructures at precipitate interfaces and interiors to inhibit coarsening. The AM heat-resistant Al alloy demonstrates satisfactory high temperature performance, exhibiting yield strengths of ~305 MPa at 300°C, ~190 MPa at 400°C, coupled with creep resistance at 200-400°C (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mover><mml:mrow><mml:mi>ε</mml:mi></mml:mrow><mml:mrow><mml:mo>°</mml:mo></mml:mrow></mml:mover></mml:math> < 10^-7/s) and prominent processability for large-size bladed disk. This strategy transcends the conventional empirical paradigm by engineering elemental segregation tendencies at specific sites, provides a universal design approach for the development of aluminum alloys or other high temperature structural materials.

Dynamical control of the nonlinear optical properties of solids - with light itself - will be essential for future ultrafast photonic technologies. Previously, methods to modulate nonlinear processes including second-harmonic generation (SHG) have relied primarily on non-resonant light-matter interaction or photo-generation of hot electrons in nanoscale materials. However, these approaches are typically constrained by limited interaction lengths and the initial frequency conversion is relatively weak under equilibrium conditions. Here, a ~ 30% modulation of efficient phase-matched SHG in bulk beta-barium borate (β-BaB₂O₄) is achieved through transient lattice deformation by intense terahertz (THz) pulses that are tuned to resonance with an infrared-active phonon mode. The effect originates from modification of the index of refraction ellipsoid and the corresponding nonlinear phase-matching conditions, rather than from direct modulation of the nonlinear susceptibility through THz-mediated <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mrow><mml:mi>χ</mml:mi></mml:mrow><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mn>3</mml:mn></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msup></mml:math> processes. This mechanism, of resonant selective lattice excitation, points toward novel THz-control schemes to tune the nonlinear optical response in materials.

The rapid growth of tropical cities and the rising challenges of climate change call for efficient, low-carbon energy systems. Solar photovoltaics could play a key role, but deployment in tropical climates is constrained by localized thunderstorms that cause rapid generation fluctuations and stress electricity grids. While electric vehicles could balance such fluctuations by acting as distributed energy storage, this potential has not been systematically explored. Here, using Singapore as a case study, we develop a decentralized, district-level vehicle charging strategy that aligns with urban mobility patterns inferred from mobile phone data. Contrary to conventional centralized charging strategies, our approach substantially reduces grid flows, enabling greater photovoltaic integration into the existing grid infrastructure. We further show that detailed urban mobility patterns are critical to the balancing performance of electric vehicle storage. Our results highlight the potential of coordinated photovoltaic and electric vehicle systems for large-scale solar energy deployment in tropical cities.

In Aotearoa New Zealand, Māori oral histories, ethno-historical accounts, and archaeological evidence indicate that kūmara (sweet potato; Ipomoea batatas) and taro (Colocasia esculenta) horticulture were key drivers of population growth and cultural change. We investigate diet, childhood residency, and chromosomal sex of Māori tūpuna (ancestors) who were discovered accidentally during roadworks in the Waikato region, an area with widespread evidence for intensive horticulture from the sixteenth century CE. The kōiwi tangata (human remains), dated to ca. 250-170 cal BP, were interred as a commingled secondary burial in a borrow pit during the Traditional Period of Māori history, a time characterized by highly distinctive art, architecture, cosmology, and whakapapa (genealogy). Using isotope and enamel peptide analyses we find that all seven tūpuna relied primarily on plant foods. Two children (chromosomally male and chromosomally female, respectively) were likely local and weaned onto plant foods within the first two to three years of life. These findings demonstrate that horticulture was central to life in the Waikato during the Traditional Period, to the extent that some individuals ate predominantly plant-based diets.

The ErCo₂ intermetallic compound exhibits a significant magnetocaloric effect at approximately 32 K and has potential applications as a magnetic refrigeration material for hydrogen liquefaction. However, exposure to a hydrogen atmosphere may lead to hydride formation, which weakens the magnetocaloric effect. Thus, preventing hydrogen permeation into ErCo₂ is crucial. Herein, we enhance the hydrogen permeation barrier (HPB) performance of ErCo₂ particles by using electroless Cu plating followed by oxidation treatment to form a CuO layer with a thickness of a few micrometers. In experiments, ErCo₂ particles, with a 1.5- to 5-µm-thick CuO surface layer, exhibited a large magnetic entropy change of 24 J kg⁻¹ K⁻¹ even after exposure to a H₂ atmosphere at 1.27 MPa and 296 K for 7 d. Experimental analyses and first-principles calculations revealed the potential of CuO as an HPB material for magnetic refrigeration.

Arc magmas are enriched in sulfur relative to mid-ocean ridge basalts, commonly attributed to slab-derived sulfur inputs during subduction. However, the contribution of slab fluids remains debated because sulfur concentrations in sub-arc fluids have not been directly measured. Here we quantify sulfur in slab-derived fluids preserved as multiphase fluid inclusions composed of H₂O, calcite, and chalcopyrite in omphacite from ultrahigh-pressure eclogites in the Sumdo orogenic belt. Three-dimensional Raman spectroscopy reveals high sulfur concentrations averaging ~6 wt.%. Mass-balance calculations indicate that such fluids can efficiently enrich the mantle wedge and supply up to ~70% of the sulfur emitted by arc volcanism. We further suggest that chalcopyrite formed through post-entrapment reduction of oxidized sulfur species by host omphacite, followed by precipitation with co-entrapped copper and iron. Our findings identify sub-arc depths as a critical window for slab sulfur release and provide key constraints on deep sulfur cycling and copper mobilization in arc systems.

Artificial intelligence-driven materials development has emerged as a powerful alternative to traditional trial-and-error methods. Despite its promise, these methods often struggle to uncover novel materials or generate actionable insights in emerging fields due to limited data availability. This challenge is particularly pronounced in electronic materials, where the intricate interplay of physical mechanisms and structure-property relationships impede progress. Here, we report a methodology combining Physical-Knowledge-Undergirded Transfer Learning for accurate property prediction with limited data, coupled with physical knowledge and artificial intelligence-driven hypothesis generation to yield scientific insights. Using this approach, we successfully identify low-voltage, high-performance organic electrochemical transistor materials and yield material design knowledge. The approach is experimentally validated through the synthesis of n-type polymers, demonstrating accurate property prediction and revealing critical structure-property relationships. We believe this approach can be applied to other emerging material systems with limited data availability and complex physical mechanisms, and accelerates the development of materials in emerging fields.

Strain-induced signal interference is a critical challenge limiting the reliability and functionality of electronic textiles in real-world, deformable environments. Mechanical deformation during motion or wear can distort signal fidelity, compromise sensing accuracy, and disrupt energy or data transmission-hindering the advancement of smart, adaptive wearables. Here, we introduce a strain-programmable fiber platform that turns mechanical strain from a liability into a tunable design feature. By embedding liquid metal (LM) particles within a polyurethane elastomer via coaxial wet spinning, we create composite fibers whose electromechanical responses can be precisely programmed-through pre-strain and composition-to exhibit negative, hybrid, or positive strain-resistance behaviors. This tunability arises from strain-induced LM particle reconfiguration, driven by a balance of geometric deformation and conductive network evolution, and captured through a hybrid parallel-series model. Leveraging this functionality, we demonstrate bidirectional strain sensors with polarity-based digital encoding and strain-invariant circuits for robust energy harvesting, wireless communication and thermal management. This programmable approach offers a scalable, material-level solution to strain interference, enabling high-performance, multifunctional e-textiles for next-generation wearable electronics.

Protein coacervates formed by liquid-liquid phase separation are emerging as active force generators, independent of ATP-driven motors. Nevertheless, the coordination and force scaling of protein coacervates remain largely unexplored. Here, we engineer a temperature-responsive elastin-based protocell model displaying temperature-modulated contractility and attendant force harnessing. By leveraging the phase separation properties, we modulate the protocell dynamics associated with volume contraction and membrane budding. Crosslinking of the elastin-based membrane influences the contraction dynamics such that the accumulation of mechanical forces in the protocells results in the spontaneous expulsion of internally trapped protein liquid-liquid phase separation (LLPS) complexes. We use a simple mathematically model to show how protein coacervation can amplify small piconewton-scale forces to perform large-scale mechanical work, highlighting the mechanical potential of protein coacervation dynamics. Taken together, our results provide a model framework for harnessing protein coacervates-driven forces and offer a step to future applications in synthetic biology, biomaterials and next-generation soft robotics.

Mercury is a persistent pollutant with significant public health impacts in polar regions where fish consumption drives human exposure. Atmospheric oxidation pathways control where mercury deposits globally, but the lack of molecular-level observations of oxidized mercury products has hindered the validation of proposed chemical mechanisms. Here, we show the in-situ online detection of individual mercuric halides (HgCl₂, BrHgCl, HgBr₂, ClHgI, BrHgI, and HgI₂) in the polar boundary layer using atmospheric pressure chemical ionization mass spectrometry. Our observations identify HgBr₂ as the dominant oxidized mercury species at both poles, while HgCl₂ and other halides were also observed in Antarctica. The observed speciation diverges from current model predictions, which favor HgCl₂ and HOHgBr as dominant oxidized forms. Our results show that real-time molecular measurements can substantially advance global mercury monitoring and improve the chemical models used to assess environmental policies and predict deposition patterns.