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363 records · Page 9

Real-space visualization of a defect-mediated charge density wave transition

Here, we study the coupled charge density wave (CDW) and insulator-to-metal transitions in the 2D quantum material 1T-TaS 2 . By applying in situ cryogenic 4D scanning transmission electron microscopy with in situ electrical resistance measurements, we directly visualize the CDW transition and establish that the transition is mediated by basal dislocations (stacking solitons). We find that dislocations can both nucleate and pin the transition and locally alter the transition temperature T c by nearly ~75 K. This finding was enabled by the application of unsupervised machine learning to cluster five-dimensional, terabyte scale datasets, which demonstrate a one-to-one correlation between resistance—a global property—and local CDW domain-dislocation dynamics, thereby linking the material microstructure to device properties. This work represents a major step toward defect-engineering of quantum materials, which will become increasingly important as we aim to utilize such materials in real devices.

4D-STEM

Gold Catalyzed Polymerization Reactions of Unsaturated Substrates: Towards New Functional, Recyclable, and Upcycled Aromatic Polymers (Final Report)

The overarching goal of this project lied in the translation of gold (Au) catalyzed small molecule synthetic transformations to the field of polymer science, the generation of new macromolecular structures, and the application of the materials and methodologies produced toward sustainable polymer development and chemical upcycling. Specifically, this project aimed to polymerize monomers based on unsaturated precursors and access novel polymeric materials through the extension of Au catalyzed intermolecular processes. The specific objectives of this project comprised: (1) the extension of Au-catalyzed intermolecular reactions to bifunctional monomers and the polycondensation of diverse nucleophiles; (2) to gain fundamental mechanistic insight into Au-catalyzed polymerizations; (3) the application of these reactions to the synthesis of new classes of aromatic polymers that can be readily and/or selectively deconstructed; and (4) to apply these chemistries to post-polymerization modification (PPM) of commercially relevant polyaromatic substrates, including post-industrial plastics and post-consumer waste.

36 MATERIALS SCIENCE

Thermal partition function of $$ {J}_3{\overline{J}}_3 $$ deformed AdS3

Abstract We derive a compact formula for the one-loop, bosonic string partition function of Euclideanized$$ {J}_3{\overline{J}}_3 $$ J 3 J ¯ 3 deformedAdS 3 with periodic Euclidean time as an integral transform of the partition function of the undeformed EuclideanizedAdS 3 . Such a deformation is interpretable as an irrelevant “single-trace$$ T\overline{T} $$ T T ¯ deformation” of the boundary. We will do this by first establishing a formal procedure to compute a worldsheet torus zero point function for an exactly marginal$$ J\overline{J} $$ J J ¯ deformation of a sigma model with U(1) L × U(1) R global symmetry. We then describe how this procedure is implemented on SL(2,R) sigma model and its Euclidean continuation. Finally, we describe the embedding of the deformed SL(2,R) torus amplitude into critical string theory and interpret the result as the leading perturbative contribution to the thermal partition function of the deformed theory.

Physics

Final Report: Process Intensification of Hydrogen Production through Sorption-Enhanced Gasification of Biomass

The University of Utah, in partnership with Idaho National Laboratory (INL), evaluated Sorption-Enhanced Gasification (SEG) as a transformative pathway for producing hydrogen with the potential for negative CO 2 emissions. SEG integrates gasification, water-gas shift, and in-situ carbon capture within a dual fluidized bed reactor to enable efficient clean hydrogen production. Key challenges related to biomass variability and process complexity were addressed through feedstock engineering, reaction optimization, and process validation. A co-pelletized biomass–limestone feedstock was developed to simplify feeding and introduction of makeup limestone. Kinetic and sorbent studies identified optimal operating conditions and confirmed the suitability of low-cost limestone, while catalysts were developed to reduce tar formation. Reactor modeling and techno-economic analysis indicated that SEG can achieve competitive hydrogen production costs, particularly when combined with carbon incentives, supporting its potential for scale-up and carbon-negative operation.

08 HYDROGEN

UL 1741SC Conformance Development, Evaluation, and Proposal [Slides]

V2G AC is a type of grid interconnection by mobile battery that transforms an EV into a DER with the potential to stabilize the grid and lower costs for electricity. UL 1741SC is a critical new standard to enable grid interconnection of V2G AC-capable vehicles, by defining requirements for V2G AC-intended EVSEs as a gatekeeper between the grid and the EV to support grid safety, such as through redundant voltage trip (namely oversight). EVSE manufacturers need a clear set of conformance test cases and criteria by which to evaluate their equipment and confirm the compliance with UL 1741SC, so that the EVSEs performs as intended for the grid safety. Hence, NLR identified necessary conformance tests and performed the tests identified to understand the maturity.

29 ENERGY PLANNING, POLICY, AND ECONOMY

Echo state network for coarsening dynamics of charge density waves

An echo state network (ESN) is a type of reservoir computer that uses a recurrent neural network with a sparsely connected hidden layer. Compared with other recurrent neural networks, one great advantage of ESN is the simplicity of its training process. Yet, despite the seemingly restricted learnable parameters, ESN has been shown to successfully capture the spatial-temporal dynamics of complex patterns. Here we build an ESN to model the coarsening dynamics of charge-density waves (CDWs) in a semiclassical Holstein model, which exhibits a checkerboard electron density modulation at half-filling stabilized by a commensurate lattice distortion. The inputs to the ESN are local CDW order parameters in a finite neighborhood centered around a given site, while the output is the predicted CDW order of the center site at the next time step. Special care is taken in the design of couplings between hidden layer and input nodes to ensure lattice symmetries are properly incorporated into the ESN model. Since the model predictions depend only on CDW configurations of a finite domain, the ESN is scalable and transferrable in the sense that a model trained on dataset from a small system can be directly applied to dynamical simulations on larger lattices. Furthermore, our work opens avenues for efficient dynamical modeling of pattern formations in functional electron materials.

2-dimensional systems

Block-Type Antiferromagnetism in Single Chain Quasi-One-Dimensional K 3 ⁢Fe 2 ⁢Se 4

One-dimensional (1D) structures provide a unique platform to study the correlated quantum interactions and phase transitions such as unconventional magnetism and superconducting states. Here, we report that iron chalcogenide K 3 ⁢Fe 2 ⁢Se 4 exhibits an unusual block-type canted antiferromagnetic (AFM) order with a clear single chain quasi-1D structure, which is structurally different from the two-leg ladder BaFe 2 ⁢Se 3 , through both experimental measurements and density matrix renormalization group (DMRG) calculations. The narrow bandgap semiconductor K 3 ⁢Fe 2 ⁢Se 4 has a quasi-1D edge-shared FeSe4 tetrahedra chain structure and orders antiferromagnetically below 110 K. The magnetic moments couple antiferromagnetically along the quasi-1D chain direction of the 𝑏 axis and form an up-down-down-up (↑−↓−↓−↑)–like spin structure with a commensurate propagation vector 𝒌=⁢(0,0,0), where block-type spin ↑−↑ or ↓−↓ coupling are between the longer Fe-Fe bonds of the quasi-1D chain. DMRG results show that block antiferromagnetic state is stable in K 3 ⁢Fe 2 ⁢Se 4 and reveal that the block-ordered arrangement of Fe 2.5+ ions spins arise from the competition between ferromagnetic and AFM interaction in the presence of strong electronic correlation. Our research results not only report the discovery of a clear block-type canted antiferromagnetic structure in a real quasi-1D chain material but also provide a theoretical approach to understand the block-type antiferromagnetism in quasi-1D iron chalcogenides.

antiferromagnetism

Unique Conductivity Behavior in Water-In-Salt Electrolytes Driven by Ion Clusters

Understanding and predicting ion transport in aqueous electrolytes are crucial for advanced energy storage and biophysics, and many emergent technologies yet remain elusive. Herein, we introduce a unified framework to quantitatively describe and predict electrolyte conductivity that shifts from conventional molar concentration-based metrics to a volume fraction-based approach. Through analyzing a variety of electrolyte solutions via this perspective, we observe a universal conductivity peak at a 37% volume fraction. Small-angle X-ray scattering (SAXS) and molecular dynamics (MD) simulations reveal that nanometer-scale ion clusters drive this general behavior. Moreover, key geometric features of the ion transport pathwayssuch as pore size, tortuosity, and connectivityfollow a consistent dependence with respect to the volume fraction, reinforcing the argument for the universal conductivity trend. This paradigm shift opens new avenues for designing high-performance electrolytes and provides transformative insights for advancing studies in many fields, wherein molecular aggregates dictate transport properties.

Nguyen, Huong T. D.

Observational evidence for Criegee intermediate oligomerization reactions relevant to aerosol formation in the troposphere

Criegee intermediates are reactive intermediates that are implicated in transforming the composition of Earth’s troposphere and in the formation of secondary organic aerosol, impacting Earth’s radiation balance, air quality and human health. Yet, direct identification of their signatures in the field remains elusive. Here, from particulate and gas-phase mass-spectrometric measurements in the Amazon rainforest, we identify sequences of masses consistent with the expected signatures of oligomerization of the CH 2 OO Criegee intermediate, a process implicated in ozonolysis-driven aerosol formation. In this study, we assess the potential contributions of oligomerization through laboratory ozonolysis experiments, direct kinetic studies of Criegee intermediate reactions, and high-level theoretical calculations. Global atmospheric models built on these kinetics results indicate that Criegee intermediate chemistry may play a larger role in altering the composition of Earth’s troposphere than is captured in current atmospheric models, especially in areas of high humidity. However, the models still capture only a relatively small fraction of the observed signatures, suggesting considerable underestimates of Criegee intermediate concentrations and reactivity and/or the dominance of other, presently uncharacterized, oxidation mechanisms. Resolving the remaining uncertainties in emission inventories and the effects of atmospheric water vapour on key chemical reactions will be required to definitively assess the role of Criegee intermediate oligomerization reactions.

58 GEOSCIENCES

Thermal Bekenstein-Hawking entropy from the worldsheet

We define and compute the leading sphere diagram contribution to the entropy of the BTZ black hole supported by Kalb-Ramond flux in bosonic string theory. In a winding condensate description, integrating exactly over the constant mode for the radial direction of AdS 3 reduces the problem to one of the correlation functions of winding operators in the free theory. The volume of the residual PSL(2,ℂ) gauge group of the sphere is canceled by the action of conformal transformations on the winding interaction insertions. We formulate a precise version of the replica trick in terms of (infinitesimally) non-integer winding condensates to produce the entropy of the BTZ black hole. The resulting entropy can be calculated from the one-point function of a non-local operator on the worldsheet.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Dynamic nanodomains dictate macroscopic properties in lead halide perovskites

Lead halide perovskites have emerged as promising materials for solar energy conversion and X-ray detection owing to their remarkable optoelectronic properties. However, the microscopic origins of their superior performance remain unclear. Here we show that low-symmetry dynamic nanodomains present in the high-symmetry average cubic phases, whose characteristics are dictated by the A-site cation, govern the macroscopic behaviour. We combine X-ray diffuse scattering, inelastic neutron spectroscopy, hyperspectral photoluminescence microscopy and machine-learning-assisted molecular dynamics simulations to directly correlate local nanoscale dynamics with macroscopic optoelectronic response. Our approach reveals that methylammonium-based perovskites form densely packed, anisotropic dynamic nanodomains with out-of-phase octahedral tilting, whereas formamidinium-based systems develop sparse, isotropic, spherical nanodomains with in-phase tilting, even when crystallography reveals cubic symmetry on average. We demonstrate that these sparsely distributed isotropic nanodomains present in formamidinium-based systems reduce electronic dynamic disorder, resulting in a beneficial optoelectronic response, thereby enhancing the performance of formamidinium-based lead halide perovskite devices. By elucidating the influence of the A-site cation on local dynamic nanodomains, and consequently, on the macroscopic properties, we propose leveraging this relationship to engineer the optoelectronic response of these materials, propelling further advancements in perovskite-based photovoltaics, optoelectronics and X-ray imaging.

Materials Science

High Pressure X-ray Diffraction and Equation of State of Hydrazine

Synchrotron X-ray diffraction has been used to investigate the structure and equation of state (EOS) of hydrazine (N 2 H 4 ) up to 54.3 GPa at 298 K. The diffraction patterns could be fit to a monoclinic unit-cell structure and put strong constraints on previously reported phase transitions documented by vibrational spectroscopy over this pressure range. Pressure–volume ( P–V ) data were fit using a Vinet EOS, yielding parameters: V 0 = 45.2 Å 3 /molecule (fixed), K 0 = 11.8(7) GPa, and K 0 ′ = 6.5(2). Previously measured high-pressure vibrational frequency shifts were used to estimate the vibrational free energy and model P–V–T isotherms from 0 to 1200 K. The results of the P–V–T isotherms are compared to existing shock Hugoniot data on hydrazine and 298 K isotherms for assemblages of possible decomposition products. This comparison suggests dissociation at high density under shock loading. Good correspondence was found between the static lattice EOS as calculated by the model and the previously reported EOS as calculated by density functional theory. Finally, these results resolve existing uncertainties about the EOS and crystal symmetry of hydrazine at high pressure and provide valuable baseline information on this important energetic material.

diffraction

Evaluation of 3D pixel silicon sensors for the CMS Phase-2 Inner Tracker

The high-luminosity upgrade of the CERN LHC requires the replacement of the CMS tracking detector to cope with the increased radiation fluence while maintaining its excellent performance. An extensive R&D program, aiming at using 3D pixel silicon sensors in the innermost barrel layer of the detector, has been carried out by CMS in collaboration with the FBK (Trento, Italy) and CNM (Barcelona, Spain) foundries. The sensors will feature a pixel cell size of 25 × 100 µm 2 , with a centrally located electrode connected to the readout chip. The sensors are read out by the RD53A and CROCv1 chips, developed in 65 nm CMOS technology by the RD53 Collaboration, a joint effort between the ATLAS and CMS groups. This paper reports the results achieved in beam test experiments before and after irradiation, up to a fluence of approximately 2 . 6 × 1 0 16 n eq /cm 2 . Measurements of assemblies irradiated to a fluence of 1 × 10 16 n˙eq/cm 2 show a hit detection efficiency higher than 96% at normal incidence, with fewer than 2% of channels masked, across a bias voltage range greater than 50 V . Even after irradiation to a higher fluence of 1.6 × 10 16 n˙eq/cm 2 , similar performance is maintained over a bias voltage range of 30 V , remaining well within CMS requirements.

3D pixel

Understanding Discharge‐Driven Growth of Cathode Impedance in Ni‐Rich NMC Cathodes

Degradation of LiNi x Mn y Co 1-x-y O 2 (NMC)-based lithium-ion batteries depends strongly on cut-off voltage ranges. In addition to the high upper cut-off voltage, a high depth of discharge (i.e., lower cut-off voltage) significantly worsens cathode impedance growth and capacity fade during long-term cycling. However, there is currently no consensus on the mechanism behind the negative role of a deep discharge. Here, this phenomenon was investigated in graphite||NMC cells with single-crystal cathodes (LiNi 0.6 Co 0.2 Mn 0.2 O 2 (NMC622) or LiNi 0.76 Co 0.14 Mn 0.10 O 2 (NMC76)) using targeted aging protocols (constant high-voltage holds vs. charge–discharge cycling), while monitoring transition-metal (TM) dissolution, cathode-electrolyte interface (CEI) impedance, and NMC surface composition. We demonstrate a correlation between discharge-driven CEI impedance growth and increased TM dissolution. Furthermore, this degradation pathway is more pronounced in lower-Ni NMC622 than in higher-Ni (NMC76) under comparable delithiation states at charge, with both compositions undergoing the H2→H3 phase transition. X-ray photoelectron spectroscopy (XPS) reveals NMC composition-dependent evolution of surface lattice oxygen and restructured surface layer composition between charged and discharged states. These findings add mechanistic depth to the role of discharge as an active driver of interfacial degradation and provide new insights into its composition dependence.

25 ENERGY STORAGE

Feedback, physics, and forecasts: The emerging paradigm of machine learning-driven battery research

Machine learning (ML) is reshaping how we understand, predict, and optimize electrochemical systems. In batteries, ML accelerates discovery across chemistry, design, and operation by transforming massive experimental and simulated datasets into predictive, interpretable models. This review consolidates a decade of progress in ML-driven battery innovation, from early-cycle feature extraction to operando image analysis and physics-informed modeling. We categorize approaches by data domain and physical fidelity, emphasizing interpretable ML for diagnostics, reinforcement learning for control, and multi-objective optimization for lifetime extension strategies. Additionally, we demonstrate how integrated models accelerate discovery, reduce testing time, and guide sustainable design. Economic analyses furthermore illustrate how these advances can lower cost per cycle and improve circularity. Together, these developments chart a path toward self-optimizing, sustainable battery technologies.

artificial intelligence

POWER ELECTRONICS GRID TIED SYSTEM FINAL REPORT

Across the country, electric utilities are grappling with the persistent hurdles of integrating Distributed Energy Resources (DERs). Managing these assets safely and effectively is a complex endeavor, complicated by varying ownership structures, management philosophies, and the diversity of the technologies themselves. Consequently, the industry has seen a proliferation of bespoke system designs, control strategies, and communication frameworks—forcing utilities to spend significant time and resources developing one-off integration solutions. This project addressed these integration hurdles through a scalable demonstration of intelligent devices designed to coordinate and control diverse resources in low-voltage applications. This concept minimized the need for complex integration by transforming the separate DERs into a dispatchable virtual power plant (VPP) with integrated resiliency functions (called a Node). By collaborating with a utility partner, the project focused on developing rapidly implementable use cases that bridged the gap between theoretical control and real-world deployment

99 GENERAL AND MISCELLANEOUS

A physics informed bayesian optimization approach for material design: application to NiTi shape memory alloys

Abstract The design of materials and identification of optimal processing parameters constitute a complex and challenging task, necessitating efficient utilization of available data. Bayesian Optimization (BO) has gained popularity in materials design due to its ability to work with minimal data. However, many BO-based frameworks predominantly rely on statistical information, in the form of input-output data, and assume black-box objective functions. In practice, designers often possess knowledge of the underlying physical laws governing a material system, rendering the objective function not entirely black-box, as some information is partially observable. In this study, we propose a physics-informed BO approach that integrates physics-infused kernels to effectively leverage both statistical and physical information in the decision-making process. We demonstrate that this method significantly improves decision-making efficiency and enables more data-efficient BO. The applicability of this approach is showcased through the design of NiTi shape memory alloys, where the optimal processing parameters are identified to maximize the transformation temperature.

Chemistry

Strain and Defect-Tailored Magnetotransport in NiCo 2 O 4 Thin Films and Freestanding Membranes

Magnetic spinel NiCo 2 O 4 is promising for developing spintronic applications due to its high magnetic Curie temperature, high spin polarization, fast spin dynamics, and strain-tunable magnetic anisotropy, while its electronic and magnetic properties depend sensitively on epitaxial strain and disorder. Here, in this study, we use epitaxial NiCo 2 O 4 thin films and freestanding NiCo 2 O 4 membranes as model systems to reveal the complex interplay of strain and defects in determining the metallicity and magnetotransport properties of the ferrimagnetic spinel. NiCo 2 O 4 on perovskite substrates and NiCo 2 O 4 membranes exhibit insulating behaviors and spin canting, in sharp contrast to the metallic NiCo 2 O 4 films on spinel substrates that possess strong perpendicular magnetic anisotropy. Anisotropic magnetoresistance studies provide critical information about disorder-induced spin scattering and strain-induced tetragonal magnetocrystalline anisotropy, which is corroborated by comprehensive electron microscopy characterizations. Our study presents a promising venue for designing flexible magnetic memory, sensor, and spintronic applications.

36 MATERIALS SCIENCE