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At least 271 records · Page 15

Nonadiabatic dynamics of photoexcited thiopyridone isomers: An interplay between El-Sayed’s conditions and energy gap law

We investigated the non-adiabatic dynamics of photoexcited thiopyridone systems across their ortho-, meta-, and para-isomeric forms. The relaxation pathways of the three isomers in both gas phase and solvent environments are mapped using surface hopping dynamics based on time-dependent density functional theory. Our analysis highlights the influence of isomeric structures on photophysical behavior, offering insights into design principles to control photochemical phenomena. The simulations suggest a systematic reduction in the rate of intersystem crossing (ISC) from ortho- to meta- to para-isomer. Comparisons with multiconfigurational wave function methods in the gas phase further demonstrate how electronic structure influences the predicted dynamical pathways. The simulated dynamics demonstrates that the spin–orbit coupling strength alone does not determine the rate of ISC, as both state energetics and underlying electronic and structural features play decisive roles. These aspects explain the much slower ISC in the para-isomer, as well as the non-negligible role of the El-Sayed forbidden pathway in the computed ISC dynamics.

Complete-active space self-consistent field

Modeling the behavior of concentrated aqueous HNO 3 using machine learning interatomic potentials

We develop two multi-defect machine learning interatomic potentials (MLIPs) trained at the BLYP-D2 and PBE-D3 density functional theories using the DeepMD-kit, allowing for the investigation of structural and thermodynamic properties of nitric acid over a wide range of concentrations via molecular dynamics (MD) simulations. We directly compute the degree of dissociation, α, and pK a from MD simulations, revealing that HNO 3 behaves as a weaker acid at higher concentrations, noting that our standard-state pK a value is in excellent agreement with the experimental one. In general, good agreement is observed with experimental results such as α and density outside the training dataset, with only modest deviations at low-to-medium concentrations. We benchmark our custom multi-defect DeepMD MLIPs against foundational models MACE-MP0 and MACE-OFF23. The foundation models capture some aspects of HNO 3 /NO 3 − solvation in concentrated nitric acid but show noticeable density errors and miss subtle structural features relevant to spectroscopy, whereas the bespoke DeepMD MLIPs yield more compact solvation shells, reproduce density-concentration trends, and run ∼12–15× faster than MACE-MP0. Although classical FFs are still more efficient and match experimental densities better, they lack chemical reactivity and thus cannot predict α or pK a , underscoring the need for system-specific reactive MLIPs beyond universal MLIPs.

Dinpajooh, Mohammadhasan [Pacific Northwest Nation

Attention-based explainability for structure–property relationships

Machine learning methods are emerging as a universal paradigm for constructing correlative structure–property relationships in materials science based on multimodal characterization. However, this necessitates the development of methods for the physical interpretability of the resulting correlative models. Here, we demonstrate the potential of attention-based neural networks for revealing structure–property relationships and the underlying physical mechanisms, using the ferroelectric properties of PbTiO3 thin films as a case study. Through the analysis of attention scores, we disentangle the influence of distinct domain patterns on the polarization switching process. The attention-based Transformer model is explored both as a direct interpretability tool and as a surrogate for explaining representations learned via unsupervised machine learning, enabling the identification of physically grounded correlations. We compare attention-derived interpretability scores with classical SHapley Additive exPlanations analysis and show that, in contrast to applications in natural language processing, attention mechanisms in materials science exhibit high efficiency in highlighting meaningful structural features.

Slautin, Boris [Independent Researcher]

Desmearing Bonse–Hart USANS data using Bayesian Gaussian process regression

Ultra-small-angle neutron scattering (USANS) enables access to micrometer-scale structures but is intrinsically affected by strong, anisotropic resolution smearing arising from slit-geometry optics. As a result, recovery of the intrinsic scattering intensity constitutes an ill-posed inverse problem, and commonly used iterative desmearing methods lack rigorous uncertainty quantification. We present a Bayesian desmearing framework for slit-geometry USANS based on Gaussian process regression. In this approach, the scattering intensity is modeled as a smooth random function, and the instrumental point spread function is incorporated explicitly as a forward operator. The resulting formulation yields a closed-form maximum a posteriori solution with well-defined credibility intervals. Computational benchmarks and experimental validation using combined USANS and small-angle neutron scattering (SANS) measurements demonstrate that the framework enables stable desmearing, suppresses experimental noise, and preserves physically meaningful structural features under realistic conditions.

Tung, Chi-Huan [Oak Ridge National Laboratory (ORN

A perspective on the electronic instabilities in kagome AV 3 Sb 5

The electronic properties of solids are strongly shaped by lattice geometry. A prime example is the kagome lattice, whose band structure features van Hove singularities (vHS), flat bands, and Dirac crossings. These characteristics naturally promote strong electronic correlations. In the kagome metals AV 3 Sb 5 , the Fermi level lies close to kagome-derived vHS, placing the system in a regime of heightened electronic susceptibility and correlation-driven instabilities. In this Perspective, we discuss the electronic instabilities observed experimentally in AV 3 Sb 5 , outline the physical pictures that we find most compelling, and share our views on the current excitement, open debates, and future opportunities in these materials. We view AV 3 Sb 5 as a uniquely clean platform for exploring how multiple correlated phases coexist, compete, and intertwine on a single Fermi surface, offering a level of conceptual richness comparable to that of the cuprates. Although a lot of information about AV 3 Sb 5 has been collected in recent years, we still lack a clear understanding of each of its electronic phases or their interplay. Furthermore this Perspective aims to expose the status of the field and cajole a communal effort toward a unified physical description of these compounds.

Yeh, Eric C. H. [University of California, Los Ang

Relative molecular orientation can impact the onset of plasticity in molecular crystals

Abstract Creating or moving dislocations is the first step to dissipating mechanical energy via plastic deformation under contact loading. In molecular crystals there is both a lattice that defines crystal orientation and a relative orientation of the basis of the molecules. We define a normalization parameter which relates strain at yield, the hardness of the bulk crystal, and a distance parameter analogous to a Burgers vector that nominally predicts the relative ease of initiating plasticity in this broad class of materials. Analyzing the yield behavior of 10 different molecular crystals of varying space groups shows the inter-molecular orientation predicts the experimentally observed applied stress needed to nucleate dislocations. When molecules are oriented ‘parallel’ relative to one another the normalized maximum shear stress at the onset of plasticity is on the order of 3–5 times lower than when molecules within the crystal are ‘anti-parallel’, and molecules with a more equiaxed shape fall in between these bounds. This provides an initial indication of a structural feature which predicts the relative ease of initiating plasticity during contact loading in molecular crystals.

36 MATERIALS SCIENCE

Physics-guided dual implicit neural representations for source separation

Significant challenges exist in efficient data analysis of most advanced experimental and observational techniques because the collected signals often include unwanted contributions, such as background and signal distortions, that can obscure the physically relevant information of interest. To address this, we have developed a self-supervised machine-learning approach for source separation using a dual implicit neural representation framework that jointly trains two neural networks: one for approximating distortions of the physical signal of interest and the other for learning the effective background contribution. Our method learns directly from the raw data by minimizing a reconstruction-based loss function without requiring labeled data or pre-defined dictionaries. We demonstrate the effectiveness of our framework by considering a challenging case study involving large-scale simulated, as well as experimental, momentum-energy-dependent inelastic neutron scattering data in a four-dimensional parameter space, characterized by heterogeneous background contributions and unknown distortions to the target signal. The method is found to successfully separate physically meaningful signals from a complex or structured background even when the signal characteristics vary across all four dimensions of the parameter space. An analytical approach that informs the choice of the regularization parameter is presented. Our method offers a versatile framework for addressing source separation problems across diverse domains, ranging from superimposed signals in astronomical measurements to structural features in biomedical image reconstructions.

47 OTHER INSTRUMENTATION

Crystal structure of MutYX: a novel clusterless adenine DNA glycosylase with a distinct C-terminal domain and 8-oxoguanine recognition sphere

Abstract The [4Fe–4S] cluster is an important cofactor of the base excision repair (BER) adenine DNA glycosylase MutY to prevent mutations associated with 8-oxoguanine (OG). Several MutYs lacking the [4Fe–4S] cofactor have been identified. Phylogenetic analysis shows that clusterless MutYs are distributed in two clades suggesting cofactor loss has occurred in multiple independent evolutionary events. Herein, we determined the first crystal structure of a clusterless MutY complexed with DNA. On the basis of the dramatic structural divergence from canonical MutYs, we refer to this as representative of a clusterless MutY subgroup “MutYX.” Interestingly, MutYX compensates for the missing [4Fe–4S] cofactor to maintain positioning of catalytic residues by expanding a pre-existing α-helix and acquisition of a new α-helix. Surprisingly, MutYX also acquired a new C-terminal domain that uniquely recognizes OG using residues Gln201 and Arg209. Adenine glycosylase assays and binding affinity measurements indicate that Arg209 is the primary residue responsible for OG:A lesion specificity, while Gln201 assists by bridging OG and Arg209. Surprisingly, replacement of Arg209 and Gln201 with Ala increased activity toward G:A mismatches. The MutYX structure serves as an example of devolution, capturing structural features required to retain function in the absence of a metal cofactor considered indispensable.

Trasviña-Arenas, Carlos H [University of Californi

Anisotropic magnetism and Kondo-lattice behavior in the frustrated antiferromagnet Ce 3 ⁢MgBi 5

Here, we report the synthesis and physical characterization of single-crystalline Ce 3 ⁢MgBi 5 , a previously unexplored member of the Ce 3 ⁢𝑀⁢𝑃⁢𝑛 5 family. This compound crystallizes in the hexagonal 𝑃⁢6 3 /𝑚⁢𝑐⁢𝑚 structure, featuring an anisotropic Ce sublattice composed of zigzag chains along the 𝑐 axis and a distorted kagome-like network in the basal plane. Magnetization measurements reveal antiferromagnetic order below 𝑇 𝑁 ≈ 4.2K with strong magnetic anisotropy and multiple field-induced metamagnetic transitions for fields applied perpendicular to [001], leading to a dome-shaped 𝐻–𝑇 phase diagram. Electrical transport exhibits characteristic signatures of a Ce-based Kondo lattice, including broad resistivity maxima and pronounced field-dependent anomalies in the magnetoresistance and Hall response that track the magnetic phase boundaries. Specific-heat measurements confirm the magnetic transition and show that the full R ⁢ln⁡ 2 entropy expected for a Ce 3+ Kramers doublet is recovered by 20 K, indicating an extended temperature range of magnetic fluctuations consistent with Kondo correlations. Our results establish Ce 3 ⁢MgBi 5 as a platform within the Ce 3 ⁢𝑀⁢𝑃⁢𝑛 5 family for exploring the interplay of geometric frustration, magnetic anisotropy, and Kondo-lattice physics under applied magnetic fields.

Kondo effect

DECADE+ DES Y3 Weak Lensing Mass Map: A 13,000 deg $\^{} 2$ View of Cosmic Structure from 270 Million Galaxies

We present the largest galaxy weak lensing mass map of the late-time Universe, reconstructed from 270 million galaxies in the DECADE and DES Year 3 datasets, covering 13,000 square degrees. We validate the map through systematic tests against observational conditions (depth, seeing, etc.), finding the map is statistically consistent with no contamination. The large area covered by the mass map makes it a well-suited tool for cosmological analyses, cross-correlation studies and the identification of large-scale structure features. We demonstrate its potential by detecting cosmic filaments directly from the mass map for the first time and validating them through their association with galaxy clusters selected using the Sunyaev-Zeldovich effect from Planck and ACT DR6.

Gatti, M.

Diffusion coefficients predicting facet-dependent crystallization in amorphous silicon nitride

Amorphous silicon nitride is a common material in microelectronics devices, which acts as an insulating barrier. Extended annealing times at elevated temperature can initiate crystallization of α-Si 3 ⁢ N 4 , which does not possess the same barrier properties. Molecular dynamics can resolve the fundamental mechanism for α-Si 3 ⁢N 4 crystallization and the influence of local environments. Here, we compare two interatomic potentials and conclude that these models predict structural features (e.g., angular distributions and densities) which span the range of experimental measurements. We confirmed these models reproduce experimental estimates of activation energy and leveraged these models to identify crystallization drivers. We conclude that near-T g , facet-dependent silicon nitride crystal growth rates can be predicted directly by either bulk or interfacial diffusion properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Composition and in situ structure of the Methanospirillum hungatei cell envelope and surface layer

Archaea share genomic similarities with Eukarya and cellular architectural similarities with Bacteria, though archaeal and bacterial surface layers (S-layers) differ. Using cellular cryo–electron tomography, we visualized the S-layer lattice surroundingMethanospirillum hungatei, a methanogenic archaeon. Though more compact than known structures,M. hungatei’s S-layer is a flexible hexagonal lattice of dome-shaped tiles, uniformly spaced from both the overlying cell sheath and the underlying cell membrane. Subtomogram averaging resolved the S-layer hexamer tile at 6.4-angstrom resolution. By fitting an AlphaFold model into hexamer tiles in flat and curved conformations, we uncover intra- and intertile interactions that contribute to the S-layer’s cylindrical and flexible architecture, along with a spacer extension for cell membrane attachment.M. hungateicell’s end plug structure, likely composed of S-layer isoforms, further highlights the uniqueness of this archaeal cell. These structural features offer advantages for methane release and reflect divergent evolutionary adaptations to environmental pressures during early microbial emergence.

Science & Technology - Other Topics

Strain mapping of three-dimensionally structured two-dimensional materials

Strain plays a crucial role in tuning materials’ properties, influencing their optical, electrical, and chemical performances. In two-dimensional (2D) materials, applied stress often induces out-of-plane deformation, resulting in a more intricate three-dimensional (3D) topography, where mapping the strain remains a challenge due to the limitations of conventional characterization techniques. In this work, we introduce BRIGHT (Bragg-Rod Informed, Gradient-based Height-mapping Technique), an integrated method for reconstructing both the topography and planar strain profile of 3D-structured 2D materials using nanobeam four-dimensional scanning transmission electron microscopy (4D-STEM). We apply BRIGHT to a MoS2-MoSe2 transition metal dichalcogenide (TMD) lateral heterojunctions exhibiting built-in strain and out-of-plane ripples and show that varying heterojunction widths lead to distinct surface morphologies and corresponding changes in the planar strain distribution. These results establish a foundation for more effective strain engineering in 2D materials by accounting for out-of-plane structural features, thereby enabling more precise control of strain-dependent properties.

Mireles, Adan [Rice Univ., Houston, TX (United Sta

Anion sublattice design enables superionic conductivity in crystalline oxyhalides

Solid-state batteries are attractive energy storage systems as a result of their inherent safety, but their development hinges on advanced solid-state electrolytes (SSEs). Most SSEs remain largely confined to single-anion systems (e.g., sulfides, oxides, halides, and polymers). Through mixed-anion design strategy, we develop crystalline Li 3 Ta 3 O 4 Cl 10 (LTOC) and its derivatives with excellent ionic conductivities (up to 13.7 millisiemens per centimeter at 25°C) and electrochemical stability. The LTOC structure features mixed-anion spiral chains, consisting of corner-shared oxygen and terminal chlorine atoms, which induces continuous “tetrahedron-tetrahedron” Li-ion migration pathways with low energy barriers. Additionally, LTOC demonstrates holistic cathode compatibility, enabling solid-state batteries operation at 4.9 volts versus Li/Li + and low temperature, down to −50°C. In conclusion, these findings describe a promising class of superionic conductors for high-performance solid-state batteries.

Zhao, Feipeng [Western University, London, ON (Can

Confocal Raman Microscopy for Measuring In Situ Temperature-Dependent Structural Changes in Poly(Ethylene Oxide) Thin Films

Crystallization from the melt is a critical process governing the properties of semi-crystalline polymeric materials. While structural analyses of melting and crystallization transitions in bulk polymers have been widely reported, in contrast, those in thin polymer films on solid supports have been underexplored. Herein, in situ Raman microscopy and self-modeling curve resolution (SMCR) analysis are applied to investigate the temperature-dependent structural changes in poly(ethylene oxide) (PEO) films during melting and crystallization phase transitions. By resolving complex overlapping sets of spectra, SMCR analysis reveals that the thermal transitions of 50 µm thick PEO films comprise two structural phases: an ordered crystalline phase and a disordered amorphous phase. The ordered structure of the crystalline PEO film entirely disappears as the polymer is heated; conversely, the disordered structure of the amorphous PEO film reverts to the ordered structure as the polymer is cooled. Broadening of the Raman bands was observed in PEO films above the melting temperature (67 °C), while sharpening of bands was observed below the crystallization temperature (45 °C). The temperatures at which these spectral changes occurred were in good agreement with differential scanning calorimetry (DSC) measurements, especially during the melting transition. The results illustrate that in situ Raman microscopy coupled with SMCR analysis is a powerful approach for unraveling complex structural changes in thin polymer films during melting and crystallization processes. Furthermore, we show that confocal Raman microscopy opens opportunities to apply the methodology to interrogate the structural features of PEO or other surface-supported polymer films as thin as 2 µm, a thickness regime beyond the reach of conventional thermal analysis techniques.

Koh, Miharu [Department of Chemistry, University o

Towards efficient light emitters via computational design of molecules with inverted singlet-triplet gaps

To move toward rational design of efficient organic light emitting diodes based on the radical idea of inverted singlet-triplet gap (INVEST) systems, we propose a set of novel quantum chemical approaches, predictive but low-cost, to unveil a set of structural-property relationships. We perform a computational study of a series of substituted molecules based on a small set of known INVEST molecules. Our study demonstrates a high degree of correlation between the intramolecular charge transfer and the singlet-triplet energy gap and hints towards the use of a quantitative estimate of charge transfer to predict and modulate these energy gaps. We aim to create a database of INVEST molecules that includes accurate benchmarks of singlet-triplet energy gaps. Furthermore, we aim to link structural features and molecular properties, enabling a control knob for rational design.

42 ENGINEERING

lllinois Storage Corridor CarbonSAFE Phase III: Pre-drilling Site Assessment: Prairie State Generating Company

The Illinois Storage Corridor project will drill a stratigraphic test well as part of the Illinois Storage Corridor CarbonSAFE Phase 3 project near the Prairie State Generating Company coal-fired power plant near Marissa, Illinois. The pre-drilling site evaluation has considered the primary target reservoirs, the Potosi Dolomite and St. Peter Sandstone, and primary seal, the Maquoketa Group. Data to be collected from the well include core, fluid samples, in situ well tests, geophysical logs intended to provide information on lithologic, geomechanical, and geophysical characteristics to determine the feasibility for the geologic sequestration of 50 million metric tons or more of injected carbon dioxide. The planned drilling site has been evaluated using available subsurface geologic data and analyses from the Illinois Basin. These data provide lithologic and structural information, shallow groundwater resource distribution, location of known nearby wellbores, and regional drilling characteristics. The data were used to generate geologic structure and isopach maps for the target reservoir and caprock strata and for prognosing the tops of major lithologic units to aid drilling and coring procedures. The regional analyses indicate that no known structural features are expected to negatively impact the target storage reservoir or caprock. No protected and sensitive areas, groundwater resources, or existing resource development are expected to be impacted by the proposed well drilling activities. The well is planned to be drilled to a total depth of approximately 5,600 feet (1,707 m) and terminate in the Precambrian. Cores (up to 5 intervals) will be collected from the Maquoketa Group, confining units above the St. Peter Sandstone, St. Peter Sandstone, confining units of the Potosi Dolomite and the Potosi Dolomite. Water samples will be attempted to be collected from the St. Peter Sandstone and Potosi Dolomite. Potential impact on drilling progress is a lost circulation zone in the Potosi Dolomite, which has been demonstrated to have intermittent cavernous porosity from karstification elsewhere in the Illinois Basin. This document also presents a preliminary coring and sampling program, proposed logging suite, and well testing program, all of which will be reviewed during drilling.

01 COAL, LIGNITE, AND PEAT

Computationally Guided and Experimentally Validated Design of Custom Chelators for Critical Mineral Recovery

Selective, high throughput separation of target critical metals from complex environments such as fly ash leachates and mining process streams presents a significant challenge for economical production. Custom chelators and sorbents are an attractive technology for selective metal extraction, however it can be difficult to predict their performance, and significant experimental efforts are often required to develop chelating technologies. Here, we present a computational strategy focused on modelling chelator-metal binding interactions and benchmark these results versus experimental data. A computational pipeline combining forcefield, semiempirical, and meta-GGA methods with a thermodynamic framework optimized for error cancellation has been developed to predict binding energies of chelator complexes towards critical mineral recovery applications. This approach, originally validated on [2.2.2] cryptates binding mono- and divalent cations, demonstrated robust predictive capabilities with an R2 of 0.850 against experimental aqueous binding energies. The workflow includes metadynamics for exploring high-dimensional potential energy surfaces and a cluster-continuum model for accurate yet computationally efficient solvation modeling. Error cancellation between solvation energies of free and chelator-coordinated ions enables faster convergence, even with finite cluster sizes. Initial studies on the cryptates revealed consistent metal-ligand coordination patterns, with systematic variations influenced by ion size and charge, highlighting key structural features linked to binding selectivity. Further studies of a proprietary chelator have resulted in identification of previously unreported selectivity towards economically significant metals, which in-house experiments have confirmed, demonstrating the feasibility of this approach. By applying this methodology to new chelators targeting critical minerals such as lithium, cobalt, nickel and other strategic metals, we aim to accelerate the discovery of next-generation chelators for efficient recovery, recycling, and separation processes. This computational framework serves as the backbone of a high-throughput design pipeline tailored for sustainable resource utilization and may be applied to a wide range of systems to meet experimental needs.

computational materials