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608 records · Page 4

PAH101: A GW+BSE Dataset of 101 Polycyclic Aromatic Hydrocarbon (PAH) Molecular Crystals

Abstract The excited-state properties of molecular crystals are important for applications in organic electronic devices. TheGWapproximation and Bethe-Salpeter equation (GW+BSE) is the state-of-the-art method for calculating the excited-state properties of crystalline solids with periodic boundary conditions. We present the PAH101 dataset ofGW+BSE calculations for 101 molecular crystals of polycyclic aromatic hydrocarbons (PAHs) with up to ~500 atoms in the unit cell. To the best of our knowledge, this is the firstGW+BSE dataset for molecular crystals. The data records include theGWquasiparticle band structure, the fundamental band gap, the static dielectric constant, the first singlet exciton energy (optical gap), the first triplet exciton energy, the dielectric function, and optical absorption spectra for light polarized along the three lattice vectors. The dataset can be used to (i) discover materials with desired electronic/optical properties, (ii) identify correlations between DFT andGW+BSE quantities, and (iii) train machine learned models to help in materials discovery efforts.

Science & Technology - Other Topics

Explainable machine learning reveals that local structural motifs encode the thermodynamic state across the CuZr metallic glass-forming range

Metallic glasses derive their properties from the statistics of local atomic motifs rather than from long-range order, yet a quantitative, chemistry-specific link between motif populations and the underlying glassy state has remained elusive. In this work we combine large-scale molecular dynamics, Voronoi tessellation, deep neural networks, and SHapley Additive exPlanations (SHAP) to identify which local structural motifs define the glassy state of Cu—Zr metallic glasses. A dataset of 17,180 atomistic configurations spanning ten compositions (Cu 20 Zr 80 –Cu 80 Zr 20 ) and four quench rates (10 9 –10 12 K/s) is used to train a feed-forward neural network that regresses temperature across the 50–2000 K liquid–supercooled–glass range, achieving a mean absolute error of 19.89 K and R 2 = 0.9974, confirming that the local structural state is faithfully encoded in motif-level structure. SHAP analysis then reveals that a tightly coupled near-icosahedral family of motifs (coordination numbers (CN) 11–13, including the full icosahedron 001200 and its single-atom-perturbation sibling 10930) collectively encodes the thermodynamic state of the system across the full glass-forming range. The CN = 11–13 ordered members carry negative SHAP values at high populations, tracking the most deeply-quenched configurations, while 10930 shows the reversed signature consistent with its role as a soft-spot host whose population shrinks as the icosahedral network deepens. The analysis demonstrates that explainable machine learning can isolate the minimal motif vocabulary defining the glassy state and recovers the near-icosahedral building blocks previously identified by data-driven analyses of Cu—Zr. The approach provides a general, chemistry-specific route for characterizing the structural state of disordered materials.

36 MATERIALS SCIENCE

Nuclear quantum effects in molecular liquids across chemical space

Abstract Nuclear quantum effects (NQEs) influence many physical and chemical phenomena, particularly those involving light atoms or occurring at low temperatures. However, their impact has been carefully quantified in few systems-like water-and is rarely considered more broadly. Here we use path-integral molecular dynamics to systematically investigate NQEs on thermophysical properties of 92 organic liquids at ambient conditions. Depending on chemical constitution, we find substantial impact across thermal expansivity, compressibility, dielectric constant, enthalpy of vaporization, and notably molar volume, which shows consistent, positive quantum-classical differences up to 5%; similar, less pronounced trends manifest as isotope effects from deuteration. Using data-driven analysis, we identify three features-molar mass, classical hydrogen density, and classical thermal expansivity-that accurately predict NQEs and facilitate understanding of how characteristics like branching and heteroatom content influence behavior. This work highlights the broad relevance of NQEs in molecular liquids, while also providing a conceptual and practical framework to anticipate their impact.

Science & Technology - Other Topics

Limited proteolysis of pea protein to promote aggregation/gelation: role of enzyme concentration and molecular characteristics

Limited proteolysis promotes aggregation/gelation of plant proteins, but its relationship with the molecular characteristics of hydrolysates remains poorly understood. In here, response surface methodology was employed to evaluate the effects of protein concentration, Alcalase level, and hydrolysis time on the storage modulus (G′) of pea protein hydrolysates (PPH). 7.5% protein, 1.65% Alcalase, and a 6-min reaction time resulted in the highest relative increase in G′ upon heating PPH, whereas both higher (3.55%) and lower (0.3%) Alcalase levels led to less increment. Increasing the Alcalase level increased the degree of hydrolysis while decreasing the molecular weight, surface hydrophobicity, and total sulfhydryl and disulfide bond contents of PPH. Confocal laser scanning microscopy and X-ray scattering analyses found PPH produced with 1.65% Alcalase formed interconnected aggregates with dual structural domains, but not at other Alcalase conditions. These results demonstrate the role of controlled proteolysis in governing the aggregation/gelation behavior of PPH.

X-ray scattering

Visualizing Crystallization Dynamics and Transformation Pathways of Disordered Rocksalt Oxides During Thermally Activated Sol–Gel Synthesis

Sol–gel synthesis is a wet-chemical processing route for fabricating functional materials with control over composition and microstructure at relatively low temperatures compared to conventional solid-state synthesis. While sol–gel process initiates with intermixed molecular precursors, the early-stage nucleation pathways are insufficiently understood. Here, in this study, the chemical and structural transformation of ion disordered rocksalt (DRX) Li 1.2 Mn 0.4 Ti 0.4 O 2 (LMTO), a promising cathode material for lithium batteries, is studied by multiscale characterizations. In situ heating transmission electron microscopy (TEM) using a liquid cell visualizes and identifies crystallization pathways at the nanoscale. While some regions follow a classical multi-step transition through thermodynamically stable intermediates, others exhibit a kinetic shortcut via a localized amorphous matrix to directly form the DRX structure. Macroscale Fourier transform infrared spectroscopy corroborates the findings and reveals that transition metal ions are more strongly incorporated into the acetate-coordinated network than lithium. Although in situ heating TEM captures diverse local transformation pathways, in situ synchrotron X-ray diffraction indicates that the macroscopic transformation proceeds predominantly through spinel LMTO and lithium titanates toward DRX-LMTO. The findings uncover the spatiotemporal chemical and structural transformations in sol–gel derived DRX-LMTO materials, and call for fine-tuning of such sol–gel chemistries to manipulate the crystallization pathways and achieve target material homogeneity more efficiently.

cathode material

Transient histone deacetylase inhibition reveals cell type invariant and specific effects of chromatin decondensation on irradiation response

Radiation therapy plays a prominent role in breast cancer treatment, but the high doses of radiation damage both healthy and cancerous cells. Therefore, additional research is needed into combination therapies that could preferentially radiosensitize cancer cells compared to surrounding healthy tissue without causing deleterious side effects. Histone deacetylase inhibitor drugs (HDACis) have been tested as radiosensitizers in both basic research and clinical trials, but the long exposure time typically used in these treatments and the lack of matched healthy cell controls often leave aspects of their mechanism of action unclear. Here, we show that transient (2 h) trichostatin A (TSA) treatment of cancerous and non-tumorigenic breast epithelial cell lines increases immediate DNA damage and decreases long term cell viability in both cell types at high radiation doses. Transient TSA treatment also causes an increase in DNA damage signals after 5 Gy X-rays in other cancer and healthy cell types: A375 melanoma cells and BJ5-ta fibroblasts. This suggests that chromatin decompaction acts to increase cellular vulnerability to initial DNA damage from high doses of radiation in a cell type independent manner that does not rely on changes to DNA repair pathways caused by longer TSA treatment. However, responses to lower doses of radiation and long term survival are more cell type specific: only MCF7 cells experience an effect of TSA on DNA damage after 1 Gy X-ray radiation while MCF10a cells experience somewhat more evident cell viability effects of combined TSA and radiation treatment long term.

Li, Heng [Biochemistry & Cellular and Molecular Bi

Molecular origin of anisotropic shear elastoplasticity in chitin

Chitin nano- and mesoscale structures present in the exoskeleton of crustaceans exhibit exceptional longitudinal stiffness and toughness, rivaling or even exceeding that of many synthetic polymer architectures. Here, we reveal the origin of the asymmetric shear response in chitin multiscale architectures, marked by pronounced anisotropy in deformation. Under shear aligned with the molecular axis, chitin accommodates strain through coherent atomic rearrangements that enable elastic recovery. In contrast, shear applied perpendicular to this axis induces liquid-like plasticity via localized sliding. These results demonstrate the intrinsic mechanical anisotropy of chitin, underpinning a dual function in resisting repetitive loading while dissipating internal stress during high-strain events. Our findings establish the molecular basis of shear elastoplasticity in multiscale chitin structures, wherein axial elasticity supports energy storage in load-bearing regions, whereas transverse plasticity enables controlled energy dissipation. These atomic-scale insights lay a foundation for the predictive design of chitin-based materials with tunable strength-toughness profiles.

Wan, Zhangmin [University of British Columbia, Van

Molecular dynamics based study on the effects of cation size on the local structure and diffusion in polymerized ionic liquids

We have used coarse-grained molecular dynamics simulations to understand the effect of cation size on ion diffusion in polymerized ionic liquids at temperatures well above the glass transition temperature of the polymers. We investigated dependencies of the diffusion constant on the cation radius and static dielectric constant and interpreted these results in terms of underlying structural changes, and decoupling phenomenon. We have found non-monotonic effects of the cation radius on the diffusion constant, with a maximum at an intermediate radius resulting from two different size dependent effects. Changes in the radial distribution functions characterizing spatial distribution of cations with respect to anions result in a monotonic increase in the coordination number. This yields an increase in the effective interaction energy as a function of cation radius, which can explain the decrease in the diffusion constant. This increase is counteracted at small cation radii by a corresponding increase in decoupling of cation and anion dynamics. In addition, the diffusion constant is found to increase on increasing the static dielectric constant for all radii of the cations. These results highlight the significant role of decoupling in designing polymerized ionic liquids with an enhanced diffusion constant of cations.

Gillespie, Colin [ORNL] (ORCID:0000000320287080)

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.

Effect of Entropic Constraints on the Thermodynamics of Molecular Adsorption in Nano‐Porous Materials

Abstract Gas separation is a critical industrial process that consumes a significant amount of energy due to the widely used techniques that are currently employed. Adsorptive materials—such as metal–organic frameworks (MOFs)—show promise as an energy‐efficient alternative. Of particular current interest are novel, temperature‐dependent separation processes in MOFs, such as the recently reported separation of ternary isomeric hydrocarbon mixtures within one and the same material. However, the mechanisms of these highly desirable separations remain poorly understood. Herein, through a combination of ab initio simulations and statistical mechanics, it is shown that the temperature dependence is the result of a constraint on the guest molecule's entropic degrees of freedom when loaded into the MOF, caused by the fortuitous tight fitting of the guest inside the pore. While the framework applies to all molecular adsorption in porous media, it is essential for the description of large molecules in small pores, which is demonstrated here using the separation of C6 isomers in Ca(H 2 tcpb) as a test case. The developed framework and analysis not only reveal the reason why separation occurs but also predict the temperatures at which it takes place, thus opening the door to newly designed MOFs with tailor‐made precision.

Chemistry

Gas permeation properties of amorphous zeolitic imidazolate framework membranes made by atomic/molecular layer deposition

Amorphous metal-organic framework (MOF) membranes are desirable because they may retain some of the molecular sieving properties of their crystalline counterparts while being free of grain boundary defects, which often hinder the consistent achievement of high membrane performance. However, current methods, like melting and compression, for fabricating amorphous MOF membranes involve multi-step processes that require the formation of a crystalline membrane first, that is then amorphized, and therefore, could be challenging to scale. Here, we utilize atomic/molecular layer deposition (ALD/MLD) of diethylzinc (DEZ) and 2-methylimidazole (2mIm) to directly synthesize ultrathin amorphous zeolitic imidazolate framework (aZIF) deposits on γ-alumina-coated α-alumina supports. As the number of ALD/MLD cycles increased from 10 to 300, gas permeances decreased while ideal selectivities increased. Mixture separation factors for C3H6/C3H8, CO2/N2, and H2/C3H8 as high as 4, 37, and 194, respectively, were obtained. At 200 °C and 2.5 bar equimolar feed of H2 and C3H8, a H2/C3H8 mixture separation factor of 185 is obtained with an H2 permeance of ca. 4.15x10-8 mol/m2-s-Pa (124 GPU). Additionally, the membrane achieves a CO2/N2 mixture separation factor of 37 at 25 °C and 1 bar with a CO2 permeance of ca. 3.96x10-8 mol/m2-s-Pa (118 GPU). Considering the vast array of compositionally distinct aZIFs that can be potentially deposited by this approach, an enormously large parameter space for membrane design is emerging to be explored.

36 MATERIALS SCIENCE

Mild-Annealed Molecular Layer Deposition (MLD) Tincone Thin Film as Photoelectrochemically Stable and Efficient Electron Transport Layer for Si Photocathodes

Metalcone thin films, composed of inorganic–organic hybrids, are synthesized using molecular layer deposition (MLD) through reactions between organometallic precursors (e.g., Sn, Al, and Ti) and organic reactants (e.g., ethylene glycol and glycerol). Despite their unique properties, metalcones exhibit significant vulnerability to water due to their organic components, limiting their potential in electrochemical applications. This study focuses on enhancing the photoelectrochemical stability of tincone thin films in aqueous electrolyte while preserving their hybrid characteristics through mild annealing in air at 250 °C. As-deposited and vacuum-annealed tincone thin films exhibited significant degradation under these conditions, while high-temperature-annealed (500 °C) tincone thin films offered improved stability with a significant decline in charge transfer efficiency. In contrast, mild annealing in air maintained the C–O bond at half level and improved the stability and charge transport without compromising the unique characteristics of tincone. This was confirmed by ellipsometry, X-ray photoelectron spectroscopy (XPS), and Fourier transform infrared spectroscopy (FTIR). Mild-annealed tincone deposited on a lightly doped p-type silicon (p-Si) photocathode produced a 20-fold increase in CO volume compared to high-temperature annealed tincone in a CO 2 -saturated potassium bicarbonate (KHCO 3 ) electrolyte with dispersed graphene oxide–cobalt phthalocyanine (GO-CoPc) under 1 sun illumination at 0.9 V vs reversible hydrogen electrode (RHE), while maintaining the faradaic efficiency for CO and H 2 . These results suggest that mild-annealed tincone thin films hold significant potential as protective charge transport layers on silicon photocathodes for the aqueous CO 2 reduction reaction (CO 2 RR).

Annealing (metallurgy)

Structure of Self-Generated Magnetic Fields in Laser-Solid Interaction from Proton Tomography

Self-generated magnetic fields in laser-solid interactions are experimentally characterized to reveal the 3D location and local field strength, rather than path-integrated quantities, using multi-view proton radiography and tomographic inversion. We infer magnetic fields that extend several millimeters off the target into the hot, rarefied corona, sufficient to strongly magnetize the plasma (Ω e τ e ≫ 1). The data are compared to MHD simulations incorporating recent improvements in modeling magnetic field generation and transport; the volume-averaged coronal field strength and magnetic flux agree to within 25% using a model with magnetic re-localization of transport, although the near-target morphology is not reproduced. This work demonstrates tomographic proton radiography as a valuable tool for investigating magnetic fields in laser-produced plasmas.

High-energy-density plasmas

32 examples of LLM applications in materials science and chemistry: towards automation, assistants, agents, and accelerated scientific discovery

Abstract Large language models (LLMs) are reshaping many aspects of materials science and chemistry research, enabling advances in molecular property prediction, materials design, scientific automation, knowledge extraction, and more. Recent developments demonstrate that the latest class of models are able to integrate structured and unstructured data, assist in hypothesis generation, and streamline research workflows. To explore the frontier of LLM capabilities across the research lifecycle, we review applications of LLMs through 32 total projects developed during the second annual LLM hackathon for applications in materials science and chemistry, a global hybrid event. These projects spanned seven key research areas: (1) molecular and material property prediction, (2) molecular and material design, (3) automation and novel interfaces, (4) scientific communication and education, (5) research data management and automation, (6) hypothesis generation and evaluation, and (7) knowledge extraction and reasoning from the scientific literature. Collectively, these applications illustrate how LLMs serve as versatile predictive models, platforms for rapid prototyping of domain-specific tools, and much more. In particular, improvements in both open source and proprietary LLM performance through the addition of reasoning, additional training data, and new techniques have expanded effectiveness, particularly in low-data environments and interdisciplinary research. As LLMs continue to improve, their integration into scientific workflows presents both new opportunities and new challenges, requiring ongoing exploration, continued refinement, and further research to address reliability, interpretability, and reproducibility.

Computer Science