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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9

Ground and excited state gradients with end-to-end differentiable semiempirical quantum chemistry

Accurate and efficient gradients of molecular energy with respect to nuclear degrees of freedom are essential for geometry optimization and molecular dynamics, including simulations that go beyond the Born–Oppenheimer regime. A common approach involves deriving analytical formulas for new electronic structure methods, which is often conceptually difficult and requires tedious coding. Here, we implement analytical, semi-numerical, and automatic differentiation (AD)-based gradient pathways for semiempirical Hamiltonian models in the PYSEQM software package, leveraging both graphics processing unit (GPU) and central processing unit (CPU) architectures. We further extend these capabilities to excited states calculated using the configuration interaction singles and time-dependent Hartree–Fock ansätze. We benchmark wall time, peak memory usage, and accuracy across three molecular families of varying chemical complexity, including systems of up to a thousand atoms. For ground-state simulations, analytical and AD gradients achieve near-identical GPU runtimes, while semi-numerical gradients are slower on GPU but remain competitive on CPU. For excited states, both analytical and custom AD approaches using implicit differentiation show similar performance and low memory requirements, whereas gradients with full AD are memory-limited. AD gradients match analytical ones in accuracy across all tested systems, aided by a quaternion-based diatomic frame rotation for two-center quantities that ensures smooth energy surfaces. Overall, automatic differentiation emerges as a practical alternative to analytical gradients in semiempirical quantum chemistry, offering high accuracy while allowing seamless integration in AI-driven workflows and popular packages, such as PyTorch and JAX. Our results provide actionable guidance for selecting optimal gradient strategies in large-scale ground- and excited-state molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Characterization of proton-induced damage in thick, p-channel skipper-CCDs

Here, in this work, we characterize the radiation-induced damage in two thick, p-channel skipper-CCDs irradiated unbiased and at room temperature with 217-MeV protons. We evaluate the overall performance of the sensors and demonstrate their single-electron/single-photon sensitivity after receiving a fluence on the order of 10 10 protons/cm 2 . Using the pocket-pumping technique, we quantify and characterize the proton-induced defects from displacement damage. We report an overall trap density of 0.134 traps/pixel for a displacement damage dose of 2.3 × 10 7 MeV/g. Three main proton-induced trap species were identified, V 2 , C i O i and V n O m , and their characteristic trap energies and cross sections were extracted. We found that while divacancies are the most common proton-induced defects, C i O i defects have a greater impact on charge integrity at typical operating temperatures because their emission-time constants are comparable or larger than typical readout times. To estimate ionization damage, we measure the characteristic output transistor curves. We found no threshold voltage shifts after irradiation. Our results highlight the potential of skipper-CCDs for applications requiring high-radiation tolerance and can be used to find the operating conditions in which effects of radiation-induced damage are mitigated.

47 OTHER INSTRUMENTATION↗

Dark matter clumps as sources of gravitational-wave glitches in LIGO-Virgo-KAGRA data

We consider the hypothetical possibility that nonstationary glitch features in the noise of ground-based gravitational-wave detectors could be produced by small dark matter clumps that pass through the earth in the vicinity of gravitational-wave detectors. Here, we first derive the gravitational-wave strain that would be generated by the passage of such a dark matter clump. We find that the strain is primarily sourced by the Newtonian gravitational acceleration of the mirrors toward the clump and by the Shapiro time delay of the photons in the laser beams as they pass through the gravitational potential created by the dark matter clump. We also find that the Newtonian acceleration effect dominates the gravitational-wave strain for both ground and space-based interferometers. We then compare our dark matter clump, gravitational-wave strain model to 84 Koi-Fish glitches detected during the second observing run of the LIGO/Virgo/KAGRA Collaboration through a Markov chain Monte Carlo Bayesian analysis. We find that all glitches but nine can be confidently rejected as having originated from dark matter clumps. For the remaining glitches, the dark matter hypothesis cannot be excluded, and the maximum a posteriori parameters yield minimum densities of about 10 −7 g⁡/cm 3 , within the model. These results allow us to place the first direct upper limits with gravitational-wave detectors on the local over-density of dark matter in the form of clumps in the local neighborhood of Earth, namely 𝜌 DM ⁢clumps ≲ 10 −15 g⁡/cm −3 .

Astronomy and AstroPhysics↗

Large-𝑁 SU(4) Schwinger boson theory for coupled-dimer antiferromagnets

Here, we develop a systematic large-𝑁 expansion based on the Schwinger boson representation of SU(4) coherent states of dimers for the paradigmatic spin-1/2 bilayer square lattice Heisenberg antiferromagnet. This system exhibits a quantum phase transition between a quantum paramagnetic state and a Néel order state, driven by the coupling constant 𝑔 = 𝐽′/𝐽, which is defined as the ratio between the interdimer 𝐽′ and intradimer 𝐽 exchange interactions. We demonstrate that this approach accurately describes static and dynamic properties on both sides of the quantum phase transition. The critical coupling constant 𝑔 𝑐 ≈ 0.42 and the dynamic spin structure factor reproduce quantum Monte Carlo results with high precision. Notably, the 1/𝑁 corrections reveal the longitudinal mode of the magnetically ordered phase along with the overdamping caused by its decay into the two-magnon continuum. The present large-𝑁 SU(4) Schwinger boson theory can be extended to more general cases of quantum paramagnets that undergo a quantum phase transition into magnetically ordered states.

Schwinger boson method↗

Decoupling Failure Pathways in Li-O 2 Cells Operated Under Lean Electrolyte Conditions

The operation of lithium-oxygen (Li-O 2 ) batteries under lean electrolyte conditions offers higher energy density but leads to rapid degradation and short cycle life. Although cathode passivation and electrolyte decomposition occur in all regimes, we show that under lean electrolyte conditions, failure is primarily driven by progressive electrolyte consumption at the lithium/solid electrolyte interphase (SEI), rather than by irreversible cathode passivation. Poor wetting of the lithium surface results in heterogeneous SEI growth and high local current densities, which accelerate electrolyte loss and cell failure. Strategies aimed at improving interfacial stability, including optimized wetting and SEI forming additives, significantly extend cycle life without compromising energy density. Our results establish anode-electrolyte interactions as the dominant degradation mechanism under lean electrolyte conditions, and emphasize the need to engineer a stable Li/SEI interface for long-lasting Li-O 2 batteries.

Córdoba, Daniel [Argonne National Laboratory (ANL)↗

Hacking Kilometer-Scale Models: A Participative Model for Climate Information

In May 2025, nearly 700 participants from all around the world coalesced at 10 regional nodes and a few satellite nodes to take part in a global hackathon of kilometer-scale (horizontal grid spacing < 10 km) regional and global Earth system models. Exciting science is emerging from these efforts, ranging across novel model analysis, new ways of integrating with satellite data, and emulation with machine learning. New technologies were trialed that enable the community to work in new and complementary ways to democratize access to global information at a local scale from a set of the world’s highest-resolution climate models. The hackathon demonstrated how exascale data can be organized to be accessible to anyone. Fundamentally, the community could apply these techniques and technologies to move toward more participative models for coproduction and delivery of diverse sources of climate information for climate scientists and citizens alike.

Climate models↗

Overcoming energy limitation in post-compression of picosecond pulses by free beam propagation in air and temporal pulse splitting and recombining

Cryogenically cooled diode-pumped Yb:YAG has been demonstrated to efficiently generate pulses of >1 J energy and several picoseconds duration at a kilohertz repetition rate. Pulse broadening and post-compression techniques capable of operating at these high pulse energies will expand the use of these lasers in applications requiring shorter pulses. Towards this goal, we demonstrate the post-compression of 5.5 ps pulses with energy in the 0.1 J range by spectral broadening of self-collimated large area beams in air. In proof-of-principle experiments, pulses of 65 mJ energy from a cryogenically cooled Yb:YAG laser were compressed to 1.1 ps after 65 m propagation in a compact setup in which the beam was folded using flat mirrors. Further energy scaling was demonstrated by combining this spectral broadening technique with temporal pulse splitting and recombining. 120 mJ pulses were split into two pulses and coherently recombined with 85% efficiency after 50 m of propagation in air to yield 1.4 ps pulses.

High Energy Laser↗

Spectral broadening and compression of picosecond pulses in air using a multi-pass cell

We report the spectral broadening and post-compression of picosecond pulses using a multi-pass cell (MPC) operating in air. A 2 m-long bi-concave cavity with 41 reflections and 96.4% transmission was designed and implemented, optimized for the compression of 5.5 ps, 4.5 mJ pulses from a Yb:YAG laser operating at 1030 nm. A 19.3-fold spectral broadening was obtained, increasing the bandwidth from 0.3 nm to 5.8 nm, which enabled pulse compression down to 547 fs with a symmetric temporal profile close to the transform limit. These results demonstrate the feasibility of using open-air MPCs for high-energy picosecond pulse post-compression, without the need for sealed chambers, while preserving high mode quality and transmission. Scaling to pulse higher energy is discussed.

Zaldivar Escola, F. [Univ. of Buenos Aires (Argent↗

The DREAMS Project: Disentangling the Impact of Halo-to-halo Variance and Baryonic Feedback on Milky Way Dark Matter Density Profiles

In this work, we utilize a new suite of Milky Way–mass halos from the DREAMS Project, simulated with cold dark matter (CDM), to quantify the influence of baryon feedback and intrinsic halo-to-halo variance on dark matter density profiles. Our suite of 1024 halos varies over supernova and black hole feedback parameters from the IllustrisTNG model, as well as variations in two cosmological parameters. We find that, for the DREAMS parameter variations, Milky Way–mass dark matter density profiles in the IllustrisTNG model are largely insensitive to astrophysics and cosmology variations, with the dominant source of scatter instead arising from halo-to-halo variance. However, most of the (comparatively minor) feedback-driven variations come from the changes to supernova prescriptions. By comparing to dark-matter-only simulations, we find that the strongest supernova wind energies are so effective at preventing galaxy formation that the halos are nearly entirely collisionless dark matter. Finally, regardless of physics variation, all of the DREAMS halos are roughly consistent with a halo contracting adiabatically from the presence of baryons, unlike models that have bursty stellar feedback. This work represents a step toward assessing the uncertainty in Milky Way dark matter profiles, with direct implications for dark matter searches where systematic uncertainty in the density profile remains a major challenge.

Garcia, Alex M. [University of Virginia, Charlotte↗

Direct Observation of Vortex Liquid Droplets in the Iron Pnictide Superconductor CaKFe 4 As 4 at 0.5T c

Type-II superconductors under magnetic fields remain in a quantum-coherent, non-dissipative state as long as vortices are pinned. Dissipation emerges when vortices depin, a process often driven by thermal fluctuations and commonly associated with a melting transition from a vortex solid to a vortex liquid. Macroscopic experiments almost always observe this transition close to the superconducting critical temperature 𝑇 𝑐 . However, how the vortex solid responds to thermal fluctuations at the scale of individual vortices, far below the melting transition, remains largely unexplored. Here, we use scanning tunneling microscopy (STM) to directly visualize vortices in the iron-based superconductor CaKFe 4 ⁢As 4 (𝑇 𝑐 ≈35 K ). We observe the formation of vortex liquid droplets—spatially localized regions where vortices exhibit strong thermal fluctuations—at temperatures as low as 0.5 𝑇 𝑐 . These results demonstrate that the onset of dissipation at the local scale occurs at temperatures significantly below 𝑇𝑐 in type-II superconductors, revealing a previously unrecognized regime of vortex dynamics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Data-driven high-dimensional statistical inference with generative models

Crucial to many measurements at the LHC is the use of correlated multi-dimensional information to distinguish rare processes from large backgrounds, which is complicated by the poor modeling of many of the crucial backgrounds in Monte Carlo simulations. In this work, we introduce HI-SIGMA, a method to perform unbinned high-dimensional statistical inference with data-driven background distributions. In contradistinction to many applications of Simulation Based Inference in High Energy Physics, HI-SIGMA relies on generative ML models, rather than classifiers, to learn the signal and background distributions in the high-dimensional space. These ML models allow for interpretable inference while also incorporating model errors and other sources of systematic uncertainties. We showcase this methodology on a simplified version of a di-Higgs measurement in the bbγγ final state, where the di-photon resonance allows for background interpolation from sidebands into the signal region. We demonstrate that HI-SIGMA provides improved sensitivity as compared to standard classifier-based methods, and that systematic uncertainties can be straightforwardly incorporated by extending methods which have been used for histogram based analyses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Mesoporous Thin Film Architectures: Addressing Material Demands through Molecular Self-Assembly

Mesoporous thin films spark interest across a wide range of disciplines due to their tunable nanostructures, large internal surface areas, and strong compatibility with planar optical, electronic, and microfluidic devices. While attention in the porous materials community has shifted toward macroporous or disordered nanoporous systems, a resurgence in mesoporous thin film research is underway, driven by new molecular self-assembly methods, advanced materials chemistry, and improved characterization techniques. The integration of high-χN block copolymer design, kinetically persistent micelle templating, and postdeposition processing protocols now allows control over structural parameters such as pore size, wall thickness, porosity, and connectivity. These advances have overcome many of the thermodynamic and processing constraints that previously limited widespread adoption. Rather than serving only as high-surface-area supports, mesoporous thin films are engineered as active interfaces where responsive chemistries and nanoscale confinement act in tandem. Embedding switchable ligands, thermoresponsive polymers, redox mediators, or ion-selective groups directly within the pore walls enables real-time control over transport, optical, and electrochemical properties. These capabilities open up new directions in adaptive coatings, gated membranes, and fast-response biosensors. To further expand their functional scope, mesoporous films are integrated into hierarchical and multicomponent architectures. Techniques such as triblock terpolymer templating, crack-directed assembly, and nanoimprint lithography allow for control over spatial organization on the micron and submicron scale and pore system orientation. This enables programmable anisotropy, enhanced molecular diffusion, and wavelength-selective photonic behavior, essential for next-generation sensing, catalysis, and energy applications. Such structural and functional complexity requires equally sophisticated characterization. Multimodal and in situ techniques can track material dynamics under operational conditions. Recent progress includes extended-range ellipsometric porosimetry (EP) for hierarchical architectures, vacuum EP for interface energetics, time-resolved EP for diffusion kinetics, and correlative AFM-SAXS mapping. The introduction of advanced neutron-based spectroscopies, particularly quasielastic neutron scattering (QENS), promises to provide real-time access to ion transport dynamics and segmental motion under nanoscale confinement, offering a path toward deeper mechanistic understanding of structure-performance correlations in mesoporous systems. This Account reflects the technical advances made and the interdisciplinary collaborations that have shaped our collective vision. The particular dimensions of mesopores enable us to subtly tune interactions at the molecular, interfacial, and mesoscopic levels that permit us to harness nanoconfinement. What emerges is a versatile, modular platform capable of chemical gating, energy transduction, and sensing with a level of tunability unmatched by other porous materials. We highlight critical challenges including the need for more robust large-area processing, a deeper understanding of dynamic behavior under cycling, and better integration with device-level architectures. Our strategies support the transition of mesoporous thin films into active high-performance components in next-generation energy, environmental, and biomedical systems.

oxides↗

Structural and Dynamic Heterogeneity of Deep Eutectic Solvents Composed of Choline Chloride and Ortho-Phenol Derivatives

Structural, thermal, and dynamic properties of four deep eutectic solvents comprising choline chloride paired with ortho-phenolic derivative hydrogen-bond donors were probed using experiments and molecular simulations. The hydrogen-bond donors include phenol, catechol, o-chlorophenol, and o-cresol, in a 3:1 mixture with the hydrogen-bond acceptor choline chloride. Density, viscosity, and pulsed-field gradient NMR diffusivity measurements were conducted over a range of temperatures. Classical and ab initio molecular dynamics simulation results match experimental data reasonably well. Furthermore, the simulation results were then used to perform a more detailed analysis of the local structure and dynamics of these systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Leveraging Multiproton-Coupled Electron Transfer to Improve Ir(III) Photocatalyst Efficiency

In photoredox reactions, charge recombination (CR) limits quantum yields, hindering the efficient conversion of light energy into catalytic activity. To address this, we drew inspiration from redox relays in photosystem II (PSII) and developed a new series of iridium(III) complexes featuring covalently attached benzimidazole-phenol-pyridine (BIP-Py) groups to facilitate intramolecular multiproton-coupled electron transfer (MPCET). Herein, we evaluate the effects of MPCET through an extended and well-defined hydrogen-bond network to improve photocatalytic activity and mitigate rapid charge recombination. Infrared spectroelectrochemistry reveals pyridine protonation upon phenol oxidation, while visible spectroelectrochemistry and transient absorption spectroscopy confirm the electro- and photochemical formation of chargeseparated states (CSS) involving oxidized BIP, resulting from intramolecular proton-coupled electron transfer (PCET). The application of the BIP-Py platform in a photocatalytic Nhydroxyphthalimide ester reduction reaction resulted in a ∼106-fold reduction in CR rate and a quantum yield enhancement of up to 157%. Our findings suggest that incorporating MPCET-based redox relays into photocatalyst frameworks is an effective strategy to enhance the efficiency of photocatalytic systems.

Catalysts↗

High-Performance Semiempirical Excited-State Molecular Dynamics Powered by Graphics Processing Units

Here, this Letter introduces excited-state molecular dynamics in PYSEQM, a GPU-accelerated semiempirical quantum chemistry engine implemented in PyTorch. The new module enables Born–Oppenheimer molecular dynamics (BOMD) using configuration-interaction singles and random phase approximation for excited states, allowing long trajectories and large statistical ensembles to be simulated efficiently on a single GPU. We also implement an extended Lagrangian excited-state BOMD (XL-ESMD) scheme that propagates auxiliary electronic variables, enabling relaxed ground and excited-state convergence thresholds without compromising energy conservation. The excited-state BOMD implementation scales smoothly from small chromophores to a nearly 900-atom dendrimer (taking 6.5 s per MD step). PYSEQM also supports batched execution, allowing many geometries or trajectories to be evaluated in a single GPU launch, substantially increasing throughput and making ensemble-based protocols routine. As a demonstration, we compute absorption, emission, and infrared spectra from trajectories propagated on the ground and first excited states. The XL-ESMD scheme yields identical spectra at significantly lower computational cost, establishing the role of extended Lagrangian based dynamics for efficient excited-state BOMD simulations. Beyond raw performance, PYSEQM’s PyTorch foundation provides automatic differentiation for forces, efficient GPU batching, and seamless interfacing with machine learning models. These capabilities position PYSEQM as a practical platform for machine learning-augmented excited-state dynamics and lay the foundation for future data-driven nonadiabatic excited-state dynamics modeling of ultrafast spectroscopic probes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Influence of Grafting Density and the Ionic Environment on the Structure of Zwitterionic Brushes

Zwitterionic polymer brushes possess a high potential for applications as surface coatings, e.g., in antifouling applications. Their complex association behavior due to the coexistence of oppositely charged groups on the same monomeric unit allows for a broad variation of polarity, hydrophilicity, and the antipolyelectrolyte effect with the variation of the surrounding environment. In this study, planar polysulfobetaine brushes were investigated with neutron reflectometry (NR) and neutron spin–echo spectroscopy under grazing incidence (GINSES) to explore the brush structure and its inner dynamics perpendicular to the substrate. In particular, the effects of the substrate–initiator system and ionic strength on the structure were investigated with neutron reflectometry and a swelling by a factor of 3–5 was found in the presence of aqueous NaCl and MgCl 2 solutions compared to the dry state. During the data analysis, the applicability of a model-free evaluation was also demonstrated for the investigated polysulfobetaine brushes. Furthermore, it was found with GINSES that in contrast to neutral brushes, these polysulfobetaine brushes do not show the typical concentration fluctuations in the nanosecond time range when partially swollen with salt-free water.

36 MATERIALS SCIENCE↗

Molecular-Level Insights into the NMR Relaxivity of Gadobutrol Using Quantum and Classical Molecular Simulations

MRI is an indispensable diagnostic tool in modern medicine; however, understanding the molecular-level processes governing NMR relaxation of water in the presence of MRI contrast agents remains a challenge, hindering the molecular-guided development of more effective contrast agents. By using quantum-based polarizable force fields, the first-of-its-kind molecular dynamics (MD) simulations of Gadobutrol are reported where the 1 H NMR longitudinal relaxivity r 1 of the aqueous phase is determined without any adjustable parameters. The MD simulations of r 1 dispersion (i.e., frequency dependence) show good agreement with measurements at frequencies of interest in clinical MRI. Importantly, the simulations reveal key insights into the molecular level processes leading to r 1 dispersion by decomposing the NMR dipole–dipole autocorrelation function G(t) into a discrete set of molecular modes, analogous to the eigenmodes of a quantum harmonic oscillator. The molecular modes reveal important aspects of the underlying mechanisms governing r 1 , such as its multiexponential nature and the importance of the second eigenmodal decay. By simply analyzing the MD trajectories on a parameter-free approach, the Gadobutrol simulations show that the outer-shell water contributes ∼50% of the total relaxivity r 1 compared to the inner-shell water, in contrast to simulations of (nonchelated) gadolinium-aqua where the outer shell contributes only ∼15% of r 1 . The deviation between simulations and measurements of r 1 below clinical MRI frequencies is used to determine the low-frequency electron-spin relaxation time for Gadobutrol, in good agreement with independent studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pulsed laser deposition of delafossite oxide thin films on YSZ (001) substrates as solar water splitting photocathodes

Development of solar energy converters with earth-abundant and environmentally friendly materials is one of the key routes explored towards a sustainable future. In this work, crystalline delafossite-phase CuAlO 2 and CuFeO 2 thin film solar water splitting photocathodes were fabricated using pulsed laser deposition. It was found that the desired delafossite phase was formed only after high temperature annealing in an oxygen-free atmosphere. Further, the homogeneous delafossite bulk structure of the films was determined by correlating simulation results from first-principles calculations with synchrotron-based X-ray absorption near edge structure (XANES) spectroscopy. Both CuAlO 2 and CuFeO 2 photocathodes are active for solar water splitting, with the latter more efficient due to its narrower band gap and improved light absorption.

36 MATERIALS SCIENCE↗