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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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205 records · Page 12

Periodic GFN1-xTB Tight Binding: A Generalized Ewald Partitioning Scheme for the Klopman–Ohno Function

A novel formulation is presented for the treatment of electrostatics in the periodic GFN1-xTB tight-binding model. Periodic GFN1-xTB is hindered by the functional form of the second-order electrostatics, which only recovers Coulombic behavior at large interatomic distances and lacks a closed-form solution for its Fourier transform. We address this by introducing a binomial expansion of the Klopman–Ohno function to partition short- and long-range interactions, enabling the use of a generalized Ewald summation for the solution of the electrostatic energy. This approach is general and is applicable to any damped potential of the form |R n + c| –m . Benchmarks on the X23 molecular crystal dataset and a range of prototypical bulk semiconductors demonstrate that this systematic treatment of the electrostatics eliminates unphysical behavior in the equation of state curves. In the bulk systems studied, we observe a mean absolute error in total energy of 35 meV/atom, comparable to the machine-learned universal force field, M3GNet, and sufficiently precise for structure relaxation. These results highlight the promising potential of GFN1-xTB as a universal tight-binding parametrization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Complexity of many-body interactions in transition metals via machine-learned force fields from the TM23 data set

Abstract This work examines challenges associated with the accuracy of machine-learned force fields (MLFFs) for bulk solid and liquid phases ofd-block elements. In exhaustive detail, we contrast the performance of force, energy, and stress predictions across the transition metals for two leading MLFF models: a kernel-based atomic cluster expansion method implemented using sparse Gaussian processes (FLARE), and an equivariant message-passing neural network (NequIP). Early transition metals present higher relative errors and are more difficult to learn relative to late platinum- and coinage-group elements, and this trend persists across model architectures. Trends in complexity of interatomic interactions for different metals are revealed via comparison of the performance of representations with different many-body order and angular resolution. Using arguments based on perturbation theory on the occupied and unoccupieddstates near the Fermi level, we determine that the large, sharpddensity of states both above and below the Fermi level in early transition metals leads to a more complex, harder-to-learn potential energy surface for these metals. Increasing the fictitious electronic temperature (smearing) modifies the angular sensitivity of forces and makes the early transition metal forces easier to learn. This work illustrates challenges in capturing intricate properties of metallic bonding with current leading MLFFs and provides a reference data set for transition metals, aimed at benchmarking the accuracy and improving the development of emerging machine-learned approximations.

Chemistry↗

Minimization of Disorder as a Key Design Principle for Natural Sizes of Light Harvesting 2 Complexes

The light harvesting 2 (LH2) complex of purple bacteria has excellent energy conversion efficiency. Clarifying the design principle behind such efficiency at the atomistic level is crucial for understanding its structure–function relationship and can be utilized for the design of artificial light harvesting systems. To this end, we conducted comprehensive computational investigation of the dynamical and statistical nature of electronic excited states of pigment molecules in a natural LH2 complex with 9-fold symmetry and its two non-natural in silico analogues with 6- and 12-fold symmetries. To ensure reliable and efficient all-atomistic molecular dynamics simulations, we combined a well established interpolation approach for the construction of the potential energy surface with a neural network machine learning approach. Outcomes of these calculations clarify that non-natural forms of LH2-type complexes have significantly larger quasistatic disorder than those for the natural one. In addition, non-natural systems have more disruptions of the hydrogen bonding, underscoring its crucial role for reducing the disorder. On the other hand, local environmental dynamics are relatively insensitive to the structural changes although there is moderate enhancement in the anharmonic or interatomic components for the synthetic ones. These findings based on all-atomistic simulations provide direct computational evidence that the structure and sizes of natural LH2 complexes are designed to minimize the energetic disorder. We analyze quantitative implications of these for the energy transferring capability of the LH2 complex.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multitarget Rydberg gates via spatial blockade engineering

Multi-target gates offer the potential to reduce gate depth in syndrome extraction for quantum error correction. Although neutral-atom quantum computers have demonstrated native multi-qubit gates, existing approaches that avoid additional control or multiple atomic species have been limited to single-target gates. We propose single-control-multi-target CZ^n gates on a single-species neutral-atom platform that require no extra control and have gate durations comparable to standard CZ gates. Our approach leverages tailored interatomic distances to create an asymmetric blockade between the control and target atoms. Using a GPU-accelerated pulse synthesis protocol, we design smooth control pulses for CZZ and CZZZ gates, achieving fidelities of up to 99.55% and $99.24\%$, respectively, even in the presence of simulated atom placement errors and Rydberg-state decay. Our approach is most effective for N=2 (CZZ) and N=3 targets (CZZZ); for larger N, increasing spatial crowding of the targets introduces significant challenges for maintaining the required blockade asymmetry. This work presents a practical path to implementing low-overhead multi-target gates in single-species neutral-atom systems, significantly reducing the resource overhead for syndrome extraction. To motivate the impact of these gates, we apply a greedy scheduling algorithm and we demonstrate that our proposed gates can reduce the number of atom reconfiguration costs by up to 50% for color code syndrome extraction of code distances greater than 5.

Stein, Samuel A.↗

Hund’s flat band in a frustrated spinel oxide

Electronic flat bands associated with quenched kinetic energy and heavy electron mass have attracted great interest for promoting strong electronic correlations and emergent phenomena such as high-temperature charge fractionalization and superconductivity. Intense experimental and theoretical research has been devoted to establishing the rich nontrivial metallic and heavy fermion phases intertwined with such localized electronic states. Here, in this study, we investigate the transition metal oxide spinel LiV 2 O 4 , an enigmatic heavy fermion compound lacking localized f orbital states. We use angle-resolved photoemission spectroscopy and dynamical mean-field theory to reveal a kind of correlation-induced flat band with suppressed interatomic electron hopping arising from intra-atomic Hund’s coupling. The appearance of heavy quasiparticles is ascribed to a proximate orbital-selective Mott state characterized by fluctuating local moments as evidenced by complementary magnetotransport measurements. The spectroscopic fingerprints of long-lived quasiparticles and their disappearance with increasing temperature further support the emergence of a high-temperature “bad” metal state observed in transport data. This work resolves a long-standing puzzle on the origin of heavy fermion behavior and unconventional transport in LiV 2 O 4 . Simultaneously, it opens a path to achieving flat bands through electronic interactions in d-orbital systems with geometrical frustration, potentially enabling the realization of exotic phases of matter such as the fractionalized Fermi liquids.

36 MATERIALS SCIENCE↗

Fast and accurate calculation of EXAFS Debye-Waller factors in U⁢O2 using the dynamical matrix method

Theoretical modeling of bonding dynamics in metal oxides is required for predicting their thermal conductivity, catalytic activity, and mechanical properties. A primary challenge is the scarcity of experimental methods for validating theoretical predictions of these atomic-scale dynamics. This work presents a workflow that uses experimental extended x-ray absorption fine structure (EXAFS) data collected at high temperatures to validate an interatomic force field for uranium dioxide (UO2), an important model material. The validated force field is then used to drive computationally intensive molecular dynamics (MD) simulations and as input for the much faster dynamical matrix Debye-Waller (DMDW) method. The predicted values of the Debye-Waller factors from the DMDW calculations are in good agreement with those obtained from the MD simulations, with residual pair-specific differences attributable to quantum zero-point motion at low temperatures and lattice anharmonicity at high temperatures. We further show that theoretical EXAFS spectra constructed directly from DMDW-derived Debye-Waller factors reproduce the experimental data (at relatively low temperatures) with accuracy comparable to full MD-EXAFS, providing an additional validation of the choice of the potential. This study establishes a validated, rapid computational pathway for modeling bond dynamics, naturally incorporating quantum nuclear\\\\r\\\\nstatistics absent in classical simulations, which are essential for the mechanistic understanding of complex oxide materials.

58 GEOSCIENCES↗

Influence of isoelectronic mass modulation on phonon decay and transport in layered pnictogen-carbon systems

This study systematically investigates the structural, electronic, and thermal transport properties of layered pnictogen–carbon (Pn 2 C 2 ; Pn = P, As, Sb, Bi) monolayers, revealing a profound influence of isoelectronic mass modulation on phonon dynamics and thermal conductivity. Through first-principles calculations and lattice dynamics analysis, we demonstrate that increasing the atomic mass of pnictogens leads to elongated Pn-C bonds, weakened interatomic interactions, and enhanced phonon-phonon scattering, resulting in a dramatic reduction in lattice thermal conductivity (κ). Specifically, κ decreases exponentially from 65.6 W/m-K in P 2 C 2 to an ultralow 0.37 W/m-K in Bi 2 C 2 , driven by suppressed acoustic-optical phonon gaps Δ$^{Γ}_{A-0}$, increased anharmonicity, and reduced phonon lifetimes and group velocities. The transition from semiconducting to metallic behavior in heavier pnictogen-based systems further enhances phonon-electron scattering, contributing to thermal conductivity suppression. Structural analysis highlights the strengthening of out-of-plane C—C bonds and the contraction of C—Pn—C bond angles, which disrupt in-plane phonon transport. Further, these findings establish a design framework for engineering ultralow-κ materials through chemical substitution and structural tuning, offering significant potential for thermoelectric and thermal management applications. This work provides fundamental insights into phonon decay mechanisms and thermal transport in 2D materials, paving the way for advanced phononic and energy-efficient devices.

2D materials↗