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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 1,405 records · Page 78

Geometry-aware framework for deep energy method: An application to structural mechanics with hyperelastic materials

Here, in this work, we introduce a novel physics-informed framework named the Geometry-Aware Deep Energy Method (GADEM) for solving structural mechanics problems on different geometries. As the weak form of the physical system equation (or the energy-based approach) has demonstrated clear advantages compared to the strong form for solving solid mechanics problems, GADEM employs the weak form and aims to infer the solution on multiple shapes of geometries. Integrating a geometry-aware framework into an energy-based method results in an effective physics-informed deep learning model in terms of accuracy and computational cost. Different ways to represent the geometric information and to encode the geometric latent vectors are investigated in this work. We introduce a loss function of GADEM which is minimized based on the potential energy of all considered geometries. An adaptive learning method is also employed for the sampling of collocation points to enhance the performance of GADEM. We present some applications of GADEM to solve solid mechanics problems, including a loading simulation of a toy tire involving contact mechanics and large deformation hyperelasticity. The numerical results of this work demonstrate the remarkable capability of GADEM to infer the solution on various and new shapes of geometries using only one trained model.

97 MATHEMATICS AND COMPUTING↗

Al-alkyls as acceptor dopant precursors for atomic-scale devices

Atomically precise ultradoping of silicon is possible with atomic resists, area-selective surface chemistry, and a limited set of hydride and halide precursor molecules, in a process known as atomic precision advanced manufacturing (APAM). It is desirable to expand this set of precursors to include dopants with organic functional groups and in this work we consider aluminium alkyls, to expand the applicability of APAM. We explore the impurity content and selectivity that results from using trimethyl aluminium and triethyl aluminium precursors on Si(001) to ultradope with aluminium through a hydrogen mask. Comparison of the methylated and ethylated precursors helps us understand the impact of hydrocarbon ligand selection on incorporation surface chemistry. Combining scanning tunneling microscopy and density functional theory calculations, we assess the limitations of both classes of precursor and extract general principles relevant to each.

36 MATERIALS SCIENCE↗

Combined Experimental and Computational Efforts to Establish Ion Mobility, Solubility and Stability of Functional Liquids for Electrochemical Energy Storage

This work provides a computation-driven investigation of the stability of organic electrolytes for lithium-air batteries. Electrolyte instability is currently a key challenge that limits practical use of aprotic Li-air batteries, and the chemical processes that cause this instability are often kinetically-driven. Computational screening for kinetic stability involves the determination of reaction barriers for the numerous potential reaction mechanisms, barriers that are challenging to calculate due to the difficulty of locating transition state structures. Here we screen a broad set of substituted electrolytes for susceptibility to nucleophilic attack by superoxide. We find that carbonates are not typically expected to be stable and that sulfones are generally stable, validating literature trends. We study the effects of chemical functionalization with electron-donating and withdrawing groups and their interplay with steric factors, identifying functional groups and other chemical modifications that increase stability in these groups. User-input driven transition state identification is used for these initial calculations, and an automated computational pipeline is subsequently presented and validated as a means to perform further high-throughput searches across mechanisms and chemistries. The pipeline integrates cheminformatics-based reaction encoding, relaxed potential energy scans, and nudged elastic band calculations for an end-to-end approach to barrier calculations. We review this automated search approach and its current limitations, and discuss challenges and further work.

25 ENERGY STORAGE↗

Ultrafast Formation of Charge Transfer Trions at Molecular‐Functionalized 2D MoS 2 Interfaces

In this work, we investigate trion dynamics occurring at the heterojunction between organometallic molecules and a monolayer transition metal dichalcogenide (TMD) with transient electronic sum frequency generation (tr-ESFG) spectroscopy. By pumping at 2.4 eV with laser pulses, we have observed an ultrafast hole transfer, succeeded by the emergence of charge-transfer trions. This observation is facilitated by the cancellation of ground state bleach and stimulated emission signals due to their opposite phases, making tr-ESFG especially sensitive to the trion formation dynamics. The presence of charge-transfer trion at molecular functionalized TMD monolayers suggests the potential for engineering the local electronic structures and dynamics of specific locations on TMDs and offers a potential for transferring unique electronic attributes of TMD to the molecular layers.

Time-resolved↗

A soft ring oscillator

Periodic actuation of multiple soft, pneumatic actuators requires coordinated function of multiple, separate components. This work demonstrates a soft, pneumatic ring oscillator that induces temporally coordinated periodic motion in soft actuators using a single, constant-pressure source, without hard valves or electronic controls. The fundamental unit of this ring oscillator is a soft, pneumatic inverter (an inverting Schmitt trigger) that switches between its two states (“on” and “off”) using two instabilities in elastomeric structures: buckling of internal tubing and snap-through of a hemispherical membrane. An odd number of these inverters connected in a loop produces the same number of periodically oscillating outputs, resulting from a third, system-level instability; the frequency of oscillation depends on three system parameters that can be adjusted. These oscillatory output pressures enable several applications, including undulating and rolling motions in soft robots, size-based particle separation, pneumatic mechanotherapy, and metering of fluids. The soft ring oscillator eliminates the need for hard valves and electronic controls in these applications.

Robotics↗

N -Terminal Octylated Peptoid Hydrogels as 3D-Printable Cell Scaffolds and Proteolytically Robust Cargo Depots

Supramolecular hydrogels that mimic the extracellular matrix (ECM) represent promising materials for tissue engineering and drug delivery. However, conventional hydrogels formed via the self-assembly of natural or synthetic building blocks often face a trade-off between biological functionality and biochemical stability, limiting their utility in long-term or protease-rich environments. Peptoids, a class of peptide-inspired, sequence-defined polymers, offer a compelling alternative due to their exceptional proteolytic resistance and bioactivity. Despite this potential, the development of supramolecular peptoid hydrogels has been hindered by the absence of backbone hydrogen bond donors, which limits long-range ordering necessary for efficient hydrogel formation. This work describes a short peptoid functionalized at the N-terminus with an octyl chain that readily self-assembles into hydrogels. Hydrophobic interactions among pendant octyl groups promote directional peptoid packing into highly ordered nanosheets, which interconnect to form a porous hydrogel network. These hydrogels exhibit tunable viscoelasticity, shear-thinning, and self-healing properties, enabling their use as inks for extrusion-based 3D printing. They support NIH-3T3 fibroblast adhesion, spreading, and proliferation, maintaining greater than 95% cell viability over 4 days. Moreover, the hydrogels retain their macroscopic integrity under protease-rich conditions, enabling sustained cargo release and uniform cellular uptake. Together, this study demonstrates a class of supramolecular peptoid hydrogelators that integrate biocompatibility, 3D printability, and proteolytic stability, providing a versatile platform for ECMmimetic scaffolds in regenerative medicine and long-term therapeutic delivery.

cargo delivery↗

A genetic algorithms approach for altering the membership functions in fuzzy logic controllers

Through previous work, a fuzzy control system was developed to perform translational and rotational control of a space vehicle. This problem was then re-examined to determine the effectiveness of genetic algorithms on fine tuning the controller. This paper explains the problems associated with the design of this fuzzy controller and offers a technique for tuning fuzzy logic controllers. A fuzzy logic controller is a rule-based system that uses fuzzy linguistic variables to model human rule-of-thumb approaches to control actions within a given system. This 'fuzzy expert system' features rules that direct the decision process and membership functions that convert the linguistic variables into the precise numeric values used for system control. Defining the fuzzy membership functions is the most time consuming aspect of the controller design. One single change in the membership functions could significantly alter the performance of the controller. This membership function definition can be accomplished by using a trial and error technique to alter the membership functions creating a highly tuned controller. This approach can be time consuming and requires a great deal of knowledge from human experts. In order to shorten development time, an iterative procedure for altering the membership functions to create a tuned set that used a minimal amount of fuel for velocity vector approach and station-keep maneuvers was developed. Genetic algorithms, search techniques used for optimization, were utilized to solve this problem.

Shehadeh, Hana↗

Spectral function of the $J_1$ – $J_2$ Heisenberg model on the triangular lattice

Spectral probes, such as neutron scattering, are crucial for characterizing excitations in quantum many-body systems and the properties of quantum materials. Among the most elusive phases of matter are quantum spin liquids, which have no long-range order even at zero temperature and host exotic fractionalized excitations with nontrivial statistics. These phases can occur in frustrated quantum magnets, such as the paradigmatic Heisenberg model with nearest- and next-nearest-neighbor exchange interactions on the triangular lattice, the so-called $J_1$ – $J_2$ model. In this work, we compute the spectral function using large-scale matrix product state simulations across the three different phases of this model's phase diagram, including a quantum spin-liquid phase at intermediate $J_2$/$J_1$. Despite a plethora of theoretical and experimental studies, the exact nature of this phase is still contested, with the dominant candidates being a gapped $\mathbb{Z}_2$, a gapless U(1) Dirac, and a spinon Fermi surface quantum spin-liquid state. We find a V-shaped spectrum near the center of the Brillouin zone ($Γ$ point), a key signature of a spinon Fermi surface, observed in prior neutron scattering experiments. However, we find a small gap near the $Γ$ point, ruling out such a phase. Furthermore, we find localized gapless excitations at the corner of the Brillouin zone boundary (K point) and the middle of the edge of the Brillouin zone boundary (M point), ruling out the gapped $\mathbb{Z}_2$ spin-liquid phase. Here, our results imply that the intermediate spin-liquid phase is a gapless $U(1)$ Dirac spin liquid, and provide clear signatures to detect this phase in future neutron scattering experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Remote Density Measurements of Molten Salts via Neutron Radiography

With an increased interest in the use of molten salts in both nuclear and non-nuclear systems, measuring important thermophysical properties of specific salt mixtures becomes critical in understanding salt performance and behavior. One of the more basic and significant thermophysical properties of a given salt system is density as a function of temperature. With this in mind, this work aims to present and layout a novel approach to measuring densities of molten salt systems using neutron radiography. This work was performed on Flight Path 5 at the Los Alamos Neutron Science Center at Los Alamos National Laboratory. In order to benchmark this initial work, three salt mixtures were measured, NaCl, LiCl (58.2 mol%) + KCl (41.8 mol%), and MgCl2 (32 mol%) + KCl (68 mol%). Resulting densities as a function of temperature for each sample from this work were then compared to previous works employing traditional techniques. Results from this work match well with previous literature values for all salt mixtures measured, establishing that neutron radiography is a viable technique to measure density as a function of temperature in molten salt systems. Finally, advantages of using neutron radiography over other methods are discussed and future work in improving this technique is covered.

Long, Alexander M. (ORCID:0000000343009454)↗

New Basis Functions for the Electromagnetic Solution of Arbitrarily-shaped, Three Dimensional Conducting Bodies Using Method of Moments

In this work, we present a new set of basis functions, de ned over a pair of planar triangular patches, for the solution of electromagnetic scattering and radiation problems associated with arbitrarily-shaped surfaces using the method of moments solution procedure. The basis functions are constant over the function subdomain and resemble pulse functions for one and two dimensional problems. Further, another set of basis functions, point-wise orthogonal to the first set, is also de ned over the same function space. The primary objective of developing these basis functions is to utilize them for the electromagnetic solution involving conducting, dielectric, and composite bodies. However, in the present work, only the conducting body solution is presented and compared with other data.

Mackenzie, Anne I.↗

New Basis Functions for the Electromagnetic Solution of Arbitrarily-shaped, Three Dimensional Conducting Bodies using Method of Moments

In this work, we present a new set of basis functions, defined over a pair of planar triangular patches, for the solution of electromagnetic scattering and radiation problems associated with arbitrarily-shaped surfaces using the method of moments solution procedure. The basis functions are constant over the function subdomain and resemble pulse functions for one and two dimensional problems. Further, another set of basis functions, point-wise orthogonal to the first set, is also defined over the same function space. The primary objective of developing these basis functions is to utilize them for the electromagnetic solution involving conducting, dielectric, and composite bodies. However, in the present work, only the conducting body solution is presented and compared with other data.

Mackenzie, Anne I.↗

In-plane and through-plane dielectric properties of graphene oxide membrane: Effect of Al 3 + modification

A graphene oxide (GO) membrane can be used in structural dielectric capacitors and planar micro-supercapacitors as a dielectric separator material due to its excellent through-plane and in-plane dielectric properties. The ability to tailor the dielectric properties of the GO membrane is crucial for dielectric applications. We believe this to be the first demonstration describing how Al 3+ ions impact the dielectric properties of the GO membrane through cation to oxygenated functional groups interactions. In this work, the Al 3+ -modification to the GO membrane was realized through a facile pre-coordination method followed by layer-by-layer assembling. The influence of Al 3+ on the GO membranes’ through-plane and in-plane dielectric properties (dielectric constant and dielectric loss) was investigated in the frequency range from 0.01 Hz to 10 5 Hz. Plane-to-plane and edge-to-edge Al 3+ coordination with the functional group on the basal plane or edge of the GO sheets was proposed to understand the metal ion's impact on the dielectric properties. The results demonstrated that the Al 3+ modification was an effective strategy to tailoring the GO membranes’ dielectric properties in a low frequency regime and further suggested the possibility of designing dielectric GO membranes with controllable dielectric performance. At a low frequency range (0.01–1 Hz), the addition of Al 3+ increased the through-plane dielectric constant and decreased the in-plane dielectric constant. In terms of dielectric loss, unmodified GO membranes exhibited a higher in-plane dielectric loss than the through-plane dielectric loss. Al 3+ -modified GO membranes exhibited increased through-plane dielectric loss and decreased in-plane dielectric loss compared to the unmodified GO membranes.

36 MATERIALS SCIENCE↗

Evaluation of Density-Functional Tight-Binding Methods for Simulation of Protic Molecular Ion Pairs

In this work, we benchmark the accuracy of the density-functional tight-binding (DFTB) method, namely the long-range corrected second-order (LC-DFTB2) and third-order (DFTB3) models, for predicting energetics of imidazolium-based ionic liquid (IL) ion pairs. We compare the DFTB models against popular density functionals such as LC-ωPBE and B3LYP, using ab initio domain-based local pair-natural orbital coupled cluster (DLPNO-CC) energies as reference. Calculations were carried out in the gas phase, as well as in aqueous solution using implicit solvent methods. We find that the LC-DFTB2 model shows excellent performance in the gas phase and agrees well with reference energies in implicit solvent, often outperforming DFTB3 predictions for complexation energetics. Our study identifies a range of opportunities for use of the LC-DFTB method and quantifies its sensitivity to protonation states and the types of chemical interactions between ion pairs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Meta-Generalized Gradient Approximation for the Cavity-Dependent Exchange-Correlation Interaction in Strongly Coupled Light–Matter Systems

Strong light–matter coupling in optical cavities enables the manipulation of chemical and physical properties without altering molecular composition. Theoretical modeling of such phenomena requires exchange-correlation (XC) functionals that account for both electron–electron and electron–photon (ep) interactions within quantum electrodynamical density functional theory (QEDFT). In this work, we develop a meta-generalized gradient approximation (meta-GGA) specifically targeting the cavity-dependent XC interaction in strongly coupled light–matter systems. This novel approximation is built upon a new semilocal polarizability approximation, which draws from the jellium-with-a-gap model, and can be extended to a “global hybrid” variant that goes beyond the isotropic model from previous approximations. The polarizability model yields significantly improved dispersion coefficients and benchmark calculations with the cavity-dependent XC functional demonstrate improved agreement with QED Hartree–Fock (QED-HF) reference energies. Application to the regioselectivity of brominated nitrobenzene intermediates reveals the functional’s capacity to capture cavity-induced energetic shifts. In conclusion, our results advance the Jacob’s ladder of functionals for QEDFT and provide a practical tool for modeling polaritonic chemistry.

Approximation↗

Learning constitutive relations using symmetric positive definite neural networks

In this work, we present a new neural-network architecture, called the Cholesky-factored symmetric positive definite neural network (SPD-NN), for modeling constitutive relations in computational mechanics. Instead of directly predicting the stress of the material, the SPD-NN trains a neural network to predict the Cholesky factor of the tangent stiffness matrix, based on which the stress is calculated in incremental form. As a result of this special structure, SPD-NN weakly imposes convexity on the strain energy function, satisfies the second order work criterion (Hill's criterion) and time consistency for path-dependent materials, and therefore improves numerical stability, especially when the SPD-NN is used in finite element simulations. Depending on the types of available data, we propose two training methods, namely direct training for strain and stress pairs and indirect training for loads and displacement pairs. We demonstrate the effectiveness of SPD-NN on hyperelastic, elasto-plastic, and multiscale fiber-reinforced plate problems from solid mechanics. The generality and robustness of SPD-NN make it a promising tool for a wide range of constitutive modeling applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

UV-Enabled Defect Engineering in Multilayer GaSe and InSe and UV Writing of the Grating Pattern

III–VI post-transition-metal chalcogenides are layered semiconductor materials that exhibit direct band gaps in multilayers. Defect engineering is essential in 2D layered semiconductors for functional devices. Here, in this work, we report defect engineering in multilayer gallium selenide (GaSe) and indium selenide (InSe), where defects generated by ultraviolet (UV, 325 nm) laser irradiation result in an additional photoluminescence (PL) line. The additional PL line is due to defect-bound excitons. Characteristics of the defect emission are similar in GaSe and InSe samples subjected to UV irradiation, air annealing, and hydrostatic pressure. Two-beam UV interference was applied to create grating patterns with a periodic array of low and high densities of defects in GaSe. Density functional theory has identified the defect type in GaSe. The results provide valuable insights into defect generation and UV scribing of photonic circuits in 2D Se-based multilayers for optical integration in a 2D platform.

2D multilayered materials↗

Multilevel Techniques for Compression and Reduction of Scientific Data-Quantitative Control of Accuracy in Derived Quantities

Although many compression algorithms are focused on preserving pointwise values of the data, application scientists are generally more concerned with derived quantities. Equally well, the user may even be willing to accept a high level of lossiness in the compression provided that the compressed data respect certain invariants, such as mass conservation. In the current work, we develop a mathematical framework and techniques that enable data to be adaptively compressed while maintaining a specified tolerance on a class of user-prescribed quantities. Here, the algorithm is used to augment the functionality of the data reduction package MGARD developed in previous work and the functionality is illustrated by a range of application including data from computational simulation of autocatalytic reaction simulation, turbulent combustion simulation, experimental data obtained from magnetic confinement fusion experiment, and simulation of turbulent flow along a rectangular channel. In each case, we consider one or more relevant quantities of interest and reduce the data so as to preserve these quantities.

97 MATHEMATICS AND COMPUTING↗