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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

A continuous symmetry breaking measure for finite clusters using Jensen-Shannon divergence

A quantitative measure of symmetry breaking is introduced that allows the quantification of which symmetries are most strongly broken due to the introduction of some kind of defect in a perfect structure. The method uses a statistical approach based on the Jensen-Shannon divergence. The measure is calculated by comparing the transformed atomic density function with its original. Software code is presented that carries the calculations out numerically using Monte Carlo methods. The behavior of this symmetry breaking measure is tested for various cases including finite size crystallites (where the surfaces break the crystallographic symmetry), atomic displacements from high symmetry positions, and collective motions of atoms due to rotations of rigid octahedra. Finally, the approach provides a powerful tool for assessing local symmetry breaking and offers new insights that can help researchers understand how different structural distortions affect different symmetry operations.

atomic & molecular structure↗

The ion-ion correlations in organic ionic plastic crystal

Organic ionic plastic crystals (OIPCs) are emerging as promising electrolyte materials for solid-state batteries. However, despite the fast ionic diffusion, OIPCs exhibit relatively low DC conductivity in solid phases caused by strong ion-ion correlations that suppress charge transport. To understand the origin of this suppression, we performed a study of ion dynamics in the OIPC 1-Ethyl-1-methylpyrrolidinium bis (trifluoromethyl sulfonyl) imide [P 12 ][TFSI] utilizing dielectric spectroscopy, light scattering, and Nuclear Magnetic Resonance diffusometry. Comparison of the results obtained in this study with the published earlier results on an OIPC with a completely different structure (Diethyl(methyl)(isobutyl)phosphonium Hexafluorophosphate [P 1,2,2,4 ][PF 6 ]) revealed strong similarities in ion dynamics in both systems. Unlike DC conductivity, which may drop more than ten times between melted and solid phases, diffusion of anions and cations remains high and does not show strong changes at phase transition. The conductivity spectra in the broad frequency range demonstrate unusual shapes in solid phases with an additional step separating fast local ion motions from suppressed long-range charge diffusion controlling DC conductivity. We suggested that in solid phases, anions and cations can jump only between the specific ion sites defined by the crystalline structure. These constraints lead to strong cation-cation and anion-anion correlations strongly suppressing long-range charge transport.

36 MATERIALS SCIENCE↗

Efficient up-conversion in CsPbBr 3 nanocrystals via phonon-driven exciton-polaron formation

Lead halide perovskite nanocrystals demonstrate efficient up-conversion, although the precise mechanism remains a subject of active research. This study utilizes steady-state and time-resolved spectroscopy methods to unravel the mechanism driving the up-conversion process in CsPbBr 3 nanocrystals. Employing above- and below-gap photoluminescence measurements, we extract a distinct phonon mode with an energy of ~7 meV and identify the Pb-Br-Pb bending mode as the phonon involved in the up-conversion process. This result was corroborated by Raman spectroscopy. We confirm an up-conversion efficiency reaching up to 75%. Transient absorption measurements under conditions of sub-gap excitation also unexpectedly reveal coherent phonons for the subset of nanocrystals undergoing up-conversion. This coherence implies that the up-conversion and subsequent relaxation is accompanied by a synchronized and phased lattice motion. This study reveals that efficient up-conversion in CsPbBr 3 nanocrystals is powered by a unique interplay between the soft lattice structure, phonons, and excited states dynamics.

Anti-Stokes Photoluminescence↗

CryoDRGN-AI: neural ab initio reconstruction of challenging cryo-EM and cryo-ET datasets

Proteins and other biomolecules form dynamic macromolecular machines that are tightly orchestrated to move, bind, and perform chemistry. Cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET) can access the intrinsic heterogeneity of these complexes and are therefore key tools for understanding their function. However, 3D reconstruction of the collected imaging data presents a challenging computational problem, especially without any starting information, a setting termed ab initio reconstruction. Here, in this study, we introduce cryoDRGN-AI, a method leveraging an expressive neural representation and combining an exhaustive search strategy with gradient-based optimization to process challenging heterogeneous datasets. Using cryoDRGN-AI, we reveal new conformational states in large datasets, reconstruct previously unresolved motions from unfiltered datasets, and demonstrate ab initio reconstruction of biomolecular complexes from in situ data. With this expressive and scalable model for structure determination, we hope to unlock the full potential of cryo-EM and cryo-ET as a high-throughput tool for structural biology and discovery.

Levy, Axel [Stanford Univ., CA (United States); SL↗

On the anatomy of acoustic emission

Abrupt, local frictional fault failure comprises a displacement that is normally accompanied by acoustic emission (AE)—an impulsive elastic wave broadcast with an amplitude proportional to particle velocity. The aggregate of these displacements is the basic fault motion. In laboratory shear experiments, the examination of a sequence of laboratory earthquakes includes continuous measurements of fault motion and the associated AE that is broadcast. From these measurements, connections between the fault motion and cumulative sum of the AE amplitude can be identified. The composition of the AE broadcasts reveals inhomogeneity in the fault mechanical structure from which they arise. This inhomogeneity can be decomposed into a time invariant AE component and an articulated AE component. The articulated AE component serves as a “state of the fault diagnostic” that follows a distinctive pattern to fault failure. Thus, the articulated AE component can be used directly to monitor the state of the fault.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Spectral broadening and vibronic dynamics of the S2 state of canthaxanthin in the orange carotenoid protein

We have performed a series of broadband multidimensional electronic spectroscopy experiments to probe the electronic and vibrational dynamics of the canthaxanthin chromophore of the Orange Carotenoid Protein (OCP) from Synechocystis sp. PCC 6803 in its photoactivated red state, OCPR. Cross-peaks observed below the diagonal of the two-dimensional electronic spectrum indicate that absorption transitions prepare the bright S2 state of the ketocarotenoid canthaxanthin near to a sequence of conical intersections, allowing passage to the dark S1 state via the Sx intermediate in <50 fs. Rapid damping of excited-state coherent wavepacket motions suggests that the branching coordinates of the conical intersections include out-of-plane deformation and C=C stretching coordinates of the π-conjugated isoprenoid backbone. The unusual proximity of the Franck–Condon S2 state structure to the conical intersections with Sx and S1 suggests that the protein surroundings of canthaxanthin prepare it to function as an excitation energy trap in the OCPR–phycobilisome complex. Numerical simulations using the multimode Brownian oscillator model demonstrate that the ground-state absorption spectrum of OCPR overlaps with the fluorescence emission spectrum of allophycocyanin due to spectral broadening derived especially from the intramolecular motions of the canthaxanthin chromophore in its binding site.

Yang, Kunwei↗

Uncertainty in Synthetic Tropical Cyclone Hazard and Risk Estimates: Insights from RAFT, CHAZ, MIT, STORM, and CLIMADA

We synthesize five complementary tropical cyclone (TC) hazard frameworks—RAFT (physics-based machine learning), CHAZ and MIT (statistical–dynamical), STORM (fully statistical), and CLIMADA (observation-driven resampling)—to characterize uncertainty in wind-related TC metrics relevant to energy applications. All datasets and the IBTrACS observational record are harmonized to a common 6-hourly, 2.5° grid. We compare basin-wide and coastal properties using consistent definitions for TC frequency, mean and maximum intensity, 24-hour intensification, and 6-hour translation speed, and quantify agreement with Pearson r, RMSE, and Kling–Gupta efficiency (KGE) alongside resampling-based confidence intervals. CLIMADA is included for basin context but excluded from coastal skill scoring because it resamples historical IBTrACS; if supplied with projected future tracks from an external hazard model, CLIMADA can be used to simulate future TC scenarios. Results show robust, cross-model signals: (i) a corridor of activity from the tropical Atlantic through the Caribbean into the Bahamas and western subtropical Atlantic; (ii) a meridional dipole in 24-hour intensification (low-latitude strengthening, subtropical weakening); and (iii) a transition from slower tropical motion to faster midlatitude translation. Coastal winds (mean and maximum) consistently cluster from the eastern Gulf into the Bahamas–western Atlantic transition. The largest structural spread occurs in the amplitude and footprint of lifetime maximum intensity and, secondarily, in translation speed; intensification exhibits similar central behavior across frameworks with variability in extremes. Translation speed shows the most uniform coastal agreement. These findings provide a decision envelope for wind-focused risk screening and clarify where uncertainty should be carried forward; wind-only results represent a lower bound on total hazard, motivating integration of surge and rainfall modules and a companion, asset-level damage analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Microscopic Mechanisms of Superionic Na-ion Conductivity in Crystalline and Amorphous NaMOCl 4 (M = Nb, Ta) Solid Electrolytes

Sodium-ion solid electrolytes offer a sustainable route toward next-generation batteries, but few match the performance of their lithium counterparts. Halide-based NaMOCl 4 (M = Nb, Ta) has recently emerged as a promising analogue to LiMOCl 4 , yet its structure–transport relationships remain unclear due to poor crystallinity in experiments. Here, we combine density functional theory and machine-learned molecular dynamics to reveal that crystalline NaMOCl 4 exhibits negligible room-temperature conductivity with high activation barriers arising from vacancy-mediated diffusion below an order–disorder transition. Above this transition, rotational and translational motion of the [MO 2/2 Cl 4 – ] ∞ chains create new Na sites and enhances transport. In contrast, the amorphous phase inherently supports facile, three-dimensional Na diffusion through dynamic framework flexibility. These results show that ordered crystalline phases hinder ionic transport, while disorder – either thermally induced or structural – facilitates it, revising prior assumptions from the Li system and providing design principles for high-conductivity Na halide electrolytes.

Wei, Grace [University of California, Berkeley, CA↗

Atomic-Scale Tracking of Topological Defect Motion and Incommensurate Charge Order Melting

Charge order pervades the phase diagrams of quantum materials where it competes with superconducting and magnetic phases, hosts electronic phase transitions and topological defects, and couples to the lattice generating intricate structural distortions. Incommensurate charge order is readily stabilized in manganese oxides, where it is associated with anomalous electronic and magnetic properties, but its nanoscale structural inhomogeneity complicates precise characterization and understanding of its relationship with competing phases. Leveraging atomic-resolution variable-temperature cryogenic scanning transmission electron microscopy, we characterize the thermal evolution of charge order as it transforms from its ground state in a model manganite system. We find that mobile networks of discommensurations and dislocations generate phase inhomogeneity and induce global incommensurability in an otherwise lattice-locked modulation. Driving the order to melt at high temperatures, the discommensuration density grows, and regions of order locally decouple from the lattice periodicity. Published by the American Physical Society 2025

Schnitzer, Noah (ORCID:0000000210421146)↗

Stochastic modal velocity field in rough-wall turbulence

Stochastically generated instantaneous velocity profiles are used to reproduce the outer region of rough-wall turbulent boundary layers in a range of Reynolds numbers extending from the wind tunnel to field conditions. Each profile consists in a sequence of steps, defined by the modal velocities and representing uniform momentum zones (UMZs), separated by velocity jumps representing the internal shear layers. Height-dependent UMZ is described by a minimal set of attributes: thickness, mid-height elevation, and streamwise (modal) and vertical velocities. These are informed by experimental observations and reproducing the statistical behaviour of rough-wall turbulence and attached eddy scaling, consistent with the corresponding experimental datasets. Sets of independently generated profiles are reorganized in the streamwise direction to form a spatially consistent modal velocity field, starting from any randomly selected profile. The operation allows one to stretch or compress the velocity field in space, increases the size of the domain and adjusts the size of the largest emerging structures to the Reynolds number of the simulated flow. By imposing the autocorrelation function of the modal velocity field to be anchored on the experimental measurements, we obtain a physically based spatial resolution, which is employed in the computation of the velocity spectrum, and second-order structure functions. The results reproduce the Kolmogorov inertial range extending from the UMZ and their attached-eddy vertical organization to the very-large-scale motions (VLSMs) introduced with the reordering process. The dynamic role of VLSM is confirmed in the –u'w' co-spectra and in their vertical derivative, representing a scale-dependent pressure gradient contribution.

42 ENGINEERING↗

Dynamical Inference and 3D Imaging of Magnetized Dusty Plasmas

This is the final technical report for this DOE award. The motion of dust particles in a laboratory plasma has been studied for nearly 30 years and has led to the discovery of strongly-coupled crystalline structures and nonequilibrium dynamics governed by gravitational, hydrodynamic, and electrostatic forces. Many of the inter-particle forces are complex; they can be non-reciprocal, and non-additive. Deciphering the mélange of particle interactions has been a challenging task, nevertheless, magnetized dusty plasmas remains an open challenge with limited understanding. With applications ranging from magnetically-confined plasmas for fusion to near-surface planetary environments, this research field is ripe for well-controlled, laboratory experiments and new theoretical tools. In collaboration with the MDPX experiment at Auburn University, this proposal aims to tease apart both the known and unknown forces that drive dusty plasmas in magnetized environments using high-resolution, three-dimensional imaging and particle tracking coupled with modern dynamical inference and machine learning techniques.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Gaunt and Breit two-electron contributions to mean-field transformations and fine structure splitting

Materials utilized by novel energy systems are often studied using weakly correlated mean-field theories. However, if these systems incorporate heavy elements, relativistic effects must be included. Therefore, a Kramers unrestricted coupled cluster with singles and doubles excitation formalism within a molecular mean-field exact two-component framework (X2C mmf ) using a four-component Dirac–Hartree–Fock (DHF) reference state is presented. The exact X2C mmf transformed normal-order Hamiltonian incorporates all one-electron and two-electron (2e) contributions from the Coulomb, Gaunt, and Breit operators and is used with the equation of motion method to calculate the excitation energies of the alkali group of elements. Using this framework, the effects of 2e Gaunt and Breit integrals are studied. Results demonstrate growing contributions from these integrals to the generated X2C mmf mean-fields and electronic fine structure calculations with increasing atomic number. Overall, this paper outlines the method, its effect within the X2C mmf approach, and lays the foundation for future theoretical development of relativistic calculations within this framework.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Diffraction-quality, ultraflexible protein single crystals engineered with DNA

DNA-functionalized colloidal nanoparticles assemble through flexible, nanoscale DNA hybridization interactions that limit atomic-level structural order. Here, we report a valence-centric strategy that enables DNA-bonded, protein single crystals with unconventional mechanical properties. An octameric enzyme, glutarate L-2-hydroxylase, was site- and number-selectively conjugated with eight self-complementary single-stranded DNA, yielding octavalent molecular bonds. The resulting conjugate assembled into the designed body-centered tetragonal crystals that diffracted to 1.42- to 2.61-angstrom resolution, with contacts mediated by B-form DNA helices spanning 17 to 25 angstroms. Increasing oligonucleotide length induces anisotropic lattice expansion while preserving atomic periodicity, even with partial DNA occupancy. Mechanistic studies suggest that the dynamic motion of unhybridized DNA facilitates crystallization, analogous to fluctuating electron clouds in atomic bonding. Compared with native protein crystals, DNA-hybridized crystals are 23-fold softer. These results challenge the assumption that flexibility is incompatible with structural order and establish a programmable framework for biomolecular crystallization and nanomaterials engineering with atomic precision.

Han, Zhenyu [Department of Chemistry, Northwestern↗

Active interlocking metasurfaces enabled by shape memory alloys

Interlocking metasurfaces (ILMs) are a newly developed joining technology that relies on arrays of interlocking features that transmit force and constrain motion between adjoining bodies in one or more directions. This study explores harnessing the shape memory effect (SME) in Nickel-Titanium shape memory alloys (NiTi SMAs) in structures fabricated using additive manufacturing (AM) to advance the development of active ILMs by creating unit cells that open or close at specific temperatures. The study encompasses designing and fabricating two distinct interlocking array configurations using near-equiatomic NiTi powder and the laser powder bed fusion (L-PBF) AM technique, following a previously developed AM process optimization framework to manufacture defect-free parts. To guide the design process, finite element analysis (FEA) was employed to predict strain values during engage-disengage cycles. The martensitic transformation characteristics of the ILMs were characterized. Thermomechanical testing revealed that the ILMs demonstrate high locking force once engaged, coupled with complete shape recovery and good cyclic stability. Digital image correlation (DIC) was also employed to validate the FEA predictions during the engage-disengage cycles. The results indicate that NiTi SMA-based ILMs can be designed and fabricated into complex shapes using L-PBF. By leveraging the SME, the functionality of an ILM can be improved upon. The combination of computational modeling, additive manufacturing, and thermomechanical and physical property characterization provides a framework for designing future ILMs out of active materials.

Additive manufacturing↗

Hybrid epoxy–acrylate resins for wavelength-selective multimaterial 3D printing

Structures in nature have evolved to combine hard and soft materials in precise 3D arrangements, which imbues bulk properties and functionality that remain elusive to mimic synthetically. However, the potential for biomimetic analogs to seamlessly interface hard materials with soft surfaces for applications ranging from robotics and sealants to medical devices (e.g., prosthetics and wearable health monitors) has driven the demand for innovative chemistries and manufacturing approaches. Herein, we unveil a liquid resin for rapid, high resolution digital light processing (DLP) 3D printing of multimaterial objects with an unprecedented combination of strength, elasticity, and resistance to aging. Two enabling discoveries are the use of a covalently bound (hybrid) epoxy-acrylate monomer that precludes plasticization of soft domains and a wavelength-selective photosensitizer that accelerates cationic curing for hard domains. Using dual projection for multicolor DLP 3D printing (UV and violet light), several bioinspired metamaterial structures are fabricated, including one with hard springs embedded in a soft cylinder to adjust compressive behavior and a detailed knee joint featuring “bones” and “ligaments” for smooth motion. Lastly, the application of this system to facilitate selective stretching for electronic devices is demonstrated with a proof-of-concept device.

36 MATERIALS SCIENCE↗

Neutrons in Structural Biology: Challenges and Opportunities (Workshop Report)

Gaining a thorough understanding of biological systems requires building our knowledge about biological processes from the level of atoms and electrons, and up to whole organisms. Such comprehensive knowledge will allow for a predictive understanding of complex biological systems behavior. It will guide us in the design and development of novel therapeutics and vaccines to tackle existing health threats and to prepare for future pandemics, and it will provide information necessary to create new biomaterials and bio-inspired technologies through manipulation of biological macromolecules, their assemblies, single cells and even microorganisms. Reaching these goals will require a synergistic combination of multiple experimental techniques with molecular calculations and predictive simulations, and the design and development of new techniques and capabilities that bridge current knowledge and technology gaps. Neutron scattering provides unique information about the biomacromolecular structure and function and can play a major role in achieving these goals. A workshop was held to engage the scientific community in identifying pressing challenges in biochemistry, structural biology, enzymology and structure-guided drug design not solved with the current neutron scattering technologies or utilizing other structural biology techniques such as X-ray crystallography, NMR, and cryo-EM. The workshop brought together structural biology, biochemistry and computational experts, as well as early career researchers and students, creating a forum for discussing scientific advancement and collaboration. The workshop included a one-day satellite training workshop where graduate students and postdoctoral researchers were educated in the application of neutron crystallography and small-angle scattering in structural biology. Furthermore, the Instrument Scientific Advisory Board (ISAB) for the development of a macromolecular neutron diffractometer at ORNL’s Second Target Station was introduced at the workshop. The major outcome was that neutrons can provide atomic-level understanding of biomacromolecular structure, function and dynamics which is of paramount importance for addressing the identified challenges. Neutron crystallography, in particular, can resolve long-standing biochemical issues regarding enzyme function by delineating the underlying chemistry and can have a major impact on the design of small-molecule therapeutics, especially in combination with molecular computation (quantum chemistry and molecular dynamics simulations) and the emerging artificial intelligence (AI)-assisted drug design technologies. The unique properties of neutrons, including their high sensitivity to hydrogen and their non-destructive nature, make them ideal probes of biological matter. There is a palpable need in the scientific community to expand and enhance the impact of neutron sciences on biology. Neutron crystallography is the only structural biology method capable of determining positions of all hydrogen atoms in proteins, nucleic acids and their complexes at near-physiological temperatures and of unstable species at cryogenic temperatures. Moreover, neutron analysis is non-ionizing, non-destructive and does not perturb the structure or redox chemistry of active site metal centers and clusters in proteins, which can be invaluable for studying radiation-sensitive metalloprotein complexes. Further, neutron energies used in scattering applications are similar to atomic motions, permitting neutron spectroscopies to characterize the dynamics of biomacromolecules on the picosecond to microsecond timescales. The different sensitivities of neutrons to protium (H) and deuterium (D) isotopes of hydrogen allow enhanced visibility of specific parts of biological complexes through isotopic labeling. The impact of neutrons will be most powerful when neutron scattering is combined with complementary experimental techniques that use photons and electrons, and with high-performance computing. The interconnection and mutuality of the experimental and theoretical capabilities will drive discoveries in biological and health sciences to generate more complete picture of complex biological systems. The major limitation in the field of biological neutron crystallography has been signal-to-noise, demanding large samples that are difficult to produce for the majority of biomacromolecules and limiting the applicability of this technique in biological sciences. A neutron crystallography instrument at the Second Target Station will revolutionize biological science with neutrons by engaging a large scientific community of structural biologists, enabling successful neutron diffraction experiments from radically smaller biomacromolecular crystals, resolving unanswered biochemical questions, and meaningfully contributing to rational drug design. The meeting highlighted 10 grand challenges that will be addressed with this advanced capability over the next decade and beyond, and the recommendations required to help address them are given below.

59 BASIC BIOLOGICAL SCIENCES↗

Bioinspired Design of Dissipative Self-Assembly of Active Materials (Final Technical Report)

The major objective of this DOE-funded research program was to establish general, experimentally validated design principles for dissipative, out-of-equilibrium self-assembly of synthetic active materials. In living systems, structures such as actin filaments and microtubules are maintained far from thermodynamic equilibrium through continuous energy consumption. This persistent nonequilibrium operation enables functions including adaptability, self-healing, directed motion, and force generation—properties that are largely absent in traditional equilibrium soft materials.

36 MATERIALS SCIENCE↗

Smart Droplets Stabilized by Designer Surfactants: From Biomimicry to Active Motion to Materials Healing

The science and technologies of emulsion droplets have been a long‐term focus of extensive research endeavors for their practical utility across a breadth of industries, including pharmaceutical products, oil recovery processes, and the food sciences. However, with advances in materials chemistry and characterization tools, new emerging areas are arising with a focus on “smart droplets”. The versatility of emulsion droplets across is based on their ability to partition and create isolated systems with properties defined by the liquid–liquid interface, while preparative routes allow manipulation of droplet size, stability, and encapsulated contents. As described in this article, significant efforts are being devoted to creating new types of droplets by “activating” this interface through the incorporation of reactive structures that trigger droplet response to applied or environmental stimuli (e.g., pH, temperature, salt, or external fields). Moreover, parallels between droplets and live cells inspire efforts to conceive systems that resemble biological motifs or that can produce cellular behaviors that imitate biology (e.g., swarming, communication, or motion). Here, the authors highlight recent advances in smart droplets, with emphasis on organic, polymer, and/or particle surfactants that give rise to inter‐droplet communication (via aggregation, fusion, division, or mass transfer), droplet vehicles for controlled delivery, autonomous droplet motion, and tunable emulsion inversion. Especially emphasized is the macromolecular design to produce reactive and functional surfactants, which are crucial to responsive droplet behavior and their underlying mechanisms. More generally, the exquisite interplay between materials science and biology inspires the review of this research area that provides unique opportunities for insight and inspiration into the capabilities of new droplet designs.

36 MATERIALS SCIENCE↗