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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Influence of Rigidity–Hydration Coupling on Size-Dependent Diffusion in Hydrated Polymer Membranes

Selective ion transport in polymer membranes depends critically on how penetrant motion couples to polymer dynamics and hydration. Yet, the mechanistic interplay between polymer rigidity, water content, and penetrant size remains poorly understood, especially in the regime where the penetrant diameter, polymer Kuhn length, and correlation length are comparable. Here, we employ coarse-grained molecular dynamics simulations to systematically investigate penetrant diffusion in hydrated polymer networks across a broad range of water volume fractions, chain rigidities, and penetrant sizes. The results reveal a transition from a decoupled regime, where small penetrants diffuse nearly independently of polymer relaxation, to a coupled regime in which large penetrants require cooperative polymer motion for transport. Increasing polymer rigidity amplifies the sensitivity of diffusivity to hydration, particularly at low water content, leading to pronounced deviations from Stokes−Einstein scaling. Comparison with scaling theories and free-volume models shows that classical nanoparticle-based frameworks fail to capture this intermediate regime. To address this gap, we extend the Yasuda model to incorporate polymer rigidity through a single parameter that quantifies the dynamic contribution of chain stiffness to free-volume fluctuations. The resulting model collapses diffusivity data across all sizes, water contents, and rigidities, providing a unified description of penetrant transport in hydrated polymer matrices. Furthermore, these findings establish polymer rigidity as a key, tunable determinant of diffusion and offer a framework for interpreting size-dependent transport in ion-selective membranes.

diffusion↗
DOE OSTI2021

Collective Nanoparticle Dynamics Associated with Bridging Network Formation in Model Polymer Nanocomposites

The addition of nanoparticles (NPs) to polymers is a powerful method to improve the mechanical and other properties of macromolecular materials. Such hybrid polymer–particle systems are also rich in fundamental soft matter physics. Among several factors contributing to mechanical reinforcement, a polymer-mediated NP network is considered to be the most important in polymer nanocomposites (PNCs). Here, we present an integrated experimental–theoretical study of the collective NP dynamics in model PNCs using X-ray photon correlation spectroscopy and microscopic statistical mechanics theory. Silica NPs dispersed in unentangled or entangled poly(2-vinylpyridine) matrices over a range of NP loadings are used. Static collective structure factors of the NP subsystems at temperatures above the bulk glass transition temperature reveal the formation of a network-like microstructure via polymer-mediated bridges at high NP loadings above the percolation threshold. The NP collective relaxation times are up to 3 orders of magnitude longer than the self-diffusion limit of isolated NPs and display a rich dependence with observation wavevector and NP loading. A mode-coupling theory dynamical analysis that incorporates the static polymer-mediated bridging structure and collective motions of NPs is performed. It captures well both the observed scattering wavevector and NP loading dependences of the collective NP dynamics in the unentangled polymer matrix, with modest quantitative deviations emerging for the entangled PNC samples. Here, we identify an unusual and weak temperature dependence of collective NP dynamics, in qualitative contrast with the mechanical response. Hence, the present study has revealed key aspects of the collective motions of NPs connected by polymer bridges in contact with a viscous adsorbing polymer medium and identifies some outstanding remaining challenges for the theoretical understanding of these complex soft materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Toward Continuous, Oriented Covalent Organic Framework Membranes for Precise Molecular Separations

The goal of achieving energy-efficient, precise molecular separations has motivated interest in developing and employing porous crystalline frameworks as membrane materials. Covalent organic frameworks (COFs) are ordered crystalline matrices composed of covalently bonded organic monomers and are synthesized via reversible reticular chemistry. COFs possess high porosity, structural tunability, and chemical and thermal stability, making them ideally suited for emerging, high-value membrane separation processes, such as ion separations, organic solvent nanofiltration, and gas separations. Although a range of COF membranes have been fabricated and tested in the past decade, these membranes are primarily polycrystalline, weakly crystalline, and/or discontinuous, resulting in suboptimal performance. In this review, we identify the properties that make COFs well-suited as membrane materials, while critically outlining the shortcomings of existing disordered COF membranes. We then highlight the recent emergence of highly crystalline, continuous, oriented two-dimensional COF membranes as a promising path forward for highly selective molecular separations. These continuous, oriented COF membranes exhibit tunable one-dimensional nanochannels, allowing for ultrafast molecular transport and precise species selectivity, thereby expanding the set of separations that can be practically achieved with membrane systems. We discuss synthesis and modification techniques that result in continuous, oriented COF membranes and evaluate the performance of such membranes for a variety of molecular separations. We conclude by identifying ongoing challenges in the development of COF membranes and outlining the future of their applications in molecular separations, which will necessarily rely on advancements in the synthesis of continuous, oriented membranes.

COF modification↗
DOE OSTI2023

Organic Matrix Derived from Host–Microbe Interplay Contributes to Pathological Renal Biomineralization

Matrix stones are a rare form of kidney stones. They feature a high percentage of hydrogel-like organic matter, and their formation is closely associated with urinary tract infections. Herein, comprehensive materials and biochemical approaches were taken to map the organic-inorganic interface and gather insights into the host-microbe interplay in pathological renal biomineralization. Surgically extracted soft and slimy matrix stones were examined using micro-X-ray computed tomography and various microspectroscopy techniques. Higher-mineral-density laminae were positive for calcium-bound Alizarin red. Lower-mineral-density laminae revealed periodic acid-Schiff-positive organic filamentous networks of varied thickness. These organic filamentous networks, which featured a high polysaccharide content, were enriched with zinc, carbon, and sulfur elements. Neutrophil extracellular traps (NETs) along with immune response-related proteins, including calprotectin, myeloperoxidase, CD63, and CD86, also were identified in the filamentous networks. Expressions of NETs and upregulation of polysaccharide-rich mucin secretion are proposed as a part of the host immune defense to "trap" pathogens. These host-microbe derived organic matrices can facilitate heterogeneous nucleation and precipitation of inorganic particulates, resulting in macroscale aggregates known as "matrix stones". These insights into the plausible aggregation of constituents through host-microbe interplay underscore the unique "double-edged sword" effect of the host immune response to pathogens and the resulting renal biominerals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Ultra-Low Viscosity and High Magnetic Susceptibility Magnetic Ionic Liquids Featuring Functionalized Diglycolic Acid Ester Rare-Earth and Transition Metal Chelates

Magnetic ionic liquids (MILs) comprise a subcategory of ionic liquids (ILs) and contain a paramagnetic metal center allowing them to be readily manipulated by an external magnetic field. While MILs are popularly employed as solvents in catalysis, separations, and organic synthesis, most low viscosity combinations possess a hydrophilic character that limits their use in aqueous matrices. To date, no study has reported the synthesis and characterization of hydrophobic MILs with viscosities similar to those of hydrophilic MILs and organic solvents while simultaneously exhibiting enhanced magnetic and thermal properties. In this study, diglycolic acid esters are employed as ligands to chelate with paramagnetic metals to produce cations that are paired with metal chelates composed of hexafluoroacetylacetonate ligands to form MILs incorporating multiple metal centers in the cation and anion. Viscosity values below 31.6 cP were obtained for these solvents, the lowest ever reported for hydrophobic MILs. Solubilities in nonpolar solvents such as benzene were observed to be as high as 50% (w/v) MIL-to-solvent ratio while being insoluble in water at concentrations as low as 0.01% (w/v). Effective paramagnetic moment values for these solvents ranged from 5.33 to 15.56 Bohr magnetons (μB), with mixed metal MILs containing multiple lanthanides in the anion generally offering higher magnetic susceptibilities. MILs composed of ligands containing octyl substituents were found to possess thermal stabilities up to 190 °C. The synthetic strategies explored in this study exploit the highly tunable nature of the employed cation and anion pairs to design versatile ultra-low viscosity magnetoactive solvents that possess tremendous potential and applicability in liquid–liquid separation systems, catalysis, and microfluidics where the mechanical movement of the solvent can be easily facilitated using electromagnets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Experimental Investigation of Uranium and Iron Condensation from High-Temperature Plasma Conditions

We used a plasma flow reactor (PFR) to generate synthetic fallout nanoparticles from vapor-phase condensation of two different input concentrations of uranium and iron analytes (U/Fe = 1:1 and 1:2). Synthetic fallout from complex chemical matrices (e.g., mixtures of U and Fe) has not been generated in this setup before and allows for the observation of relative condensation and fractionation of nuclear debris. Experiments were conducted under two different temperature histories with variations in particle flow patterns along the PFR. Transmission electron microscopy (TEM) observation and analysis of the nanoparticles revealed variations in speciation of uranium oxides (UO 2 and α-UO 3 ) depending on the competition between flow mixing and oxygen sequestration by iron. A ternary metal oxide, UFeO 4 , was observed in addition to iron oxides (e.g., FeO and Fe 3 O 4 ), which suggests that fallout models should account for chemical speciation of ternary metal oxides (i.e., UFeO 4 ) and their relative condensation behaviors in addition to those of singular metal oxides (e.g., FeO and UO 2 ). X-ray Energy Dispersive Spectroscopy (EDS) elemental maps showed that some particles had Fe-rich cores surrounded by U-rich regions. This suggests that either condensed U oxides coagulate onto molten Fe oxides or that the increase in iron analyte concentration might drive the system toward a higher degree of supersaturation, leading to earlier formation of iron oxide particles and providing an energetically favored pathway for nucleation of uranium oxides around iron oxide particles.

and nuclear chemistry↗
DOE OSTI2026

A mild calcium carbonate treatment improves moisture resistance and mechanical/interfacial properties of jute and hemp fibers

Natural fibers are attractive, sustainable reinforcements, but often exhibit high moisture uptake and weak bonding with polymer matrices. In this study, jute and hemp were treated by immersion in aqueous calcium carbonate (CaCO3) suspensions (10–40?wt.%, 1.5?h, room temperature) and were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), moisture sorption testing, single-fiber tensile testing, and bundle pull-out testing. SEM showed granular CaCO3 deposition on fiber surfaces, with particulates bridging surface voids and microcracks. At 40 wt.% CaCO3, equilibrium moisture uptake decreased to ~5% (hemp) and ~3% (jute), while tensile strength increased to ~904 MPa (hemp) and ~960 MPa (jute). Apparent interfacial shear strength from pull-out testing increased up to ~1.35 MPa (hemp) and ~0.56 MPa (jute). These results indicate that CaCO3 deposition is a mild, scalable surface treatment that improves moisture resistance, fiber tensile strength, and interfacial load transfer relevant to semi-structural composite applications, including interior and secondary automotive components.

Calcium carbonate treatment↗
DOE OSTI2020

Redox-Based Electrochemical Affinity Sensor for Detection of Aqueous Pertechnetate Anion

Rapid, selective, in-situ detection of TcO4- in multicomponent matrices consisting of interfering anions such as the ubiquitous NO3- and Cl- or the isostructural and isoelectronic CrO42- is challenging. Present sensors mostly lack the selectivity to exclude these interferences, or the sensitivity to meet the detection limits that are lower than the drinking water standards across the globe. This work presents an affinity based electrochemical sensor for TcO4- detection that relies on selective reductive precipitation of aqueous TcO4- induced by a capture probe immobilized on an electrode platform. This results in a direct decrease of the electron transfer current, the magnitude of the decrease being proportional to the amount of TcO4- added. Using this approach, we were able to achieve a detection limit of 1x10-10 M, which is lower than the drinking water standard of 5.2x10-10 M set by United States Environmental Protection Agency. Our proposed approach also allowed us to detect TcO4- from a multicomponent groundwater sample obtained from a well at the Hanford site in Washington (well 299-W19-36) that also contained NO3- , Cl- and CrO42-, without discernably affecting the detection limits.

Chatterjee, Sayandev↗
DOE OSTI2021

Recycled Cardboard Containers as a Low Energy Source for Cellulose Nanofibrils and Their Use in Poly(l-lactide) Nanocomposites

Cellulose nanomaterials have attracted a great deal of interest as sustainable alternatives to nonrenewable or fossil fuel-derived materials, particularly in composite applications. Cellulose nanofibrils (CNF) are most often derived from wood sources through energy-intensive and costly mechanical fibrillation processes. Here, recycled cardboard, referred to as old corrugated cardboard (OCC), was investigated as an alternate CNF source. OCC is a recycled material that can be obtained at one-tenth the cost of the commonly used bleached softwood Kraft pulp and can be refined to similar levels with nearly one-half of the energy consumption. Additionally, the distinct composition and morphology of OCC-derived CNF provides a more favorable fiber–matrix interface and better reinforcement capabilities of the cellulose nanofibrils in polymer matrices, displaying an over 70% increase in tensile modulus at a loading of 40 wt % with no decrease in tensile strength. When paired with biobased poly(l-lactide) (PLLA), OCC-derived CNF is proven to be an attractive low-cost and low-energy reinforcing agent for sustainable, high performance nanocomposites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The Signature C=C=O Stretch of Propenylketenes and Ketene Clusters [Book Chapter]

A combined experimental and theoretical approach has been used to examine the signature antisymmetric C=C=O stretch of prop-1-enylketene and prop-2-enylketene, as well as a series of ketene multimers and hydrates. Optimization and frequency calculations executed at the B3LYP/6-311G++(d,p) level of theory reveal four conformers of prop-1-enylketene and three conformers of prop-2-enylketene. These ketenes were generated via the pyrolysis of 3-pentenoic anhydride and 4-pentenoic anhydride, respectively, and isolated in low-temperature argon matrices prior to FTIR analysis. The resultant spectra display several bands consistent with B3LYP predictions. A similar computational and experimental survey of ketene multimers and hydrates, generated by the pyrolysis of acetic anhydride, has generated a list of frequencies for the antisymmetric C=C=O stretching mode. Furthermore, the results provide useful benchmarks for identification of propenylketenes in future experiments as well as insight for assigning other substituted ketenes in infrared spectra.

02 PETROLEUM↗
DOE OSTI2025

Functional Design of Peptide Materials Based on Supramolecular Cohesion

Peptide materials offer a broad platform to design biomimetic soft matter, and filamentous networks that emulate those in extracellular matrices and the cytoskeleton are among the important targets. Given the vast sequence space, a combination of computational approaches and readily accessible experimental techniques is required to design peptide materials efficiently. Here, we report here on a strategy that utilizes this combination to predict supramolecular cohesion within filaments of peptide amphiphiles, a property recently linked to supramolecular dynamics and consequently bioactivity. Using established coarse-grained simulations on 10,000 randomly generated peptide sequences, we identified 3500 likely to self-assemble in water into nanoscale filaments. Atomistic simulations of small clusters were used to further analyze this subset of sequences and identify mathematical descriptors that are predictive of intermolecular cohesion, which was the main purpose of this work. We arbitrarily selected a small cohort of these sequences for chemical synthesis and verified their fiber morphology. With further characterization, we were able to link the latent heat associated with fiber to micelle transitions, an indicator of cohesion and potential supramolecular dynamicity within the filaments, to calculated hydrogen bond densities in the simulation clusters. Based on validation from in situ synchrotron X-ray scattering and differential scanning calorimetry, we conclude that the phase transitions can be easily observed by very simple polarized light microscopy experiments. We are encouraged by the methodology explored here as a relatively low-cost and fast way to design potential functions of peptide materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Functionalized Porous Polymer Networks as High-Performance PFAS Adsorbents

Toxic per- and polyfluoroalkyl substances (PFAS) are now found in nearly every water source on the planet. Exposure to these molecules can have negative health consequences, but the low concentration of PFAS relative to other solutes in water makes their removal challenging. Adsorbents offer a promising treatment route, but often exhibit low selectivities and removal capacities, as well as slow kinetics. The performance in these metrics can be improved by chemically optimizing PFAS binding sites and maximizing PFAS-adsorbent interactions. To explore how to achieve this, a porous polymer network solid (PPN-6, also known as PAF-1) was postsynthetically modified with various chemical moieties capable of leveraging unique combinations of electrostatic, hydrogen-bonding, hydrophobic, and fluorophilic interactions with PFAS molecules. Batch adsorption experiments and computational studies revealed that electrostatic and hydrogen-bonding interactions drive short-chain PFAS adsorption, while hydrophobic and fluorophilic interactions improve long-chain PFAS adsorption. In complex water matrices, a combination of electrostatic and fluorophilic interactions led to the greatest total PFAS removal. The best-performing material, functionalized with a fluorinated alkylammonium (PPN-6-FNDMB), selectively adsorbs PFAS with high capacity (up to 4.0 mmol/g) and rapid kinetics (equilibrium reached in <30 s). Furthermore, PPN-6-FNDMB outperforms several commercial adsorbents, achieving near-complete removal of 21 different PFAS from a groundwater sample collected at a US Air Force base. The PFAS could subsequently be desorbed from PPN-6-FNDMB, concentrating them by a factor of over 50 times. The recycled PPN-6-FNDMB could then be reused with minimal losses in long-chain PFAS adsorption capacity over four cycles.

Pezoulas, Ethan R↗
DOE OSTI2022

Molecular-Level Control over Ionic Conduction and Ionic Current Direction by Designing Macrocycle-Based Ionomers

Poor ionic conductivity of the catalyst-binding, submicrometer- thick ionomer layers in energy conversion and storage devices is a huge challenge. However, ionomers are rarely designed keeping in mind the specific issues associated with nanoconfinement. Here, we designed nature-inspired ionomers (calix-2) having hollow, macrocyclic, calix[4]arene-based repeat units with precise, sub-nanometer diameter. In ≤100 nm-thick films, the in-plane proton conductivity of calix-2 was up to 8 times higher than the current benchmark ionomer Nafion at 85% relative humidity (RH), while it was 1-2 orders of magnitude higher than Nafion at 20-25% RH. Confocal laser scanning microscopy and other synthetic techniques allowed us to demonstrate the role of macrocyclic cavities in boosting the proton conductivity. The systematic self-assembly of calix-2 chains into ellipsoids in thin films was evidenced from atomic force microscopy and grazing incidence small-angle X-ray scattering measurements. Moreover, the likelihood of alignment and stacking of macrocyclic units, the presence of one-dimensional water wires across this macrocycle stacks, and thus the formation of long-range proton conduction pathways were suggested by atomistic simulations. We not only did see an unprecedented improvement in thin-film proton conductivity but also saw an improvement in proton conductivity of bulk membranes when calix-2 was added to the Nafion matrices. Nafion-calix-2 composite membranes also took advantage of the asymmetric charge distribution across calix[4]arene repeat units collectively and exhibited voltage-gating behavior. The inclusion of molecular macrocyclic cavities into the ionomer chemical structure can thus emerge as a promising design concept for highly efficient ion-conducting and ion-permselective materials for sustainable energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Actinide Elemental Ratios of Spent Nuclear Fuel Samples by Resonance Ionization Mass Spectrometry

While resonance ionization mass spectrometry (RIMS) has demonstrated utility in measuring isotopic compositions of elements in complex matrices without the need for chemical separation to remove isobaric interferences, it has had limited application in measuring elemental compositions. The ability to determine elemental compositions via an in situ method like RIMS would be an exceptional asset in spent nuclear fuel analysis, where they are important in assessing reactor histories and whose chemical separation presents a radiological hazard. However, quantitative elemental analysis by RIMS requires special considerations because each element is ionized by its own set of lasers tuned to element specific resonant ionization wavelengths. We present the first comprehensive study of measuring elemental ratios by RIMS in spent nuclear fuel. All actinides produced by neutron capture are enhanced significantly radially from the center to the edge of a fuel pellet. This edge effect is not readily accessible by conventional bulk measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Disentangling the Effects of Vapor Pressure Deficit and Soil Water Availability on Canopy Conductance in a Seasonal Tropical Forest During the 2015 El Niño Drought

In land models used in Earth system models, vegetation water stress is heuristically related to soil water matric potential, and root water uptake in soil layers is simply proportional to root density to meet the transpiration demand. The efficiency of roots utilizing deeper soil water under water stress cannot be well represented, but it is of critical importance for transpiration regulation and carbon flux. To improve modeling of tropical forest response to drought, a plant hydrodynamic scheme (HYDRO), adapted from a trait-based model in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), has been implemented in the Energy Exascale Earth System Model (E3SM) Land Model (ELM) to represent the hydraulic dynamics and root water uptake strategy. The adapted model conforms to the big-leaf photosynthesis model in ELM. Vegetation water stress in the model is a function of prognostic leaf water potential and is used to regulate stomatal conductance. Point simulations were performed at two tropical forest sites in the Amazon and Panama. Model sensitivity to the numerical solver, plant hydraulic traits, soil properties, and atmospheric forcing has been evaluated. Our results showed that, even though water stress factors calculated at our study sites using HYDRO are comparable to that simulated by the heuristic water stress model, soil moisture prediction is improved with soil water redistributions through roots. Simulated results using HYDRO is not as sensitive to plant hydraulic traits measured for different tree species as to the soil properties and atmospheric forcing. Simplified numerical solver may cause inaccuracy as to where roots uptake water. This study suggests that plant hydrodynamic representation is critical for improved simulations of soil moisture under water stresses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Opportunistic Short‐Term Water Uptake Dynamics by Subalpine Trees Observed via In Situ Water Isotope Measurements

Abstract Variations in tree water sources are important to understand in semi‐arid ecosystems because climatic shifts towards lower snowpack and increased drought affect water availability in subalpine forests of the western US. Here, we use daily in situ measurements of stable isotopes ( 2 H & 18 O) in soil and tree stem water, soil matric potential and sap flow to study tree water uptake dynamics. We instrumented three soil profiles down to 90 cm, as well as three aspen and engelmann spruce trees near Gothic, Colorado, in the East River watershed. We observed the fate of natural isotopic variations in rainfall, soil, and plants from June to October 2022, and in August 2023 we conducted a 2 H labeled irrigation experiment. Our observations showed that all studied aspen trees compensated for water scarcity in the shallow soil by shifting the dominant water source at 60(±20) cm to ⅔ of uptake from 90 cm within a few days of a dry period. Both species relied on snowmelt stored in the subsoil to sustain transpiration. Intense rainfall caused the plant water uptake to shift partially to top soil layers within 2 days. Spruce transpiration was lower and relied more on snowmelt, because rainfall infiltration was low in the spruce stand due to high canopy interception. Our findings highlight the important role of snowmelt stored in the deep soil layers for subalpine forest drought response and the dominant fate of monsoonal rainfall to become transpiration rather than recharging groundwater and streams in the Upper Colorado River. Plain Language Summary There is a need to understand how trees in mountainous regions respond to dry conditions that lead to water scarcity, because climate projections suggest that such conditions will become more frequent in the future. Here we present a novel data set of measurements of daily stable isotopes of water across soil profiles and in tree stems of aspen and spruce. Our data show that when the upper soil dried out, aspen trees shifted to using water from deeper layers (beneath 60 cm) to keep transpiring. For spruce trees the uptake pattern is less clear, but both types of trees mainly used snowmelt stored in the deeper soil layers to survive the dry summer. After heavy rain, aspen and spruce trees switched to using water from the top 20 cm of soil. However, for spruce, only some rain reached the soil because the dense tree canopy intercepted it, so spruce trees stayed more dependent on snowmelt and used less water overall. This study shows how important deep snowmelt water is for helping forests survive dry periods and suggests that most summer rain is quickly used by trees rather than replenishing streams and groundwater in the headwaters of the Colorado River. Key Points Tree water resources changed within a few days from snow dominated to higher share of rainfall as soils wetted up after a dry period Compensatory plant water uptake by aspen from the deep layer (90 cm), while uptake from soil depths that became drier (60 cm) declined Strong differences between water sources and availability beneath aspen and spruce, respectively

Sprenger, Matthias↗
DOE OSTI2026

Multidimensional Distributional Neural Network Output Demonstrated in Super‐Resolution of Surface Wind Speed

Accurate quantification of uncertainty in neural network predictions remains a central challenge for scientific applications involving high-dimensional, correlated data. While existing methods capture either aleatoric or epistemic uncertainty, few offer closed-form, multidimensional distributions that preserve spatial correlation while remaining computationally tractable. In this work, we present a framework for training neural networks with a multidimensional Gaussian loss, generating a closed-form predictive distribution over outputs informed by non-identically distributed training data. Our approach captures aleatoric uncertainty by iteratively estimating the means and covariance matrices, and is demonstrated on a super-resolution example out-of-training-sample. We leverage a Fourier representation of the covariance matrix to stabilize network training and preserve spatial correlation. We introduce a novel regularization strategy—referred to as information sharing—that interpolates between image-specific and global covariance estimates, enabling convergence of the super-resolution downscaling network trained on image-specific distributional loss functions. This framework allows for efficient sampling, explicit correlation modeling, and extensions to more complex distribution families all without disrupting prediction performance. We demonstrate the method on a surface wind speed downscaling task and discuss its broader applicability to uncertainty-aware prediction in scientific models.

17 WIND ENERGY↗
DOE OSTI2020

Spin-phonon relaxation from a universal ab initio density-matrix approach

Designing new quantum materials with long-lived electron spin states urgently requires a general theoretical formalism and computational technique to reliably predict intrinsic spin relaxation times. We present a new, accurate and universal first-principles methodology based on Lindbladian dynamics of density matrices to calculate spin-phonon relaxation time of solids with arbitrary spin mixing and crystal symmetry. This method describes contributions of Elliott-Yafet and D’yakonov-Perel’ mechanisms to spin relaxation for systems with and without inversion symmetry on an equal footing. We show that intrinsic spin and momentum relaxation times both decrease with increasing temperature; however, for the D’yakonov-Perel’ mechanism, spin relaxation time varies inversely with extrinsic scattering time. We predict large anisotropy of spin lifetime in transition metal dichalcogenides. The excellent agreement with experiments for a broad range of materials underscores the predictive capability of our method for properties critical to quantum information science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗