SEARCH · Search NASA

Results for “CHARGE DISTRIBUTION”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

317 records · Page 12

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Blockage effects in the chemotaxis of diffusiophoretic particles

Transport mechanisms at the micro- and nano-scale play an essential role in regulating intracellular organization. Recent work indicates that directed motion of constituents inside cells can emerge through diffusiophoretic transport, in which colloidal particles move under the influence of chemical gradients. Here, we examine how blockers—passive or actively consuming—reshape those gradients and thereby influence the motion of diffusiophoretic particles. By combining analytical solutions with finite element simulations, we first show that a single blocker can distort a background gradient enough to create or eliminate stagnation points, significantly modifying particle transport. We then introduce a second, explicitly sized blocker at one of these stagnation points and measure how its finite radius alters the diffusiophoretic velocity field for a test particle. Even moderate changes in the second blockers size can cause noticeable shifts in the substrate distribution, highlighting the importance of accounting for explicit particle radii under crowded or consumption-driven conditions. Our findings underscore that subtle geometric variations—such as the radii and positions of two or more blockers—can profoundly affect diffusiophoretic motion, providing a more complete picture of how blocking and crowding phenomena shape intracellular transport.

Song, Zehao [Northwestern Univ., Evanston, IL (Uni↗

DOE OSTI2026

Atomistic Mechanisms of Stress-Dependent Molten Salt Corrosion in NiCr Alloys

Ni-based structural alloys in molten salt environments often experience simultaneous mechanical loading and corrosive attack, yet the mechanisms governing stress-corrosion interactions remain unclear. Prior studies largely emphasize tensile stress, while the role of compressive stress has received limited attention. Here, reactive molecular dynamics simulations are used to investigate the coupled effects of applied strain and corrosion in Ni 0.75 Cr 0.25 exposed to molten FLiNaK at 800 °C. A Σ5(210) grain boundary model is subjected to tensile (+4%) to compressive (−4%) uniaxial strains, and corrosion behavior is evaluated through fluorine adsorption, charge redistribution, and grain boundary evolution. Tensile strain accelerates intergranular corrosion susceptibility by reducing local atomic packing through elastic dilation and increasing excess free volume at the grain boundary, which enhances atomic mobility and salt infiltration. In contrast, compressive strain can suppress corrosion by promoting the formation of a ridge-like surface layer along the grain boundary, limiting salt access to the underlying alloy. These results provide atomistic insight into how stress states influence grain boundary corrosion in molten salts.

36 - MATERIALS SCIENCE↗

DOE OSTI2026

Development of in-situ polymerized intrinsically conductive resin and low-cost carbon pigments offering high conductivity for sensing, EMI shielding and lighting protection

Electrically conductive composites are emerging across diverse industries such as electronic, automotive, aerospace, advanced air mobility, biomedical, infrastructure, defense and security offering static charge dissipation, electromagnetic interference shielding, lighting protection, sensing, dicing, corrosion monitoring, etc. Conductivity enhanced composites provide several advantages compared to conventional metals including weight reduction, corrosion resistance, energy efficient processability, tunable properties and multifunctionality. Polymers are typically insulating in nature and require conducting filler for electron transport. However, dispersion and polymer-filler interphases are critical and often disrupt conducting pathways. Besides, conductive fillers such as graphene, carbon nanotube, MXene, silver nanowire, etc. are expensive, limiting their wide adoption in composite industry. On the other hand, a limited number of intrinsically conductive polymers are available among which polyaniline (PANI) has been widely studied due to its high conductivity, thermal and chemical stability. However, PANI is difficult to process and exhibits weak mechanical properties. In brief, there is a significant demand for electrically conductive polymer formulation with cost-effective conducting fillers that offer processability in scale to expand the market of conductivity enhanced materials.

Kumar, Vipin [Oak Ridge National Laboratory (ORNL)↗

DOE OSTI2026

Microstructural Engineering of Cu-Rich Nanoprecipitate formation in NiCoFeCrCu0.12 High-Entropy Alloy via Severe Plastic Deformation for Enhanced Irradiation Tolerance

This study demonstrates a defect-engineering approach for controlling Cu-rich precipitates in FeNiCrCoCu0.2 high-entropy alloys (Cu-HEAs), delivering a novel pathway for next-generation nuclear reactor materials with superior irradiation resistance. This work establishes that severe plastic deformation (SPD) processing via Shear Assisted Processing and Extrusion (ShAPE) and Friction Stir Layer Deposition (FSLD) creates dense dislocation networks and subgrain boundaries that fundamentally alter precipitation behavior under identical thermal treatments. Atom probe tomography (APT) indicates that SPD produces a metastable, atomically homogeneous solid solution that, upon moderate heat treatment (500°C/10 hour), develops remarkedly stronger Cu clustering than the as-cast counterpart. High-temperature exposure (800°C/100 h) produces near-pure Cu precipitates (~90 at% Cu) with significantly enhanced defect-sink efficacy in SPD-processed alloys: precipitate sizes of 50-60 nm and number densities of 2.7-3.8 × 10¹7 m?³, compared to 89 nm and 0.44 × 10¹7 m?³ in as-cast materials. Collectively, the findings establish defect-mediated precipitation control as a scalable, high-impact route to tailor sink density and distribution in HEAs, enabling microstructures optimized for irradiation tolerance and mechanical robustness in nuclear reactor environments.

Meher, Subhashish↗

DOE OSTI2026

Hierarchical low Pt-loading “core-shell” electrocatalysts for the oxygen reduction reaction in fuel cells

The sluggish kinetics of the oxygen reduction reaction (ORR) hinder cost-effective polymer electrolyte fuel cells (PEFCs), which rely on scarce, expensive platinum-based electrocatalysts (ECs). Here, we present a novel synthesis method for ORR ECs achieving exceptional platinum utilization. The design features a hierarchical “multi-carbon” support comprising carbon nanoparticles interacting with graphene nanoplatelets as the “core”, encapsulated by a porous carbon nitride (CN) “shell”. This configuration promotes strong core/shell interactions and a bimodal active site distribution, consisting of chemically dispersed Pt and Ni single-atom complexes and PtNix alloy nanoclusters embedded in the CN shell. These advantages enable high activity and durability, achieving an ORR activity of 1.6 A mgPt−1 at 0.9 V vs. RHE-an order of magnitude higher than Pt/C (0.17 A mgPt−1). A proof-of-concept PEFC demonstrates a specific power of 12.0 kW gPt−1 at 0.60 V. This approach offers a significant step toward more efficient and sustainable PEFC technologies.

Pagot, Gioele [University of Padova, Italy]↗

DOE OSTI2026

A Chemist’s Guide to Solid-State Qubits: Diamond Color Centers as Embedded Vacancy-Centered Molecules

Diamond point defects or color centers are at the crux of solid-state quantum technology applications, from computing to sensing. Modeling molecular qubits has advanced by leaps and bounds mainly due to the advanced quantum mechanical (QM) tools in the arsenal of quantum chemists for modeling (isolated) molecular systems, which should be easily translatable for analogous systems in the solid state. Here, we simulate a series of diamond defects: a carbon vacancy (V C ) and second row substitutions that are adjacent to a V C or D C V C , with D = B, N, and O, to evaluate their magnetic and optical properties. We applied molecular orbital principles, an embedded cluster method, and a multiconfigurational QM theory to computationally characterize the above-mentioned defects for a multitude of spin, charge, and excited states. Our computational approach delivered high-quality QM insights that compare well with experiments. Furthermore, with this framework, we confirm the spin-triplets B C V C – and O C V C 0 to be analogous to N C V C – , with calculated bright transitions that respectively correspond to UV (3.80 eV) and blue (2.65 eV) light absorption and emission lifetimes (τ) of 2.3 and 5.6 ns, which are higher in energy and more short-lived (and thus brighter) than that for N C V C – : green (2.26 eV), τ = 9.5 ns.

Martirez, John Mark P. [Princeton Plasma Physics L↗

DOE OSTI2026

Active learning using hybrid surrogate tool life modeling for machining process optimization

Here, this paper describes an active learning approach for part-to-part iterative machining process optimization using a hybrid surrogate tool life model. A probabilistic interpolating tool life model is developed by combining the empirical Taylor-type tool life equation and the model fit error. The probabilistic tool life model is then used to calculate the machining cost per part distribution. The optimal machining parameters are selected using an expected improvement in machining cost per part criterion. The method is validated numerically using experimental results; the results show a median convergence error of 2.2% after three tests over 400 simulations. The method is validated experimentally on two industrial applications for Ti-6Al-4V roughing resulting in a cost per part reduction greater than 23% after two tests. The described method is a robust solution for rapid convergence to optimal machining parameters in an industrial production environment.

Active learning↗

DOE OSTI2024

Computational modeling of coupled mechanical damage and electrochemistry in ternary oxide composite electrodes

Performance degradation of ternary layered oxide cathodes largely originates from their loss of structural integrity in cyclic usage. Mechanical damage, such as intergranular fracture of the active particles, is not only a mechanical cleavage process but also interferes with electrochemical kinetics such as infiltration of liquid electrolyte, surface corrosion of the constituent primary particles, and may eventually isolate the primary grains from the electron conducting network. Here, in this work, we develop a computational framework that integrates electrochemistry of a LiNi x Mn y Co 1−x−y O 2 (NMC) composite cathode with mechanical damage of the active particles. To fully examine the intricate chemomechanical behavior of the electrode, we evaluate the effects of the anisotropic material properties, the influence of mechanical potential on Li transport, and the concurrent intergranular fracture and electrolyte penetration along the grain boundaries upon multiple cycles. Electrolyte infiltration benefits capacity retention but aggravates further mechanical damage by corrosion. Structural failure mostly occurs in the first charging due to the anisotropic mechanical strain between the primary grains, while the resulting damage remains stable in the later few cycles. The results are consistent with experimental observations and the integration of electrochemistry and mechanical failure enables a step further understanding of the complex mechanism of battery degradation.

Battery degradation↗

DOE OSTI2025

High-throughput micro-scale bandgap mapping for perovskite-inspired materials with complex composition space

Abstract To realize the full promise of high-throughput experimental workflows, the rate of sample synthesis must be matched by that of characterization. Of growing interest are contactless optical techniques that can rapidly measure material homogeneity and properties. Here, we present a hyperspectral imaging method to measure local optical bandgap distributions within samples, utilizing spatially-resolved reflectance spectra coupled with automated data analysis. We collect approximately one million optical bandgap data across the compositional space of Cs 3 (Bi x Sb 1-x ) 2 (Br y I 1-y ) 9 perovskite-inspired materials. Our results show non-monotonic bandgap variations (i.e., bandgap bowing) along six composition gradient sequences, in addition to identifying samples with multiple bandgaps in statistics. High-throughput transient absorption spectroscopy reveals that within these compositions, the depletion of the ground state carriers to excited states occurred at discrete energy levels with independent carrier dynamics, consistent with the bandgap observation and indicative of phase separation. This work demonstrates the potential for rapid optical measurements to assess material quality and homogeneity in a high-throughput experimental setting, supporting screening and recipe optimization of optoelectronic material candidates with desired carrier dynamics and optical properties.

Science & Technology - Other Topics↗

DOE OSTI2026

Ionic Interdiffusion at Cathode|Solid-Electrolyte Interface: A Machine Learning–Assisted Multiscale Investigation and Mitigation Strategies

Future lithium batteries are expected to use solid electrolytes to achieve higher energy density and fast charge capabilities. However, most solid electrolytes are thermodynamically unstable against layered oxide cathodes. In this study, the stability of LiCoO2 (LCO) cathode with Li10GeP2S12 (LGPS) solid electrolyte is investigated using ab initio molecular dynamics (AIMD) and machine learning molecular dynamics (MLMD). The propensity of ionic interdiffusion, formation of a passivating interphase layer, and corresponding decay in cell performance is addressed using a continuum model. Large-scale MLMD simulations confirm that the LCO|LGPS interface permits interdiffusion of cobalt (Co) and other ionic species, leading to the formation and growth of a resistive interphase and to dramatic capacity fade even in the first cycle. We examine the literature evidence that incorporating a thin layer of LiNb0.5Ta0.5O3 (LNTO) between LCO and LGPS prevents the interdiffusion of ions. Atomistic simulations suggest that substituting lithium (Li) in LNTO with Co is thermodynamically unfavorable, thereby inhibiting ionic interdiffusion. The stable Nb5+/Ta5+ states form a rigid metal-oxide framework, which consequently also prevents the substitution of niobium (Nb) or tantalum (Ta). However, continuum-level analysis suggests that the higher mechanical stiffness of LNTO can lead to interfacial delamination between the LCO and LNTO. This phenomenon reduces the effectiveness of the protective layer. This paper, therefore, highlights the need to develop novel interlayers that balance low ionic interdiffusion with low mechanical stiffness.

Ncube, Musawenkosi K.↗

DOE OSTI2024

Characterizing the γ-Ray Emission from FR0 Radio Galaxies

Abstract FR0 galaxies constitute the most abundant jet population in the local Universe. With their compact jet structure, they are broadband photon emitters and have been proposed as multimessenger sources. Recently, these sources have been detected for the first time inγrays. Using a revised FR0 catalog, we confirm that the FR0 population as a whole areγ-ray emitters, and we also identify two significant sources. For the first time, we find a correlation between the 5 GHz core radio luminosity andγ-ray luminosity in the 1–800 GeV band, having a 4.8σstatistical significance. This is clear evidence that the jet emission mechanism is similar in nature for FR0s and the well-studied canonical FR (FRI and FRII) radio galaxies. Furthermore, we perform broadband spectral energy distribution modeling for the significantly detected sources as well as the subthreshold source population using a one-zone synchrotron self-Compton model. Within the maximum jet power budget, our modeling shows that the detectedγrays from the jet can be explained as inverse Compton photons. To explain the multiwavelength observations for these galaxies, the modeling results stipulate a low bulk Lorentz factor and a jet composition far from equipartition, with the particle energy density dominating over the magnetic field energy density.

Astronomy & Astrophysics↗

DOE OSTI2024

Massive red spiral galaxies in SDSS-IV MaNGA survey

ABSTRACT Massive red spiral galaxies (MRSGs) are supposed to be the possible progenitors of lenticular galaxies (S0s). We select a large sample of MRSGs ($M_*\gt 10^{10.5}\rm {\rm M}_{\odot }$) from Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) DR17 using the g − r colour versus stellar mass diagram, along with control samples of blue spirals and S0s. Our main results are as follows: (1) After comparing the Sérsic index, concentration parameter, asymmetry parameter distribution, size–mass relation, and Σ1 (stellar mass surface density within the central 1 kpc)−mass relation, we find MRSGs are similar to S0s and have more compact and symmetric structures than blue spirals. MRSGs also resemble S0s in Dn4000, metallicity, Mgb/$\rm \left\langle Fe \right\rangle$, and V/σ radial profile. (2) By using MaNGA 2D spectra data, we separate the spatial regions into inner (R < 0.8Re) and outer (0.8 < R < 1.5Re) regions, and detect residual star formation in the outer regions of MRSGs. (3) When we select a sub-sample of MRSGs with NUV − r > 5, we find that they are completely star formation quenched in both inner and outer regions. Compared to optically selected MRSGs, NUV − r selected MRSGs appear to be more concentrated and have more massive dark matter haloes. The similarities between S0s and MRSGs suggest the possible evolutionary trend between MRSGs and S0s.

Astronomy & Astrophysics↗

DOE OSTI2026

Peptoid-Based Nanosheets Exhibiting Broad Antiviral Activity Against Enveloped RNA Viruses

Enveloped RNA viruses, such as Influenza A (H1N1) and Sindbis virus, pose persistent global health threats due to their high mutation rates, efficient transmission, and frequent drug resistance. By mimicking host cell membrane receptors, multivalent virus inhibitors can block viral attachment, making them promising broad-spectrum antiviral agents. However, most of existing antivirals are often limited by strain specificity, short-lived efficacy, and toxicity. Here, we introduce a broad-spectrum antiviral platform based on highly tunable and biocompatible two-dimensional nanomembranes (2DNMs) self-assembled from amphiphilic peptoids, operating via a non-genomic, mutation-insensitive mechanism. By varying peptoid sequence, we design and synthesize over twenty different 2DNMs with various surface charge and high density of viral-attachment ligands (VALs). The self-assembled architecture of these stable 2DNMs provides cooperative noncovalent multivalent binding to virus particles that result in effective inhibition of viral infection. Screening of variants identified three leads that potently suppressed Influenza A (H1N1) and Sindbis virus infection across median tissue culture infectious dose (TCID50), plaque, RT–qPCR, and immunofluorescence assays, while maintaining >90% cell viability. These nanosheets significantly reduced infectious titers, viral RNA replication, and intracellular viral protein expression, indicating inhibition at early stages of viral entry and propagation. The sequence programmability, chemical robustness, and mutation-insensitive antiviral activity distinguish 2DNMs from traditional antivirals and positions them as a versatile materials platform for antiviral coatings, protective barriers, and prophylactic biomedical applications.

Influenza A virus↗

DOE OSTI2026

Preliminary Assessment for the Electric Load Shifting Potential of Integrating Thermal Energy Storage with Heat Pumps in Residential Buildings in Texas of United States

The widespread adoption of electric-driven heat pumps for heating and cooling is expected to significantly increase electric demand. Cooling electric demand will result in an increase in peak hours electric loads, placing additional strain on the grid during peak hours. This challenge, combined with the current rapidly increasing demand from data centers, exacerbates the electric demand duck curve problem. Integrating thermal energy storage (TES) with heat pump can shift electric use for heating and cooling from peak to off-peak hours of the electric grid, which can help flatten the daily electric demand profile of a building. This paper presents a novel design that integrates heat pump with TES (HP-TES), which uses phase change materials (PCM). Heat pump charges TES by melting or freezing PCM during off-peak hours when there is no thermal demand from the building. TES is then discharged (i.e., by freezing or melting PCM) during peak hours to provide a more favorable heat source or heat sink for the heat pump to meet the thermal demand of the building with lower electricity use than conventional air-source heat pumps. Computer simulations were developed to predict the performance of HP-TES applied to a typical single-family house in the US. The building-level simulation results were scaled up to preliminarily assess the aggregated impacts of deploying HP-TES across all single-family houses in Texas of the United States, including reduction of peak demand of the electric grid.

Anees, Fady [ORNL]↗

DOE OSTI2025

A quantitative imaging framework for lithium morphology: Linking deposition uniformity to cycle stability in lithium metal batteries

Characterizing the morphology of lithium (Li) is crucial for developing long-lasting lithium metal batteries. It is well established that more uniform Li deposition correlates with better cell performance. Li morphology is often characterized through qualitative analysis of scanning electron microscopy (SEM) images; however, there are no widely accepted metrics to quantitatively describe deposition uniformity. Here, we propose a framework to quantify uniformity through SEM image analysis via the index of dispersion (ID) metric, which is defined and presented in the context of Li metal batteries. We also explore experimental impacts of sampling protocols onIDmeasurements. Our results demonstrate that theIDmetric is highly sensitive to variations in deposition uniformity, including the coexistence and uniformity of multiple morphologies, uniformity within a single morphology, and particle size distribution uniformity. Furthermore, it is demonstrated that uniformity, as measured by theID, can be related to the average potential of Li||Li symmetric cells over cycling. Higher capacity cycling leads to more pronounced changes in bothIDand average cell potential. Local minima/maxima are found consistently in bothIDand average cell potential immediately before cells short-circuit, which we suggest may indicate a collapse of the microstructure prior to failure. We put forward this framework as a more robust approach to quantify Li deposition uniformity, advancing the development of Li metal batteries that are safer and longer lasting.

Science & Technology - Other Topics↗

DOE OSTI2026

Revealing the Hidden Third Dimension of Point Defects in Two-Dimensional MXenes

Point defects govern many important functional properties of two-dimensional (2D) materials. However, resolving the three-dimensional (3D) arrangement of these defects in multi-layer 2D materials remains a fundamental challenge, hindering rational defect engineering. Here, we overcome this limitation using an artificial intelligence-guided electron microscopy workflow to map the 3D topology and clustering of atomic vacancies in Ti3C2TX MXene. Our approach reconstructs the 3D coordinates of vacancies across hundreds of thousands of lattice sites, generating robust statistical insight into their distribution that can be correlated with specific synthesis pathways. This large-scale data enables us to classify a hierarchy of defect structures-from isolated vacancies to nanopores-revealing their preferred formation and interaction mechanisms, as corroborated by molecular dynamics simulations. This work provides a generalizable framework for understanding and ultimately controlling point defects across large volumes, paving the way for the rational design of defect-engineered functional 2D materials.

2D materials↗

DOE OSTI2023

High‐Entropy Lithium Argyrodite Solid Electrolytes Enabling Stable All‐Solid‐State Batteries

Abstract Superionic solid electrolytes (SEs) are essential for bulk‐type solid‐state battery (SSB) applications. Multicomponent SEs are recently attracting attention for their favorable charge‐transport properties, however a thorough understanding of how configurational entropy (ΔS conf ) affects ionic conductivity is lacking. Here, we successfully synthesized a series of halogen‐rich lithium argyrodites with the general formula Li 5.5 PS 4.5 Cl x Br 1.5‐x (0≤x≤1.5). Using neutron powder diffraction and 31 P magic‐angle spinning nuclear magnetic resonance spectroscopy, the S 2− /Cl − /Br − occupancy on the anion sublattice was quantitatively analyzed. We show that disorder positively affects Li‐ion dynamics, leading to a room‐temperature ionic conductivity of 22.7 mS cm −1 (9.6 mS cm −1 in cold‐pressed state) for Li 5.5 PS 4.5 Cl 0.8 Br 0.7 (ΔS conf =1.98R). To the best of our knowledge, this is the first experimental evidence that configurational entropy of the anion sublattice correlates with ion mobility. Our results indicate the possibility of improving ionic conductivity in ceramic ion conductors by tailoring the degree of compositional complexity. Moreover, the Li 5.5 PS 4.5 Cl 0.8 Br 0.7 SE allowed for stable cycling of single‐crystal LiNi 0.9 Co 0.06 Mn 0.04 O 2 (s‐NCM90) composite cathodes in SSB cells, emphasizing that dual‐substituted lithium argyrodites hold great promise in enabling high‐performance electrochemical energy storage.

Chemistry↗

DOE OSTI2025

Multiscale aperture synthesis imager

Synthetic aperture imaging has enabled breakthrough observations from radar to astronomy. However, optical implementation remains challenging due to stringent wavefield synchronization requirements among multiple receivers. Here we present the multiscale aperture synthesis imager (MASI), which utilizes parallelism to break complex optical challenges into tractable sub-problems. MASI employs a distributed array of coded sensors that operate independently yet coherently to surpass the diffraction limit of single receiver. It combines the propagated wavefields from individual sensors through a computational phase synchronization scheme, eliminating the need for overlapping measurement regions to establish phase coherence. Light diffraction in MASI naturally expands the imaging field, generating phase-contrast visualizations that are substantially larger than sensor dimensions. Without using lenses, MASI resolves sub-micron features at ultralong working distances and reconstructs 3D shapes over centimeter-scale fields. MASI transforms the intractable optical synchronization problem into a computational one, enabling practical deployment of scalable synthetic aperture systems at optical wavelengths.

electrical and electronic engineering↗