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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Turbulent-like flows in quasi two-dimensional dense suspensions of motile colloids

Dense bacterial suspensions exhibit turbulent-like flows at low Reynolds numbers, driven by the activity of the microswimmers. In this study, we develop a model system to examine these dynamics using motile colloids that mimic bacterial locomotion. The colloids are powered by the Quincke instability, which causes them to spontaneously roll in a random-walk pattern when exposed to a square-wave electric field. We experimentally investigate the flow dynamics in dense suspensions of these Quincke random walkers under quasi two-dimensional conditions, where the particle size is comparable to the gap between the electrodes. The results suggest a scaling regime in the energy spectrum ∼k −4 at high wavenumbers, observed consistently across activity levels and particle concentrations. We observe that velocity time correlations decay within a single period of the square-wave field, yet an anti-correlation appears between successive field applications, indicative of a dynamic structural memory of the ensemble.

Luo, Rui [Northwestern Univ., Evanston, IL (United↗
DOE OSTI2026

Heat exposure and maternal stress: evidence from the GRAPHS pregnancy cohort in Ghana

Heat exposure has been linked to psychosocial stress, an established antecedent of perinatal depression; however, evidence on heat-related stress during pregnancy in sub-Saharan Africa remains limited. We analyzed psychosocial stress scores and covariate data from the Ghana Randomized Air Pollution and Health Study, linking daily maximum and minimum shaded wet bulb globe temperature (WBGT) metrics to participants’ stress scores derived from the Crisis in Family Systems-Revised Life Events Questionnaire. We evaluated associations using ordinal logistic regression of pregnancy-average and trimester-average exposures and distributed lag non-linear models (DLNMs) to assess time-varying associations across gestation. Higher average maximum WBGT exposure across pregnancy was associated with increased odds of higher psychosocial stress; each 1 °C increase in maximum WBGT was associated with 64% higher odds of belonging to a higher stress category (OR = 1.64; 95% CI = 1.17–2.31; p = 0.0040). In trimester-average models, higher first-trimester maximum WBGT was also associated with higher stress (OR = 1.44; 95% CI = 1.15–1.81; p = 0.0014). DLNMs suggested that relatively cooler daily maximum WBGT values (25th percentile) were associated with decreased odds of stress in early pregnancy, whereas extreme daily maximum WBGT values (99th percentile) showed a pattern consistent with increased odds of stress in mid-to-late gestation. These findings highlight gestational windows in which heat exposure may influence stress, emphasizing the need for further research into underlying mechanisms and effective interventions to protect maternal mental health in heat-vulnerable settings.

White, Lewis [Columbia University] (ORCID:00090005↗
DOE OSTI2022

Interplay between disorder and collective coherent response: Superradiance and spectral motional narrowing in the time domain

The interplay between static and dynamic disorder and collective optical response in molecular ensembles is an important characteristic of nanoplasmonic and nanophotonic molecular systems. Here we investigate the cooperative superradiant response of a molecular ensemble of quantum emitters under the influence of environmental disorder, including inhomogeneous broadening (as induced by a static random distribution of the molecular transition frequencies) and motional narrowing (as induced by stochastic modulation of these excitation energies). The effect of inhomogeneous broadening is to destroy the coherence of the collective molecular excitation and suppress superradiant emission. However, fast stochastic modulation of the molecular excitation energy can effectively restore the coherence of the quantum emitters and lead to a recovery of superradiant emission, which is an unexpected manifestation of motional narrowing. For a light-scattering process as induced by an off-resonant incident pulse, stochastic modulation leads to inelastic fluorescence emission at the average excitation energy at long times and suggests that dynamic disorder effects can actually lead to collective excitation of the molecular ensemble.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Controlled thermal coefficient product system and method

A controlled thermal coefficient product manufacturing system and method is disclosed. The disclosed product relates to the manufacture of metallic material product (MMP) having a thermal expansion coefficient (TEC) in a predetermined range. The disclosed system and method provides for a first material deformation (FMD) of the MMP that comprises at least some of a first material phase (FMP) wherein the FMP comprises martensite randomly oriented and a first thermal expansion coefficient (FTC). In response to the FMD at least some of the FMP is oriented in at least one predetermined orientation. Subsequent to deformation, the MMP comprises a second thermal expansion coefficient (STC) that is within a predetermined range and wherein the thermal expansion of the MMP is in at least one predetermined direction. The MMP may be comprised of a second material phase (SMP) that may or may not transform to the FMP in response to the FMD.

Monroe, James Alan↗
DOE OSTI2023

Controlled thermal coefficient product system and method

A controlled thermal coefficient product manufacturing system and method is disclosed. The disclosed product relates to the manufacture of metallic material product (MMP) having a thermal expansion coefficient (TEC) in a predetermined range. The disclosed system and method provides for a first material deformation (FMD) of the MMP that comprises at least some of a first material phase (FMP) wherein the FMP comprises martensite randomly oriented and a first thermal expansion coefficient (FTC). In response to the FMD at least some of the FMP is oriented in at least one predetermined orientation. Subsequent to deformation, the MMP comprises a second thermal expansion coefficient (STC) that is within a predetermined range and wherein the thermal expansion of the MMP is in at least one predetermined direction. The MMP may be comprised of a second material phase (SMP) that may or may not transform to the FMP in response to the FMD.

Monroe, James Alan↗
DOE OSTI2024

Systems and methods for manufacturing nano-scale materials

Methods and systems for high-speed production of nanoparticles with very high product yields are described. Systems utilize concentric micro-scale capillaries arranged to define nanoparticle formation regions that lie along predetermined length(s) of the capillaries. Flow through the formation regions can be laminar during a formation protocol. The system can include on-line analytical tools for real time characterization of products or intermediates. Systems include an additive manufacturing-type deposition at the terminus of the formation section. The deposition area includes a print head and a print bed and provides for random or patterned deposition of nanoparticles. The print head and/or the print bed can be capable of motion in one or more degrees of freedom relative to one another.

Source record↗
DOE OSTI2021

Responding To A Downed Unmanned Aircraft System (UAS) Platform

A drone may be forced down as part of a kinetic Counter-UAS action or as a spoof signal with a command to land immediately. A drone could also be incidentally discovered by an employee or by a random patrol. In each case, the platform should be considered a suspicious package until it can be determined to be nonhazardous by qualified personnel.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

Holographic Kolmogorov-Sinai entropy and the quantum Lyapunov spectrum

In classical chaotic systems the entropy, averaged over initial phase space distributions, follows a universal behavior. While approaching thermal equilibrium it passes through a stage where it grows linearly, while the growth rate, the Kolmogorov-Sinai entropy (rate), is given by the sum over all positive Lyapunov exponents. A natural question is whether a similar relation is valid for quantum systems. We argue that the Maldacena-Shenker-Stanford bound on quantum Lyapunov exponents implies that the upper bound on the growth rate of the entropy, averaged over states in Hilbert space that evolve towards a thermal state with temperature T, should be given by πT times the thermal state’s von Neumann entropy. Strongly coupled, large N theories with black hole duals should saturate the bound. To test this we study a large number of isotropization processes of random, spatially homogeneous, far from equilibrium initial states in large N, $\mathcal{N}$ = 4 Super Yang Mills theory at strong coupling and compute the ensemble averaged growth rate of the dual black hole’s apparent horizon area. We find both an analogous behavior as in classical chaotic systems and numerical evidence that the conjectured bound on averaged entropy growth is saturated granted that the Lyapunov exponents are degenerate and given by λ i = ±2πT. This fits to the behavior of classical systems with plus/minus symmetric Lyapunov spectra, a symmetry which implies the validity of Liouville’s theorem.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Spatiotemporal features of traffic help reduce automatic accident detection time

Quick and reliable automatic detection of traffic accidents is of paramount importance to save human lives in transportation systems. However, automatically detecting when accidents occur has proven challenging, and minimizing the time to detect accidents (TTDA) by using traditional features in machine learning (ML) classifiers has plateaued. We hypothesize that accidents affect traffic farther from the accident location than previously reported. Therefore, leveraging traffic signatures from neighboring sensors that are adjacent to accidents should help improve their detection. We confirm this hypothesis by using verified ground-truth accident data, traffic data from radar detection system sensors, and light and weather conditions and show that we can minimize the TTDA while maximizing classification performance by considering spatiotemporal features of traffic. Specifically, we compare the performance of different ML classifiers (i.e, logistic regression, random forest, and XGBoost) when controlling for different numbers of neighboring sensors and TTDA horizons. We use data from interstates 75 and 24 in the metropolitan area that surrounds Chattanooga, TN. Our results show that the XGBoost classifier produces the best results by detecting accidents as quickly as 1.0 min after their occurrence with an area under the receiver operating characteristic curve of up to 83% and an average precision of up to 49%. We describe limitations, open challenges, and how the proposed framework can be used for quicker operational accident detection.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Recent Advances in Nonclassical Crystallization: Fundamentals, Applications, and Challenges

We report crystals are ubiquitous and play an important role in our daily life. Recent studies on properties and formation of crystals have proven the attachment of particle ranging from ion pairs to well-crystallized nanocrystal is one of the most important ways for crystallization. Compared with the monomer-by-monomer (i.e., atoms, ions, or molecules) addition described in longstanding classical theories, so-called nonclassical crystallization pathways are more complex as the non-specific interaction of variation in system free energy and reaction kinetics. In view of the detailed insights into nonclassical crystallization pathways has broadened the scope of research across various disciplines such as geological events, biomineralization mechanisms, environmental remediation, and the development of functional materials, this paper reviews the current state of the art in nonclassical nucleation (the prenucleation clusters pathway, aggregation pathway, etc.) and growth pathways (oriented attachment and random attachment) based on several spotlights. In addition, the observed specific phenomena on crystallization in the last 10 years as well as recent advancements and achievements made on the synthesis of mesocrystals are also elucidated. With implications and perspectives of nonclassical crystallization researches proposed in this paper, this review aims to summarize research advancement regarding crystallizing systems. Emphasis will be placed on novel insights into nonclassical crystallization of materials, which are expected to provide completely new perspectives on the underlying crystallization mechanisms.

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

Hexagonal Lattices of HIV Capsid Proteins Explored by Simulations Based on a Thermodynamically Consistent Model

HIV capsid proteins (CAs) may self-assemble into a variety of shapes under in vivo and in vitro conditions. Here, we employed simulations based on a residue-level coarse-grained (CG) model with full conformational flexibility to investigate hexagonal lattices, which are the underlying structural pattern for CA aggregations. Facilitated by enhanced sampling simulations to rigorously calculate CA dimerization and polymerization affinities, we calibrated our model to reproduce the experimentally measured affinities. Here using the calibrated model, we performed unbiased simulations on several large systems consisting of 1512 CA subunits, allowing reversible binding and unbinding of the CAs in a thermodynamically consistent manner. In one simulation, a preassembled hexagonal CA sheet developed spontaneous curvatures reminiscent of those observed in experiments, and the edges of the sheet exhibited local curvatures larger than those of the interior. In other simulations starting with randomly distributed CAs at different concentrations, existing CA assemblies grew by binding free capsomeres to the edges and by merging with other assemblies. At high CA concentrations, rapid establishment of predominant aggregates was followed by much slower adjustments toward more regular hexagonal lattices, with increasing numbers of intact CA hexamers and pentamers being formed. Our approach of adapting a general CG model to specific systems by using experimental binding data represents a practical and effective strategy for simulating and elucidating intricate protein aggregations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Benchmarking structural evolution methods for training of machine learned interatomic potentials

When creating training data for machine-learned interatomic potentials (MLIPs), it is common to create initial structures and evolve them using molecular dynamics (MD) to sample a larger configuration space. Here, we benchmark two other modalities of evolving structures, contour exploration (CE) and dimer-method (DM) searches against MD for their ability to produce diverse and robust density functional theory training data sets for MLIPs. We also discuss the generation of initial structures which are either from known structures or from random structures in detail to further formalize the structure-sourcing processes in the future. The polymorph-rich zirconium-oxygen composition space is used as a rigorous benchmark system for comparing the performance of MLIPs trained on structures generated from these structural evolution methods. Using Behler–Parrinello neural networks as our MLIP models, we find that CE and the DM searches are generally superior to MD in terms of spatial descriptor diversity and statistical accuracy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Polaritons and excitons: Hamiltonian design for enhanced coherence

The primary questions motivating this report are: Are there ways to increase coherence and delocalization of excitation among many molecules at moderate electronic coupling strength? Coherent delocalization of excitation in disordered molecular systems is studied using numerical calculations. The results are relevant to molecular excitons, polaritons, and make connections to classical phase oscillator synchronization. In particular, it is hypothesized that it is not only the magnitude of electronic coupling relative to the standard deviation of energetic disorder that decides the limits of coherence, but that the structure of the Hamiltonian—connections between sites (or molecules) made by electronic coupling—is a significant design parameter. Inspired by synchronization phenomena in analogous systems of phase oscillators, some properties of graphs that define the structure of different Hamiltonian matrices are explored. The report focuses on eigenvalues and ensemble density matrices of various structured, random matrices. Some reasons for the special delocalization properties and robustness of polaritons in the single-excitation subspace (the star graph) are discussed. The key result of this report is that, for some classes of Hamiltonian matrix structure, coherent delocalization is not easily defeated by energy disorder, even when the electronic coupling is small compared to disorder.

Science & Technology - Other Topics↗
DOE OSTI2024

Electronic structure, magnetic correlations, and superconducting pairing in the reduced Ruddlesden-Popper bilayer La 3 Ni 2 O 6 under pressure: Different role of d 3 z 2 - r 2 orbital compared with La 3 Ni 2 O 7

The recent discovery of superconductivity in bilayer La 3 Ni 2 O 7 (327-LNO) under pressure stimulated much interest in layered nickelates. However, superconductivity was not found in another bilayer nickelate system, La 3 Ni 2 O 6 (326-LNO), even under pressure. To understand the similarities and differences between 326-LNO and 327-LNO, using density functional theory and the random phase approximation (RPA), we systematically investigate 326-LNO under pressure. The large crystal-field splitting between the e g orbitals caused by the missing apical oxygen moves the d 3z 2 -r 2 orbital farther away from the Fermi level, implying that the d 3z 2 -r 2 orbital plays a less important role in 326-LNO than in 327-LNO. This also results in a smaller bandwidth for the d x 2 -y 2 orbital and a reduced energy gap for the bonding-antibonding splitting of the d 3z 2 -r 2 orbital in 326-LNO, as compared to 327-LNO. Moreover, the in-plane hybridization between the d x 2 -y 2 and d 3z 2 -r 2 orbitals is found to be small in 326-LNO, while it is much stronger in 327-LNO. Furthermore, the low-spin ferromagnetic state is found to be the likely ground state in 326-LNO under high pressure. The weak interlayer coupling suggests that s ± -wave pairing is unlikely in 326-LNO. The robust in-plane ferromagnetic coupling also suggests that d-wave superconductivity, which is usually caused by antiferromagnetic fluctuations of the d x 2 -y 2 orbital, is also unlikely in 326-LNO. These conclusions are supported by our many-body RPA calculations of the pairing behavior. Additionally, contrasting with the cuprates, for the bilayer cuprate HgBa 2 CaCu 2 O 6 , we find a strong self-doping effect of the d x 2 -y 2 orbital under pressure, with the charge of Cu being reduced by approximately 0.13 electrons from 0 GPa to 25 GPa. In contrast, we do not observe such a change in the electronic density in 326-LNO under pressure, establishing another important difference between the nickelates and the cuprates.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Copula based Damage Detection for Structural Health Monitoring

This project utilizes copulas for damage detection in a Structural Health Monitoring (SHM) application. A copula-based system was chosen for the benefit of multivariate joint distribution with a goal to detect damage based on how the system as a whole reacts rather than one or two sensors by themselves. Copulas are commonly used in the field of finance for risk modeling based on two or more random inputs. A few applications in the field of SHM and Non-Destructive Evaluation (NDE) have been researched mostly on risk or reliability of the structure. The goal of this project is to determine if a copula-based approach can be used for damage detection. An unsupervised learning method was desired to reduce the dimensionality, minimal training, and be a faster evaluation method than other unsupervised methods. If a copula method can be used to detect damage what additional information on the damage can be interpreted. The remainder of this report will go over the background needed, SHM methodology, SHM applications, conclusions, and future developments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Dataset for SIAM MPI23 Project "Model inversion for complex physical systems using low-dimensional surrogates"

Training and testing data for the SIAM MPI23 workshop "Model inversion for complex physical systems using low-dimensional surrogates". The data consists of ensembles of input and output pairs corresponding to queries of a 2D saturated groundwater flow model. The inputs consist of random vectors which map to discretized model parameter fields via a Kosambi-Karhunen-Loève expansion. Output corresponds to discretized pressure fields.

basis adaptation, conditional Karhunen-Loève expan↗
DOE OSTI2023

ABF DFO with Technology Holding, Inc.

This Agile BioFoundry Directed Funding Opportunity project with Technology Holding and partners focuses on the development of both a strain of Pseudomonas putida KT2440 and a corresponding bioprocess to convert cellulosic sugars to beta-ketoadipic acid, which can be used in performance nylons and polyesters. Our approach follows the Design-Build-Test-Learn cycle wherein we have transferred learnings from muconic acid production in P. putida to develop a glucose and xylose-utilizing beta-ketoadipic acid production strain. This strain achieves 65 g/L of beta-ketoadipic acid at 0.7 g/L/hr and a C-mol yield of 0.40. We are currently on-boarding arabinose utilization as well. To identify non-intuitive strain modifications as well, we are deploying a beta-ketoadipic acid biosensor and building randomly barcoded transposon insertion sequencing (RB-TnSeq) libraries and gene over-expression libraries in beta-ketoadipic acid production strains. Moreover, we are using global metabolomics and other systems biology tools to identify off-target pathways. Lastly, we are scaling up beta-ketoadipic acid production to kg-scale production for Technology Holding to evaluate in performance polymers with their partners.

beta-ketoadipic acid↗