Search NASA⌕ Search

SEARCH · Search NASA

Results for “Dynamic Stability”

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.

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

At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Dynamic molecular architecture of the synaptonemal complex

During meiosis, pairing between homologous chromosomes is stabilized by the assembly of the synaptonemal complex (SC). The SC ensures the formation of crossovers between homologous chromosomes and regulates their distribution. However, how the SC regulates crossover formation remains elusive. We isolated an unusual mutation in Caenorhabditis elegans that disrupts crossover interference but not SC assembly. This mutation alters the unique C terminal domain of an essential SC protein, SYP-4, a likely ortholog of the vertebrate SC protein SIX6OS1. We use three-dimensional stochastic optical reconstruction microscopy (3D-STORM) to interrogate the molecular architecture of the SC from wild-type and mutant C. elegans animals. Using a probabilistic mapping approach to analyze super-resolution image data, we detect changes in the organization of the synaptonemal complex in wild-type animals that coincide with crossover designation. We also found that our syp-4 mutant perturbs SC architecture. Our findings add to growing evidence that the SC is an active material whose molecular organization contributes to chromosome-wide crossover regulation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Accurate and efficient interatomic potentials are essential for molecular dynamics (MD) simulations of radiation damage, gas diffusion, and phase stability in complex ceramics such as LiAlO 2 , especially under extreme conditions relevant to tritium production. Here, we evaluate the performance of six machine-learned interatomic potentials (MLIPs), moment tensor potential (MTP), Gaussian approximation potential, deep potential (DeePMD), atomic cluster expansion (ACE), message-passing ACE (multilayer atomic cluster expansion (MACE) pretrained) and MACE (trained from-scratch), all trained on the same density functional theory dataset with inclusion of tritium. The MLIPs are benchmarked against traditional Buckingham and ReaxFF potentials in terms of energy accuracy, density predictions, thermal equilibration behavior, threshold displacement energy (E d ), tritium diffusivity, and computational cost. Among the models, MTP shows the best overall balance between efficiency and accuracy, with low force and energy errors and realistic E d values for Li and Al. The ACE and MACE (pretrained and trained from scratch) models exhibit high E d (>200 eV) and unphysical pair interactions. DeePMD underestimates Ed due to overly repulsive behavior even at equilibrium distances. All models over-estimate tritium diffusion but the pretrained MACE model behaves well during tritium-diffusion simulations up to 500 K, maintaining diffusivities in the physically consistent 10 −11 m 2 /s range. Finally, we quantify the computational cost of each potential in large-scale atomic/molecular massively parallel simulator, finding that only MTP is more efficient than traditional empirical potentials, while others are significantly more expensive. These findings explain the trade-offs between accuracy and computational cost in MLIP development and provide essential guidance for use in high-throughput radiation damage and gas diffusion simulations in nuclear ceramics.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Vapor-phase self-assembly for generating thermally stable single-atom catalysts

Preparation of thermally stable metal single-atom catalysts (SACs) is a challenge in heterogeneous catalysis, especially on conventional supports that provide a weak metal-support interaction. In this work, we report that a modified support MgAl 2 O 4 can stabilize Pt single atoms by a mechanism of vapor-phase self-assembly in a high-temperature treatment (800°C, air). The experimental results on the formation mechanism and the structure are validated by DFT and ab initio molecular dynamics simulations. We infer that stable triangular K 3 O 3 structures help stabilize Pt single atoms at high temperatures in oxidizing conditions, exhibiting excellent reactivity for methane oxidation. The obtained Pt/K/MgAl 2 O 4 SAC presents excellent stability in methane oxidation after steam treatment at elevated temperatures, whereas the Pt/MgAl 2 O 4 nanocatalyst suffers from rapid deactivation due to Pt nanoparticle growth. Now this work paves the way for preparing thermally stable and highly active SACs using conventional high-surface-area supports, despite the weak metal-support interaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Effects of sodium and calcium chloride ionic stresses on model yeast membranes revealed by molecular dynamics simulation

As efforts to move a renewable economy grow, it will be necessary to make use of microbial conversion strategies for the production of novel materials or the upgrading of waste to high-value products. One critical technical challenge currently limiting waste upgrading remains the difficulty in obtaining single-pot conversion techniques where physical, chemical, and biological conversion are performed in a single step. To overcome this challenge, a detailed understanding of how different stresses impact microbial membrane stability will be necessary. In this work, using all-atom molecular dynamics simulations, we examine the impacts of moderate concentrations of NaCl and CaCl 2 on a model yeast plasma membrane. Weak, though statistically significant, changes in membrane morphology and dynamics functions are observed that are consistent with swelling and stiffening. Additionally, an examination of the ion-lipid contacts and the behavior of water at the water-membrane interface suggests that the impacts of these common salts may, in part, be mediated through changes to water-membrane hydrogen-bonding and hydration water dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Multiplexable intrinsic Fabry-Pérot interferometers inscribed by femtosecond laser for vibration measurement in high temperature environments

This article reports fabrication technique and demodulation algorithm developments to use multiplexable intrinsic Fabry-Pérot interferometer (IFPI) fiber sensor array for distributed vibration measurements at high temperatures. Using femtosecond laser direct writing scheme, IFPI array were fabricated through laser-induced Type II scattering points in single mode fiber cores. Reflection spectra of IFPI array were demodulated in real-time using modified Bunemen frequency analysis. The demodulation algorithm, which was implemented using a photodetector-array spectrometer, achieves 64-nε dynamic strain resolution at 1-kHz spectral acquisition rate and 2-kHz maximum vibration bandwidth. Performance and stabilities of IFPI sensor array were characterized from room temperatures to 800 °C. The static strain resolution was 0.6 με and the minimum detectable dynamic strain amplitude was 23 nε/√Hz at 800 °C. The multiplex performance was also tested by measuring dynamic strain in time domain through six IFPI sensor array fabricated in one fiber. This paper presents an integrated and low-cost sensing solution to perform distributed vibration measurements in harsh environments.

42 ENGINEERING↗
DOE OSTI2024

A New Simple-to-Configure Self-Perturbing Multivariable Extremum-Seeking Controller

This paper presents a new stochastic relay-based extremum-seeking controller (ESC) for multi-input-single-output (MISO) systems. The algorithm was developed with the goal of simplifying configuration to enable easier deployment to real-world problems. A solution is developed first for a static map and then adapted for a general class of dynamic systems. The number of configurable parameters is one per input channel for the static case and only one additional parameter is needed for the dynamic version. The problem of gradient identifiability is solved via the use of stochastic relay gains and a simple stability proof for the static case is presented. Simulation tests demonstrate the performance of the strategy for optimizing both static and dynamic systems.

Salsbury, Timothy [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2022

Chain Redistribution Stabilizes Coexistence Phases in Block Copolymer Blends

The nanoscale morphologies of block copolymer (BCP) thin films are determined by chain architecture. Experimental studies of thin film blends of different BCP chain types have demonstrated that blending can stabilize new motifs, such as coexistence phases. Here, we deploy coarsegrained molecular dynamics (MD) simulations in order to better understand the self-assembly behavior of BCP blend thin films. Here, we consider blends of lamella- and cylinder-forming BCP chains, studying their morphological makeup, the chain distribution within the morphology, and the underlying polymer chain conformations. Our simulations show that there are local concentration deviations at the scale of the morphological objects that dictate the local structure, and that BCP chains redistribute within the morphology so as to stabilize the structure. Underlying these effects are measurable distortions in the BCP chain conformations. The conformational freedom afforded by BCP blending stabilizes defects and allows coexistence phases to appear, while also leading to kinetic trapping effects. These results highlight the power of blending in designing the morphology that forms.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Effect of sink strength on coherency loss of precipitates in dilute Cu-base alloys during in situ ion irradiation

In situ irradiations with 1 MeV Kr ions at 50~613 K up to a fluence of 6.25 × 10 14 ions/cm 2 (~1.25 displacements per atom, dpa) have been performed on pre-aged dilute Cu-0.9%Co, Cu-0.9%Fe and Cu-0.8%Cr alloys containing uniform matrix dispersions of coherent precipitates in order to study the effects of initial precipitate sink strength, damage dose and irradiation temperature on radiation-induced coherency loss of precipitates. Coherent precipitates with different point defect sink strengths (2πNd, where N and d are the precipitate density and diameter) were used in this work to examine potential differences in atomic relaxation during absorption of point defects. In all cases, irradiation to low doses (<~1 dpa) was very effective at inducing loss of precipitate coherency. At low sink strengths (~10 13 m -2 ), loss of precipitate coherency could be induced for doses ~0.01 dpa. This suggests there might be an efficient preferential medium-range strain-induced bias for absorption of interstitial defects due to tensile strains emanating from the undersized precipitates, which induces relatively rapid loss of coherency at low precipitate sink strengths. High precipitate sink strength (~10 14 m -2 ) conditions were relatively resistant to the radiation-induced loss of coherency (requiring higher doses approaching ~1 dpa) and this might be due to nearly equal numbers of interstitial and vacancy defects arriving at the precipitate interface for such high sink strength conditions. The precipitate coherency loss was observed to have a weak dependence on irradiation temperature. Molecular dynamics simulations confirm a strong effect of precipitate sink strength on the probability of interstitial absorption at precipitates.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Dynamic security assessment of systems powered only by grid-forming power plants with uncertain dispatch using polynomial vectors

A modern challenge in power engineering is to perform the dynamic security assessment (DSA) of grids that are 100% powered by inverter-based resources (IBRs). Addressing this challenge is difficult because: (i) the dispatch of IBRs can be uncertain as a result of the variability of renewable resources and (ii) they have hard current control limits that cannot be neglected, contrasting synchronous machines. To address this problem, this paper sets forth a framework to conduct DSA of bulk power systems that are 100% powered by grid-forming IBRs. Furthermore, the framework considers that IBR operational conditions are unknown but bounded by a zonotope which is also expressed as a polynomial vector for uncertainty propagation via Dormand–Prince integration. The framework is applied to modified versions of the WSCC 9-bus and IEEE 39-bus grids.

14 SOLAR ENERGY↗
DOE OSTI2025

Electronic Structure and Safety Insights into Prussian Blue Analog Cathode Behavior at Elevated Temperatures in Sodium-Ion Batteries

Prussian blue analogs (PBAs) represent promising cathode materials for sodium-ion batteries (SIBs) due to their high theoretical capacity, open framework structure, and use of earth-abundant elements. However, the high-temperature structural evolution, water content effects, and thermal safety of PBAs, particularly in charged states, remain poorly understood, hindering their practical deployment. Here, we investigate Na 2 Fe[Fe(CN) 6 ]·2H 2 O using thermogravimetric analysis (TGA), ex situ and in situ temperature-dependent X-ray absorption spectroscopy (XAS), and accelerated rate calorimetry (ARC). TGA and ex situ XAS confirm water loss between 150 and 200 °C, resulting in Fe 2+ oxidation, enhanced local symmetry, and uniform redox behavior that improves electrochemical performance. In situ XAS reveals irreversible structural changes above 240 °C, including ligand loss, Fe site distortion, and increased disorder, while ARC on charged electrodes shows minimal self-heating rates (<0.1 °C/min) up to 300 °C, indicating exceptional thermal stability without lattice oxygen release. These insights elucidate PBA thermal dynamics, demonstrating improved electrochemical performance of water-deficient PBAs and informing future material design and safety assessment for SIB applications.

batteries↗
DOE OSTI2021

Revealing Au13 as Elementary Clusters During the Early Formation of Au Nanocrystals

Understanding the formation mechanism of nanocrystals in solution is very fundamental to the development of materials science. For a metal nanocrystal, the cluster mediated formation mechanism is still poorly understood. Particularly, identifying what types of clusters are dominant and how they evolve into a nanocrystal in the early nucleation stage remains a great challenge. Here, using liquid-cell transmission electron microscopy, we directly observe the formation of ultra-small Au clusters (~0.84 nm) in the presence of PAA-Na. These clusters, which correspond to the size of Au13 cluster, coalesce to form nanocrystals. Our molecular dynamics simulations suggest Au13 in an aqueous environment have higher stability when compared to other cluster sizes and provide atomistic details of growth by cluster coalescence. Collectively, our demonstration of Au13 as the dominant species with elaboration of their coalescence kinetics sheds light on nonclassical nanocrystal formation mechanisms and offers useful guidelines for designing innovative pathways for synthesis of nanomaterials.

Au13 clusters, cluster coalescence, liquid-cell TE↗
DOE OSTI2022

Asymmetrically Stratified Beaufort Gyre: Mean State and Response to Decadal Forcing

Abstract Recent progress in understanding Beaufort Gyre (BG) dynamics reveals an important role of ice‐ocean stress in stabilizing BG freshwater content (FWC) over seasonal to interannual timescales. But how the BG's stratification and FWC respond to surface forcing over decadal timescales has not been fully explored. Using a global ocean‐sea ice model, we partition the BG into upper, middle (halocline), and lower (thermocline) layers and perform a volume budget analysis over 1948–2017. We find that the BG's asymmetric geometry (with steep and tight isohalines over continental slopes relative to the deep basin) is key in determining the mean volume transport balance. We further find that a net Ekman suction during 1983–1995 causes the upper and middle layers to deflate isopycnally, while an enhanced Ekman pumping during 1996–2017 causes these layers to inflate both isopycnally and diapycnally, the latter via anomalous flux from the upper to the middle layer.

Zhang, Jiaxu↗
DOE OSTI2024

Bayesian blacksmithing: discovering thermomechanical properties and deformation mechanisms in high-entropy refractory alloys

Finding alloys with specific design properties is challenging due to the large number of possible compositions and the complex interactions between elements. This study introduces a multi-objective Bayesian optimization approach guiding molecular dynamics simulations for discovering high-performance refractory alloys with both targeted intrinsic static thermomechanical properties and also deformation mechanisms occurring during dynamic loading. The objective functions are aiming for excellent thermomechanical stability via a high bulk modulus, a low thermal expansion, a high heat capacity, and for a resilient deformation mechanism maximizing the retention of the BCC phase after shock loading. Contrasting two optimization procedures, we show that the Pareto-optimal solutions are confined to a small performance space when the property objectives display a cooperative relationship. Conversely, the Pareto front is much broader in the performance space when these properties have antagonistic relationships. Density functional theory simulations validate these findings and unveil underlying atomic-bond changes driving property improvements.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Evidence of shock-compressed stishovite above 300 GPa

SiO 2 is one of the most fundamental constituents in planetary bodies, being an essential building block of major mineral phases in the crust and mantle of terrestrial planets (1–10 M E ). Silica at depths greater than 300 km may be present in the form of the rutile-type, high pressure polymorph stishovite (P4 2 /mnm) and its thermodynamic stability is of great interest for understanding the seismic and dynamic structure of planetary interiors. Previous studies on stishovite via static and dynamic (shock) compression techniques are contradictory and the observed differences in the lattice-level response is still not clearly understood. Here, laser-induced shock compression experiments at the LCLS- and SACLA XFEL light-sources elucidate the high-pressure behavior of stishovite on the lattice-level under in situ conditions on the Hugoniot to pressures above 300 GPa. We find stishovite is still (meta-)stable at these conditions, and does not undergo any phase transitions. This contradicts static experiments showing structural transformations to the CaCl 2 , α-PbO 2 and pyrite-type structures. However, rate-limited kinetic hindrance may explain our observations. These results are important to our understanding into the validity of EOS data from nanosecond experiments for geophysical applications.

58 GEOSCIENCES↗
DOE OSTI2021

Hierarchical excitations from correlated spin tetrahedra on the breathing pyrochlore lattice

The hierarchy of the coupling strengths in a physical system often engenders an effective model at low energies where the decoupled high-energy modes are integrated out. Here, using neutron scattering, we show that the spin excitations in the breathing pyrochlore lattice compound CuInCr 4 S 8 are hierarchical and can be approximated by an effective model of correlated tetrahedra at low energies. At higher energies, intratetrahedron excitations together with strong magnon-phonon couplings are observed, which suggests the possible role of the lattice degree of freedom in stabilizing the spin tetrahedra. Finally, our work illustrates the spin dynamics in CuInCr 4 S 8 and demonstrates a general effective-cluster approach to understand the dynamics on the breathing-type lattices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Transient Simulations with a Large Penetration of Converter-Interfaced Generation: Scientific Computing Challenges and Opportunities

Current trends in energy systems point to renewable energy sources (RESs) and battery energy storage systems (BESSs) becoming prevalent in power system operations. As of writing this article, the United States has more than 37 GW of utility-scale solar capacity and an additional 112 GW under development. With the rapidly declining capital costs of many of these technologies, we can expect significant deployments in the coming years.

analytical models↗
DOE OSTI2020

Using Machine Learning Tools to Predict Compressor Stall

Clean energy has become an increasingly important consideration in today’s power systems. As the push for clean energy continues, many coal-fired power plants are being decommissioned in favor of renewable power sources such as wind and solar. However, the intermittent nature of renewables means that dynamic load following traditional power systems is crucial to grid stability. With high flexibility and fast response at a wide range of operating conditions, gas turbine systems are poised to become the main load following component in the power grid. Yet, rapid changes in load can lead to fluid flow instabilities in gas turbine power systems. These instabilities often lead to compressor surge and stall, which are some of the most critical problems facing the safe and efficient operation of compressors in turbomachinery today. Although the topic of compressor surge and stall has been extensively researched, no methods for early prediction have been proven effective. This study explores the utilization of machine learning tools to predict compressor stall. The long short-term memory (LSTM) model, a form of recurrent neural network (RNN), was trained using real compressor stall datasets from a 100 kW recuperated gas turbine power system designed for hybrid configuration. Two variations of the LSTM model, classification and regression, were tested to determine optimal performance. The regression scheme was determined to be the most accurate approach, and a tool for predicting compressor stall was developed using this configuration. Overall, results show that the tool is capable of predicting stalls 5–20 ms before they occur. With a high-speed controller capable of 5 ms time-steps, mitigating action could be taken to prevent compressor stall before it occurs.

42 ENGINEERING↗
DOE OSTI2022

MSASGCN : Multi-Head Self-Attention Spatiotemporal Graph Convolutional Network for Traffic Flow Forecasting

Traffic flow forecasting is an essential task of an intelligent transportation system (ITS), closely related to intelligent transportation management and resource scheduling. Dynamic spatial-temporal dependencies in traffic data make traffic flow forecasting to be a challenging task. Most existing research cannot model dynamic spatial and temporal correlations to achieve well-forecasting performance. The multi-head self-attention mechanism is a valuable method to capture dynamic spatial-temporal correlations, and combining it with graph convolutional networks is a promising solution. Therefore, we propose a multi-head self-attention spatiotemporal graph convolutional network (MSASGCN) model. It can effectively capture local correlations and potential global correlations of spatial structures, can handle dynamic evolution of the road network, and, in the time dimension, can effectively capture dynamic temporal correlations. Experiments on two real datasets verify the stability of our proposed model, obtaining a better prediction performance than the baseline algorithms. The correlation metrics get significantly reduced compared with traditional time series prediction methods and deep learning methods without using graph neural networks, according to MAE and RMSE results. Compared with advanced traffic flow forecasting methods, our model also has a performance improvement and a more stable prediction performance. We also discuss some problems and challenges in traffic forecasting.

Cao, Yang↗