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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The influence of alfalfa-switchgrass intercropping on microbial community structure and function

The use of nitrogen fertilizer on bioenergy crops such as switchgrass results in increased costs, nitrogen leaching and emissions of N 2 O, a potent greenhouse gas. Intercropping with nitrogen-fixing alfalfa has been proposed as an environmentally sustainable alternative, but the effects of synthetic fertilizer versus intercropping on soil microbial community functionality remain uncharacterized. Here we analysed 24 metagenomes from the upper soil layer of agricultural fields from Prosser, WA over two growing seasons and representing three agricultural practices: unfertilized switchgrass (control), fertilized switchgrass and switchgrass intercropped with alfalfa. The synthetic fertilization and intercropping did not result in major shifts of microbial community taxonomic and functional composition compared with the control plots, but a few significant changes were noted. Most notably, mycorrhizal fungi, ammonia-oxidizing archaea and bacteria increased in abundance with intercropping and fertilization. However, only betaproteobacterial ammonia-oxidizing bacteria abundance in fertilized plots significantly correlated to N 2 O emission and companion qPCR data. Collectively, a short period of intercropping elicits minor but significant changes in the soil microbial community toward nitrogen preservation and that intercropping may be a viable alternative to synthetic fertilization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Attribute-Guided Adversarial Training for Robustness to Natural Perturbations

We report while existing work in robust deep learning has focused on small pixel-level norm-based perturbations, this may not account for perturbations encountered in several real world settings. In many such cases although test data might not be available, broad specifications about the types of perturbations (such as an unknown degree of rotation) may be known. We consider a setup where robustness is expected over an unseen test domain that is not i.i.d. but deviates from the training domain. While this deviation may not be exactly known, its broad characterization is specified a priori, in terms of attributes. We propose an adversarial training approach which learns to generate new samples so as to maximize exposure of the classifier to the attributes-space, without having access to the data from the test domain. Our adversarial training solves a min-max optimization problem, with the inner maximization generating adversarial perturbations, and the outer minimization finding model parameters by optimizing the loss on adversarial perturbations generated from the inner maximization. We demonstrate the applicability of our approach on three types of naturally occurring perturbations --- object-related shifts, geometric transformations, and common image corruptions. Our approach enables deep neural networks to be robust against a wide range of naturally occurring perturbations. We demonstrate the usefulness of the proposed approach by showing the robustness gains of deep neural networks trained using our adversarial training on MNIST, CIFAR-10, and a new variant of the CLEVR dataset.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Laser Plasma Interaction in the MG Magnetic Field (Final Report)

Strong magnetic fields change properties of plasma. Employment of the magnetic fields can improve conditions for inertial confinement fusion. Compression and heating of the magnetized plasma is a base of the MagLIF pulsed power approach to the controlled fusion. Study of expansion and heating of plasma in the external magnetic fields, development of plasma instabilities, parametric and other effects are important for basic physics and applications. The main goal of the research for the grant was experimental investigation of laser produced plasma in the well characterized and controlled MG magnetic fields. We developed a platform for investigation of high intensity laser-plasma interaction (LPI) in the MG fields using a university-scale pulsed power machine. A Zebra machine at UNR generated transverse magnetic fields of 3 MG on the surface of the rod load and longitudinal fields of 1.4 MG in the coil loads. The magnetic fields were characterized with two-color Faraday rotation diagnostics. The pulsed power machine provided almost static magnetic fields for LPI compared to the much faster laser driven magnetic fields. We found that eddy currents in the rising magnetic field generate plasma on the metal targets. Eddy currents did not impact Si and CH dielectric targets. A Leopard laser with intensity in the focus up to 10 19 W/cm 2 produced plasma in the MG magnetic fields. The modified reflected Faraday diagnostics was used to study laser driven B-field at the MTW laser at Laboratory for Laser Energetics, UR. We demonstrated a slow dependence of the magnetic field in the coil on the applied laser intensity. The magnetic field increased by a factor of 2 if laser intensity increased by a factor of 30. This scaling is important for comparison of experiments at different laser facilities. Expansion of the plasma in the 2-3 MG external B-field was studied. Laser-produced plasma in the azimuthal magnetic field took the unique form of a thin disc expanding radially with a velocity of 250 km/s and confined in the vertical direction. A HYDRA MHD program at the University of Rochester was applied for simulations of LPI in the magnetic field B >3 MG. Simulations for the plasma disc parameters and the expansion dynamics were in a good agreement with experiments. Generation of narrow dense plasma jets in the longitudinal magnetic field of 0.6-0.8 MG was studied. Narrow plasma jets reached a length of 3-4 mm with the electron plasma density of (0.2-1.2)x10 20 cm -3 . A jet tip propagated with the velocity of 160-200 km/s. MHD simulations showed a good agreement of the dynamics of the formation of plasma jets with experiments. These jets are relevant to astrophysical jets. Simulations of K-shell spectra of Si plasma was performed for LPI in the B-field. The laser prepulse generated plasma near the laser target. A PrismSPECT model with a MeV electron beam produced by the laser was used. The spectral modelling showed the increased plasma density by a factor by 2-3 in the magnetic field. This was in agreement with the observed dynamics of the plasma plume confined by the axial magnetic field. The two-plasmon decay was studied in the 2.5-3 MG transversal magnetic fields. Strong 2-3.5 nm spectral widening and a 2-4 nm shifts of “red” and “blue” 3/2ω 0 spectral components were observed. The large shift and widening exceed the expected temperature and magnetic shift. PIC simulations are performing to clarify physics of this effect. The experimental research program for the grant is completed. New plasma effects in the MG fields were studied at the university-scale pulsed power generator. Two graduate and two undergraduate UNR and UR students carried experiments at the Zebra generator, supported and developed plasma diagnostics, provided data processing, and performed MHD simulations of LPI in the strong magnetic field. Research results are published in 9 referred papers and presented in 12 conferences. Program manager: Kramer U. Akli; Collaborators: R. C. Mancini and H. Sawada, University of Nevada, Reno (UNR); R. Betti and A. V. Maximov, University of Rochester (UR).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

SFA-VirOmics

PNNL's Soil Microbiome Science Focus Area (SFA) is focused on understanding the basic biology underpinning how interactions among various soil microbial community members, across trophic levels, lead to the emergence of community functions. Moisture, in particular, drives microbial interactions and influences everything from cell function to substrate fate within soils. The group predicts this results in repeatable, predictable phenotypes. The sum of these phenotypes comprises the “soil metaphenome”. Understanding how the soil metaphenome shifts in response to moisture will provide a basis for modeling and predicting these shifts in reaction network responses. Visit the PNNL Soil Microbiome Science Focus Area Program homepage for more information. PNNL’s Soil Microbiome SFA Virome Dataset Annotation page is an extension to the PNNL Soil Microbiome SFA repository on DataHub allows for exploring and downloading integrated experimental omics dataset annotations, associated experimental metadata, pre- and post-processed viral data files, and other associated materials directly related to experimental viral project data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Nontargeted vs. Targeted vs. Smart Load Shifting Using Heat Pump Water Heaters

Deployment of CTA-2045–enabled devices is increasing in the U.S. market. These devices allow utilities or third-party aggregators to control appliance energy use in homes, and could also be applied to end uses in small commercial buildings. This study focuses on a field study using CTA-2045–enabled water heaters to shift electric load off the peak and toward periods when renewable resources are more prevalent (e.g., near noon for solar resources and near midnight for wind resources). The following load shifting strategies were compared to understand effects on the aggregate load-shifting capabilities of Heat Pump Water Heaters (HPWHs) and on consumer hot water supply: non-targeted (traditional), targeted (grouped, with different shifting schedules) and “smart” (adaptive control commands). The results of this study show that targeted and smart control strategies yield significantly more load-shifting potential from a population of water heaters than the non-targeted approach without sacrificing hot water supply to occupants. However, as control commands become more aggressive, aggregators may face challenges in meeting consumer hot water demand. Furthermore, the findings and lessons learned can benefit electric utilities and inform updates to manufacturer controls and communications standards. The data collected may also be useful for developing and validating HPWH models.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Learning Spectral Templates for Photometric Redshift Estimation from Broadband Photometry

Estimating redshifts from broadband photometry is often limited by how accurately we can map the colors of galaxies to an underlying spectral template. Current techniques utilize spectrophotometric samples of galaxies or spectra derived from spectral synthesis models. Both of these approaches have their limitations: either the sample sizes are small and often not representative of the diversity of galaxy colors, or the model colors can be biased (often as a function of wavelength), which introduces systematics in the derived redshifts. In this paper, we learn the underlying spectral energy distributions from an ensemble of ∼100 K galaxies with measured redshifts and colors. We show that we are able to reconstruct emission and absorption lines at a significantly higher resolution than the broadband filters used to measure the photometry for a sample of 20 spectral templates. We find that our training algorithm reduces the fraction of outliers in the derived photometric redshifts by up to 28%, bias up to 91%, and scatter up to 25%, when compared to estimates using a standard set of spectral templates. We discuss the current limitations of this approach and its applicability for recovering the underlying properties of galaxies. Our derived templates and the code used to produce these results are publicly available in a dedicated Github repository: https://github.com/dirac-institute/photoz-template-learning.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

dlppi2 (b1)

The Doppler lidar (DL) is an active remote-sensing instrument that provides range- and time-resolved measurements of the line-of-sight component of air velocity (i.e., radial velocity) and attenuated aerosol backscatter. The DL operates in the near-infrared and is sensitive to backscatter from atmospheric aerosol, which are assumed to be ideal tracers of atmospheric wind fields. The DL works by transmitting short pulses of infrared laser light into the atmosphere. Atmospheric aerosols scatter a small fraction of that light energy back to the transceiver, where it is collected and recorded as a time-resolved signal. From the delay between the outgoing pulse and the backscattered signal, the instrument infers the distance to the scattering volume. Coherent detection is used to measure the Doppler frequency shift of the backscatter signal. This is accomplished by mixing the backscatter signal with a reference laser beam (i.e., local oscillator) of known frequency. The onboard signal processor then determines the Doppler frequency shift from the spectrum of the mixed signal. The Doppler frequency shift and thus the radial air velocity is determined from the peak of the Doppler spectrum. The attenuated backscatter is determined from the energy content of the Doppler spectra. The DL provides accurate measurements of radial velocity in regions of the atmosphere where aerosol concentrations are high enough to ensure good signal-to-noise ratio. Thus, valid data are usually limited to the atmospheric boundary layer where aerosol is ubiquitous. Valid measurements can also be obtained in elevated aerosol layers or in optically thin clouds above the boundary layer. Most of the ARM DLs have full upper-hemispheric scanning capability, enabling 3D mapping of turbulent flows in the atmospheric boundary layer. With the scanner pointed vertically, the DL provides height- and time-resolved measurements of vertical velocity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Grid Value Analysis of Geothermal Systems for End-Use Applications

Fuel based end-uses for residential, commercial, and industrial consumers require a technology change to achieve economy-wide decarbonization. Space heating accounts for 42% of residential and 32% of commercial energy demand, much of which is currently met through carbon emitting fuels. Industrial energy use is heavily fuel based with electricity currently representing 13% of energy demand. Geothermal heat pumps (GHPs) and geothermal direct use can eliminate the need for CO2 emitting and simultaneously allow for more efficient electrification of end uses. Past work has assessed the impact on total energy costs and generation investments but did not identify specific grid services benefited. Energy usage in residential and commercial structures was assessed by leveraging data from ComStock and ResStock models. These models utilize housing attributes, occupancy patterns, weather data, and sophisticated energy simulations to generate hourly load profiles for individual buildings identified by unique IDs associated with their locations. Industrial sector energy use was evaluated using information from the Manufacturing Energy Consumption Survey (MECS) as well as plant utilization data from the US Census to estimate hourly plant operations. The change in end-use demand for electricity, natural gas, and other fuels was calculated for different technologies that could meet this need. Using the ReEDS capacity expansion model, we produce regional price profiles that capture the grid benefit associated with the amount and timing of energy shifts in the power system from the adoption of geothermal systems relative to other technologies that could meet space heating, space cooling, and process heat requirements. We find that geothermal systems for meeting end-use demand add value to the energy system. In buildings where geothermal systems increase grid costs, these values are offset by reduced fuel costs and benefits to externalities, including emissions and health impacts.

decarbonization↗
DOE OSTI2025

The HTR-Proteus Benchmark: Analysis and Use as a Verification and Validation Case

This presentation outlines the evaluation and application of the HTR-Proteus benchmark as a verification and validation (V&V) case for advanced reactor modeling tools. The work supports the U.S. Department of Energy’s HALEU Availability Program (HAP) and the joint DOE/NRC DNCSH project, which aims to reduce criticality safety uncertainties in commercial-scale HALEU fuel cycle and transportation systems. The HTR-Proteus experiments, conducted at the Paul Scherrer Institute, provide high-fidelity data for TRISO-fueled, graphite-moderated pebble bed reactors with high neutron leakage—conditions relevant to HALEU transport scenarios. This study focuses on Cores 4.2 and 4.3 of the HTR-Proteus benchmark, analyzing key sources of uncertainty including pebble packing, TRISO particle positioning, and core height. Using Project Chrono for realistic pebble geometries and Serpent, SHIFT, and MCNP for neutronics simulations, the study quantifies the impact of these uncertainties on the effective multiplication factor (keff). Results show that a sample size of 110 pebble configurations is sufficient to converge keff, with ±30 pcm uncertainty due to packing randomness. TRISO positioning and core height variations also significantly influence keff, highlighting the importance of detailed modeling in V&V efforts. The benchmark serves as a valuable test case for validating the Griffin reactor physics code and improving confidence in HALEU system simulations.

73 - NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Phenological shifts in lake stratification under climate change

One of the most important physical characteristics driving lifecycle events in lakes is stratification. Already subtle variations in the timing of stratification onset and break-up (phenology) are known to have major ecological effects, mainly by determining the availability of light, nutrients, carbon and oxygen to organisms. Despite its ecological importance, historic and future global changes in stratification phenology are unknown. Here, we used a lake-climate model ensemble and long-term observational data, to investigate changes in lake stratification phenology across the Northern Hemisphere from 1901 to 2099. Under the high-greenhouse-gas-emission scenario, stratification will begin 22.0 ± 7.0 days earlier and end 11.3 ± 4.7 days later by the end of this century. It is very likely that this 33.3 ± 11.7 day prolongation in stratification will accelerate lake deoxygenation with subsequent effects on nutrient mineralization and phosphorus release from lake sediments. Further misalignment of lifecycle events, with possible irreversible changes for lake ecosystems, is also likely.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Hyperspectral radiance mapping and chromatic correction for temperature measurement in laser-heated diamond anvil cells

In laser-heated diamond anvil cell (DAC) experiments, the effective heated region typically decreases in size with increasing pressure, leading to steeper thermal gradients. Under these conditions, chromatic aberration in the optical path from sample to detector can significantly create bias in spectro-radiometric temperature measurement. We present a radiance-mapping approach using a hyperspectral camera that records 25 spectral channels spanning 605–875 nm at each pixel in a single exposure, providing spatially and spectrally resolved radiance in each frame. This enables chromatic effects to be recorded and corrected in data processing. We developed a procedure for hyperspectral mapping, involving per-camera calibration, crosstalk removal, measured spectral throughput functions, and optional sub-pixel co-registration to minimize chromatic distortion. The calibrated radiance maps are then used to derive temperature maps of the laser-heated hotspots. For smaller heating spots, the radiance mapping approach reveals chromatic shifts that conventional spectro-radiometric methods cannot quantify. Ambient-pressure heating experiments confirm accurate temperature retrieval. At high pressure, application of the hyperspectral system to a platinum-heating experiment at 12 GPa demonstrates stable temperature reconstruction under steep thermal gradients. Beyond mitigating chromatic aberrations, the ability to diagnose optical artifacts separately from emissivity variations during controlled test experiments or in situ suggests a path toward more rigorous spectral emissivity analysis and improved modeling of thermal transport in laser-heated DAC experiments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Orbital and spin character of doped carriers in infinite-layer nickelates

The recent discovery of superconductivity in Nd1-xSrxNiO2 has drawn significant attention in the field. A key open question regards the evolution of the electronic structure with respect to hole doping. Here we exploit x-ray absorption spectroscopy (XAS) and resonant inelastic x-ray scattering (RIXS) to probe the doping-dependent electronic structure of Nd1-xSrxNiO2. Upon doping, a high-energy feature in Ni L3-edge XAS develops in addition to the main absorption peak, while XAS at the O K-, Nd M3- and Nd M5-edge exhibits a much weaker response. This implies that doped holes are mainly introduced into Ni 3d states. By comparing our data to atomic multiplet calculations including D4h crystal field, the doping-induced feature in Ni L3-edge XAS is consistent with a d8 spin-singlet state in which doped holes reside in the 3dx2-y2 orbitals. This is further supported by the softening of RIXS orbital excitations due to doping, corroborating with the Fermi level shift associated with increasing holes in the Ni 3dx2-y2 orbital.

2-dimensional systems↗
DOE OSTI2021

An Integrated View of Hydraulic Induced Fracture Geometry in Hydraulic Fracture Test Site 2

Until relatively recently, most of our understanding about the geometry of hydraulically induced fractures in unconventional reservoirs has been inferred by patterns observed via microseismic monitoring. Important information, such as fracture-azimuth, fracture-length, height-growth and other geometric data has been determined from microseismic “event clouds”, which in turn has been used to interpret a stimulated reservoir volume (SRV). It is important to note that relatively limited microseismic results have been acquired in conjunction with other diagnostics and validated in a consistent manner. The Hydraulic Fracture Test Site 2 (HFTS2) in the Permian Delaware Basin provides a unique opportunity to compare the frac geometry interpretations derived from multiple frac diagnostic tools and at multiple scales. The integrated view that emerges from all the frac diagnostic tools is that in HFTS2 the geometries of hydraulically induced fractures are not random and with a highly complex branching architecture. In fact, the fracs are mostly vertical, parallel plana domains, and both vertically and horizontally asymmetrical. The hydraulically induced fractures have a very consistent azimuth with a strike that matches SHmax. At the distance corresponding to the spacing between nearby wells in HFTS2, ~ 660 ft, the pattern of strain interceptions observed from Low Frequency Distributed Acoustic Sensing (LF-DAS) shows far-field dimensions that are consistent with the stage length dimensions at the stimulated well. In general, larger stages with higher number of clusters create larger number of interceptions and wider stimulated intervals than that of shorter stages with the same cluster to cluster spacing and fewer clusters. The hydraulically induced fractures also show a clear tendency to preferentially grow upwards as shown by the microseismic data, by the relative lower number of LF-DAS interceptions in nearby deeper wells and finally by the observed LF-DAS strain patterns in the vertical observation well. In the near field, the geometries of the fracture domains are also consistent. As shown by the distributed strain measurements obtained during production via the monitoring of Rayleigh Frequency Shift (RFS), each cluster has a separate, non-overlapping, frac-zone-domain that are generally centered around the locations of each perforation cluster. Overall, the hydraulically induced fractures in HFTS2 are interpreted as occurring in swarms associated with individual clusters, each with its own unique geometry but with similar predictable geometric and propagation tendencies. The comprehensive frac diagnostic program in HFTS2, the well-pad layout that permits the investigation of the Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/1-21URTC/D011S018R003/2477511/urtec-2021-5396-ms.pdf/1 by Carol Worster on 28 February 2022 URTeC 5396 2 impact that nearby producing wells has on frac geometry, together with an innovative Design of Experiment (DofE) that includes sequential-fracing, consistent cluster-to-cluster distances and few single-perforation cluster stages, has allowed us to gain a unique perspective about the geometry of the induced hydraulic fractures on this pad. Finally, the HFTS2 dataset has also provided us with a better understanding of the applicability and limitations of the different diagnostic tools.

58 GEOSCIENCES↗
DOE OSTI2026

JWST Observations of Starbursts: Dust Processing in the M82 Superwind

We present JWST MIRI and NIRCam imaging of the inner ∼5 kpc of the M82 superwind at ~ $0''_{.}05 - 0''_{.}375$(∼0.9–6.5 pc) resolution. Targeted filters probe emission from polycyclic aromatic hydrocarbons (PAHs; F335M, F360M, F770W, F1130W) and continuum (F250M, F360M) The images reveal a network of cool wind filaments traced by PAHs. PAH surface brightness declines with the inverse square of distance to the midplane, suggesting that the incident radiation field from the starburst drives the observed PAH intensity out to ±2.5 kpc. The 3.3/11.3 and 3.3/7.7 μm band ratios show uniformity with distance from the starburst, though comparisons with mid-IR dust emission models indicate a modest shift toward larger PAHs. Outside the disk, 11.3/7.7 μm increases moderately, reflecting that PAHs become more neutral with distance from the starburst as they are exposed to a declining radiation field and ionization parameter. Overall, PAHs in the wind are consistent with standard-to-large sizes and standard-to-high ionization states. Including Spitzer and Herschel data, PAH abundance (q PAH ) is set at ∼1% in the starburst and remains unchanging out to ±5 kpc off the disk. This flat q PAH profile suggests that PAHs are shielded from the hot wind, perhaps residing in the surface layers of cool clouds, with possible replenishment from cloud interiors and enrichment of the halo from previous bursts. In this picture, clouds are not dense enough to promote PAH growth, and they likely undergo radiative cooling and mixing with the hot phase to survive the gauntlet for at least ∼20 Myr.

Cronin, Serena A. [University of Maryland, College↗
DOE OSTI2022

Simulation of Peach Bottom turbine trip transient with RETRAN-3D using BXFGEN

The Peach Bottom 2 Turbine Trip transient is used to evaluate the capabilities and accuracy of coupled 3-D neutronics/thermal hydraulics best estimate calculations for support of safety analysis. Selected results, obtained with RETRAN-3D, are compared to available measurements and benchmark results. The comparisons are analyzed and the application of RETRAN-3D for a best estimate analysis approach within the safety analysis methodology is discussed. Overall, both the thermal-hydraulic and neutronic results show a good comparison to the experimental data, and the model is considered to accurately predict test data. In particular, the initial acoustic response of the main steam line and the subsequent main pressurization stages are well-predicted. During the main pressurization stage, the timing and magnitude of the in-core local pressurization and associated void compression are properly predicted based upon the agreement between local power range monitors (LPRM) predictions upwards, but the shift is slightly underpredicted. This indicates the methodology is well-posed for simulating this class of transient response.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Effect of Mn on eutectic phase equilibria in Al-rich Al-Ce-Ni alloys

Microstructural analysis of additively manufactured (AM) Al-Ce-Ni-Mn alloys has identified phases not predicted from existing ternary liquidus projections in the Al-Ce-Ni system. Because the rapid cooling rate of AM is orders of magnitude above that of traditional casting, it is unclear if these additional phases arose from the non-equilibrium processing conditions of AM, a drastic shift in phase stability in the system due to the addition of 1 wt% Mn, or some combination of these two influences. The phases and microstructure of cast samples of Al-Ce-Ni and Al-Ce-Ni-Mn alloys were characterized for several annealing conditions which revealed the equilibrium phases at different temperatures. Phase analysis confirmed that minute levels of Mn substituted for Ni in the system drastically shifts the liquidus projection in the Al-rich corner of the ternary phase diagram such that the eutectic Al 3 Ni phase is suppressed in favor of the Al 23 Ni 6 (Ce,Mn) 4 phase. Further addition of Mn promotes the formation of Al 20 Mn 2 Ce and Al 10 Mn 2 Ce phases. The phase analysis data was then used to improve the CALPHAD modeling of the liquidus projection and isothermal sections for the Al-rich Al-Ce-Ni-Mn quaternary system. Thermodynamic modeling and experimental analysis on phases in the AM sample of Al-Ce-Ni with Mn confirmed that the phases present are consistent with Mn-containing Al-Ce-Ni cast samples. Here, this investigation demonstrates the potential for using secondary alloying elements to drastically alter phase stability and microstructure in alloy systems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Crystallization Mechanisms of Poly(vinylidene Fluoride- co -chlorotrifluoroethylene): Nucleation Transitions, Growth Kinetics, and Microstructure Evolution

The crystallization kinetics of FK-800, a commercial semicrystalline copolymer of chlorotrifluoroethylene and vinylidene fluoride (poly(CTFE-co-VDF)), dictate its microstructure and functional performance. Crystallization occurs between the glass transition (T g ≈ 31 °C) and melting point (T m ≈ 110 °C), with grain boundaries playing a key role in applications such as memristors, where they regulate filament growth. This study integrates in situ atomic force microscopy (AFM), grazing-incidence wide-angle X-ray scattering (GIWAXS), and differential scanning calorimetry (DSC) to characterize nucleation, growth, and morphology across the full crystallization window. Hot-stage AFM reveals a transition from homogeneous to heterogeneous nucleation near 45 °C and a shift from reaction-limited to diffusion-limited growth above 60 °C. Kinetics are analyzed using Lauritzen–Hoffman, Turnbull–Fisher, and Avrami models to extract surface free energies and activation barriers. A multiscale modeling framework is developed in which nucleation densities and growth rates measured by AFM are used to reconstruct Avrami kinetics, which are then validated against coverage data, and extrapolated to predict bulk crystallization behavior observed by DSC. GIWAXS confirms a primarily flat-on chain orientation at all temperatures, linking orientation to domain morphology. This integrative approach quantitatively connects nanoscale crystallization dynamics with macroscopic phase evolution, establishing a quantitative framework for modeling crystallization across time, temperature, and length scales.

Crystallization↗
DOE OSTI2022

MISPR : an open-source package for high-throughput multiscale molecular simulations

Computational tools provide a unique opportunity to study and design optimal materials by enhancing our ability to comprehend the connections between their atomistic structure and functional properties. However, designing materials with tailored functionalities is complicated due to the necessity to integrate various computational-chemistry software (not necessarily compatible with one another), the heterogeneous nature of the generated data, and the need to explore vast chemical and parameter spaces. The latter is especially important to avoid bias in scattered data points-based models and derive statistical trends only accessible by systematic datasets. Here, we introduce a robust high-throughput multi-scale computational infrastructure coined MISPR (Materials Informatics for Structure–Property Relationships) that seamlessly integrates classical molecular dynamics (MD) simulations with density functional theory (DFT). By enabling high-performance data analytics and coupling between different methods and scales, MISPR addresses critical challenges arising from the needs of automated workflow management and data provenance recording. The major features of MISPR include automated DFT and MD simulations, error handling, derivation of molecular and ensemble properties, and creation of output databases that organize results from individual calculations to enable reproducibility and transparency. In this work, we describe fully automated DFT workflows implemented in MISPR to compute various properties such as nuclear magnetic resonance chemical shift, binding energy, bond dissociation energy, and redox potential with support for multiple methods such as electron transfer and proton-coupled electron transfer reactions. The infrastructure also enables the characterization of large-scale ensemble properties by providing MD workflows that calculate a wide range of structural and dynamical properties in liquid solutions. MISPR employs the methodologies of materials informatics to facilitate understanding and prediction of phenomenological structure–property relationships, which are crucial to designing novel optimal materials for numerous scientific applications and engineering technologies.

36 MATERIALS SCIENCE↗