Search NASA⌕ Search

SEARCH · Search NASA

Results for “Physical Stimulation”

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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Electrical Resistivity Tomography based monitoring of stress perturbations to optimize placement of high-precision strain meters

The Center for Understanding Subsurface Signals and Permeability is a new U.S. Department of Energy Earthshot Center focused on understanding and predicting the long-term evolution of permeability in enhanced geothermal systems. The center will use a highly instrumented testbed within the Sanford Underground Research Facility to conduct field scale experiments that elucidate and test capabilities to simulate geochemical-geomechanical interactions and permeability evolution. Here we demonstrate initial developments using previously collected electrical resistivity tomography (ERT) monitoring data with high-performance multi-physics modelling advancements to inform the optimal location of two new monitoring boreholes. Specifically, ERT monitoring data collected during shear stimulation testing shows marked responses to changes in stress during borehole pressurization. We demonstrate how the same response is being simulated, ultimately to train a machine-learning algorithm to estimate rock properties and enable enhanced prediction of stress and strain responses anticipated during future testing campaigns.

Stress, EGS, CUSSP, 3D Electrical Imaging↗
DOE OSTI2026

Assessing the Effect of a Deep‐Rooted Grass on Belowground Carbon Storage in Cultivated Land: Insights From a Multi‐Site US Study

Agriculture depletes soil organic carbon (SOC), partly due to the exclusion of deep-rooted perennials. Reintroducing deep-rooted perennials to cultivated land may help to mitigate SOC loss. We quantified the effect of deep roots on SOC by comparing 8 to 30 year-old stands of switchgrass ( Panicum virgatum L .) with paired annual row crop fields at 12 sites across the central and eastern USA. We hypothesized that switchgrass would store more root C and SOC than neighboring shallow-rooted annual crops, and that these effects would extend deeper than 30 cm. We also evaluated whether switchgrass stimulates decomposition of SOC at depth using radiocarbon ( 14 C). Finally, we explored whether the effect of switchgrass on SOC is moderated by soil chemical and physical properties. While the effect of switchgrass on SOC in the surface 100 cm was positive at most sites, the average effect was not statistically significant (difference in SOC = 0.6 kg C m −2 [95% CI −0.8 to +1.9 kg C m −2 ]). By contrast, we found that root C was consistently more abundant under switchgrass, yielding an estimated additional 0.6 kg C m −2 in the surface 100 cm of soil [95% CI +0.5 to +0.7 kg C m −2 ]. 14 C measurements suggested that root C inputs were adding to existing SOC without stimulating decomposition. The effect of switchgrass on belowground C was not strongly related to any of the soil properties that we evaluated. Our observations show that root C can contribute substantially to belowground C stocks when deep-rooted perennials replace shallow-rooted crops.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Laminarin stimulates single cell rates of sulfate reduction whereas oxygen inhibits transcriptomic activity in coastal marine sediment

Abstract The chemical cycles carried out by bacteria and archaea living in coastal sediments are vital aspects of benthic ecology. These ecosystems are subject to physical disruption, which may allow for increased respiration and complex carbon consumption—impacting chemical cycling in this environment often thought to be a terminal place of deposition. We use the redox-enzyme sensitive probe RedoxSensor Green to measure rates of electron transfer physiology in individual sulfate reducer cells residing in anoxic sediment, subjected to transient exposure of oxygen and laminarin. We use index fluorescence activated cell sorting and single cell genomics sequencing to link those measurements to genomes of respiring cells. We measure per-cell sulfate reduction rates in marine sediments (0.01–4.7 fmol SO42− cell−1 h−1) and determine that cells within the Chloroflexota phylum are the most active in respiration. Chloroflexota respiration activity is also stimulated with the addition of laminarin, even in marine sediments already rich in organic matter. Evaluating metatranscriptomic data alongside this respiration-based technique, Chloroflexota genomes encode laminarinases indicating a likely ability to degrade laminarin. We also provide evidence that abundant Patescibacteria cells do not use electron transport pathways for energy, and instead likely carry out fermentation of polysaccharides. There is a decoupling of respiration-related activity rates from transcription, as respiration rates increase while transcription decreases with oxygen exposure. Overall, we reveal an active community of respiring Chloroflexota that cycles sulfate at potential rates of 23–40 nmol h−1 per cm3 sediment in incubation settings, and non-respiratory Patescibacteria that can cycle complex polysaccharides.

Lindsay, Melody R.↗
DOE OSTI2025

Hydraulic performance and wave transmission through nature-inspired perforated hollow-base piles breakwater

Nature-based Solutions (NbS) are critical to achieving long-term sustainable coastlines in deltaic coastlines, particularly susceptible to severe impacts under climate change. In recent years, coastal erosion has accelerated in the Vietnam Mekong Delta (VMD), particularly in the West Sea (from Ca Mau to Kien Giang). Due to the characteristics of muddy coastlines and eroded mangrove forests in this region, only a few engineering solutions have effectively reduced waves and promoted sediment accumulation to facilitate beach accretion. However, these solutions require significant investment and cannot be relocated or reused. Therefore, this study introduces a coastal mangrove-inspired perforated hollow-base piles breakwater (PHBPB), which uses the principle of biomimicry by studying the ability of mangrove groups to protect the coastline, stimulate sediment deposition, and over time, restore mangrove forests in the VMD. The hydraulic parameters of PHBPB were tested in 260 scenarios using a physical model, which included varying parameters such as crest width (B), pile row numbers (n c ), crest freeboard (R c ), and wave parameters (H s , T p ) in determining the capabilities of wave transmission, reflection, and wave dissipation. The results showed that the process of wave energy dissipation through perforated hollow-base breakwaters without piles (PHBBWP) is governed by three main parameters, including the relative water depth of the crest (R c /H m0,i ), the relative width of the crest (B/H m0,i ), and the wave slope at the structure location (s m = H m0,i /L m ). In contrast, for PHBPB, the primary influencing factors are the relative submergence depth or the length of the submerged pile portion (R c /H m0,i ) and the relative width of the pile system (X b /L m ). Finally, the hollow structure is suitable for the soft, weak mud geology in this region with poor load-bearing capacity, allows for rapid installation, is reasonably cost-effective, and can be relocated and reused once regeneration has been completed in each stretch of coastline.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Manipulating Excitonic Quantum Droplets in Two-Dimensional CdSe Nanoplatelets via Thickness and Core/Shell Morphology

Recently, photoexcitation of high-density 4 or 5 monolayer (ML) thick CdSe nanoplatelet films at temperatures below ~200K was observed to produce pump-intensitydependent, superlinear, progressively red-shifted light output due to amplified spontaneous emission (ASE) from polyexcitonic species, distinct from biexcitonic ASE. These polyexcitonic species comprise Coulombically bound multiexciton states, termed “quantum droplets”, that form when multiexciton binding energy exceeds thermal energy fluctuations. In this work, we investigate thinner samples as well as core/shell nanoplatelet films and find that the 3 ML sample supports quantum droplet ASE up to higher temperatures than the 4 or 5 ML whereas core/shell structures suppress this form of ASE even at very low sample temperatures despite observable biexcitonic ASE, suggesting that the reduced or repulsive Coulomb binding energy of multiple excitons suppresses quantum droplets. These findings help to add understanding of routes to harness quantum droplet optical nonlinearities.

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

Twisted perovskite layers come together

The realization of twisted ligand-free two-dimensional halide perovskite-based moiré superlattices enables twistronic control of exciton dynamics in these systems and brings stimulating implications towards the development of halide perovskite photonic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Lignin Removal in Subcellular Location of Poplar Cell Wall During Pretreatment Significantly Impacts Cellulose Digestibility

The γ-valerolactone (GVL) pretreatment is one of the leading solvent-based methods for producing high-quality lignin under mild conditions. However, the glucan conversion yield from GVL pretreated biomass remains unsatisfactory. To explore the discrepancies between the relatively low glucan conversion and high lignin extraction, we conducted GVL−HCl and NaOH pretreatments on poplar and investigated their effects on lignin content and location, as well as on enzymatic hydrolysis of poplar cell walls at the subcellular level. Under designated pretreatment conditions of GVL−HCl (90% GVL, 0.1 M HCl, 100 °C, 1 h) and NaOH (1 M, 121 °C, 2 h), the glucan conversion yields were 69.4% and 95.8%, with lignin removal rates of 67.8% and 47.7%, respectively. Four types of GFP-labeled carbohydrate binding modules were used to identify different forms of cellulose in the pretreated cell walls. The overall binding intensities to pretreated poplar were stronger for NaOH compared to GVL−HCl pretreatment. Stimulated Raman scattering microscopy imaging revealed that GVL−HCl preferentially extracted lignin from the compound middle lamella and cell corner areas, while NaOH effectively dissolved lignin in the secondary cell walls. Real-time imaging of cellulase degradation of pretreated cell walls further indicated that digestion started from both the cell lumen and the compound middle lamella areas for GVL, whereas it occurred uniformly across the secondary cell walls for NaOH. Our findings suggest that the location of lignin removal during pretreatment is crucial for enzymatic cellulose degradation, in addition to the total amount of lignin extraction.

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

High Energy Physics Network Requirements Review: Final Report, July 2024–December 2024

The world-class research infrastructure at the US Department of Energy (DOE) Office of Science (SC) provides the research community with premier observational, experimental, computational, and network capabilities. Each user facility is designed to provide unique capabilities to advance the core DOE mission in science and technology for its SC program to stimulate rich scientific discoveries and enhance its innovation ecosystem. Research communities gather and flourish around each user facility, bringing together new and enhanced perspectives. The continual reinvention of the practice of science — as users and staff forge novel approaches expressed in research workflows — unlocks new discoveries and propels scientific progress. Within this research ecosystem, the high-performance computing (HPC) and networking user facilities stewarded by the SC’s Advanced Scientific Computing Research (ASCR) program play a dynamic cross-cutting role, enabling complex workflows demanding high-performance data, networking, and computing solutions. The ASCR facilities enterprise seeks to understand and meet the needs and requirements across SC and DOE domain science programs and priority efforts, highlighted by the formal requirements review methodology. Between July and December 2024, the Energy Sciences Network (ESnet) and the Office of High Energy Physics (HEP) of the DOE-SC organized an ESnet requirements review of HEP-supported program activities. Preparation for these events included identification of key stakeholders: program and facility management, research groups, and technology providers. Each stakeholder group was asked to prepare formal case study documents about its relationship to the HEP program to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Prediction and Analysis of Utah FORGE Injection Activities using a Coupled Thermo-hydro-mechanical and Earthquake (THM+E) Modeling Workflow

A coupled thermo-hydro-mechanical (THM) numerical workflow that is capable of modeling seismic slip is critical for the successful development of enhanced geothermal systems (EGS). By integrating key physical processes, this workflow enables accurate simulation of temperature and pressure diffusions, stress changes, and induced seismicity. As a result, it serves as a vital tool for predicting induced seismicity and optimizing reservoir stimulation strategies. The Utah FORGE (Frontier Observatory for Research in Geothermal Energy) project, located near Milford, Utah, is a U.S. Department of Energy initiative aimed at advancing EGS technology. In April 2024, eight new stimulation stages (Stages 3R-10) were conducted in well 16A (injection well) subsequent to the first series of stimulation (Stages 1-3) performed in April, 2022. To monitor the induced seismicity, geophones were deployed in wells 58-32, 56-32, and 78B-32, while fiber optic cables were also installed in wells 16B, 78-32, and 78B-32 to collect microseismic data and detect frac hits Preliminary analyses of microseismic catalogs and fiber optic data suggest that the stimulated fractures in Stages 3R–6 closely align with that generated during Stage 3, indicating that the new stimulations were likely reactivating the previously stimulated fracture. To better understand the underlying process, a comprehensive modeling approach that can accurately capture thermal, hydrological, mechanical, and seismic responses is essential. In this work, we propose and utilize a coupled thermo-hydro-mechanical and earthquake (THM+E) simulation workflow to numerically investigate the stimulation activities on well 16A. The specific objective is to confirm whether the new stimulation stages (Stages 3R–6) reactivated fractures previously stimulated during Stage 3. For this purpose, we perform THM+E simulations individually for Stages 3, 3R, 4, and 5, incorporating the discrete fracture networks (DFNs) created by the plane-fitting technique based on the microseismic catalogs. The simulation workflow consists of two separate models: a THM model and an earthquake model, coupled in a one-way manner. Detailed descriptions of the workflow are provided in Section 3. Simulation results are presented in terms of injection pressure, permeability evolution, and predicted seismic catalogs, which are then compared with field data for further analyses. This report is structured as follows. In Section 2, we present detailed analyses of the field data and propose the hypothesis that the new stimulation stages (Stages 3R–6) were probably reactivating the previously stimulated fractures in Stage 3. In Section 3, we introduce the coupled THM+E workflow and the problem setup to validate our hypothesis, followed by the simulation results for each stage in Section 4. Meanwhile, discussions are included to analyze the model predictions and their comparison with field data. Lastly, we conclude the report and outline future plans in Section 5.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Utah FORGE 6-3712: Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks - 2024 Annual Workshop Presentation

This is a presentation on the Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks by GTC Analytics, presented by Jesse Williams. This video slide presentation discusses the development of machine learning-based predictive tools to estimate the magnitude-frequency response of stimulation-induced seismicity. This presentation was featured in the Utah FORGE R&D Annual Workshop on August 15, 2024.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

A customizable data management framework for high-repetition-rate high-energy-density science

The high-energy-density (HED) physics community is moving toward a new paradigm of high-repetition-rate (HRR) operation. To fully leverage the scientific power of HRR HED facilities, all of the components of each subsystem (laser, targetry, and performance diagnostics) must be connected and synchronized in a reliable and robust manner while the data acquired are tagged and archived in real time. To this end, GA has begun developing a generalized NoSQL-database framework, the MongoDB repository for information and archiving. An organizational strategy has been developed that shifts HED data organization from a shot-based to a diagnostic-based approach in order to increase archival and retrieval efficiency that lends itself to optimization applications. This work is a first step in pushing HRR HED science toward data management solutions that emphasize machine actionability and aim to stimulate community engagement to define data standards in HED science.

Instruments & Instrumentation↗
DOE OSTI2024

Machine Learning‐Assisted Microearthquake Location Workflow for Monitoring the Newberry Enhanced Geothermal System

Abstract Enhanced geothermal systems (EGS) offer a sustainable energy source but face challenges in accurately locating microearthquakes induced during reservoir stimulation. Locating these microearthquakes provides reliable feedback on the stimulation progress. Current deep learning methods for locating earthquakes require extensive data sets for training, which is problematic as detected microearthquakes are often limited. To address the scarcity of training data, we propose a practical workflow using probabilistic multilayer perceptron (PMLP) which predicts microearthquake locations from cross‐correlation time lags in waveforms. Utilizing a 3D velocity model of Newberry site derived from ambient noise interferometry, we generate numerous synthetic microearthquakes and 3D acoustic waveforms for PMLP training. Accurate synthetic tests prompt us to apply the trained network to the 2012 and 2014 stimulation field waveforms. To enhance the accuracy of source localization, we carefully handpick the P‐arrival times. Predictions on the 2012 stimulation data set show major microseismic activity at depths of 0.5–1.2 km, correlating with a known casing leakage scenario. In the 2014 data set, the majority of predictions concentrate at 2.0–2.9 km depths, consistent with results obtained from conventional physics‐based inversion, and align with the presence of natural fractures from 2.0 to 2.7 km. We validate our findings by comparing the synthetic and field picks, demonstrating a satisfactory match for the first arrivals. By combining the benefits of quick inference speeds and accurate location predictions, we demonstrate the feasibility of using realistic synthetic data set to locate microseismicity for EGS monitoring.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Hybrid direct drive with a two-sided ultraviolet laser

This paper presents a “hybrid” approach to direct drive inertial confinement fusion that can exploit a high-energy gas laser with two opposed beams. The target and driver are asymmetric, much like experiments performed on the National Ignition Facility, but have been designed to benefit from scale and their particular compatibility with a fusion power plant. The imploded masses (and areal densities) are increased by a factor of 12 (3) and provide a path to high-gain implosions that robustly ignite. The design also mitigates common concerns such as laser imprint and cross-beam energy transfer. We discuss the rationales for a hybrid target, the methods used to control implosion symmetry, and the implication(s) for inertial fusion energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Molten Salt Electrodeposition: Review

Molten salt electrodeposition is the process of producing impressively dense deposits of refractory metals using the electrolysis of molten salts. However, predicting which electrochemical parameters and setup will best control different kinds of deposition (density, homogeneity, etc.) is an ongoing challenge, due to our limited understanding of the properties and mechanisms that drive molten salt electrodeposition. Because these advancements have been made rapidly and in different arenas, it is worth taking the time to stop and assess the progress of the field as a whole. These advancements have increasing relevance for the energy sector, the development of space materials and engineering applications. In this review, we assess four critical facets of this field: (1) how the current understanding of process variables enhances the electrodeposition of various molten salts and the quality of the resulting product; (2) how the electrochemical setup and the process parameters (e.g., cell reactions) are known to impact the electrodeposition of different metal coatings and refractory-metal coatings; (3) the benefits and drawbacks of non-aqueous molten salt electrodeposition, and (4) promising future avenues of research. The aim of this work is to enhance our understanding of the many procedures and variables that have been developed to date. The expectation is that this review will act as a stimulant, motivating scientists to delve further into the investigation of refractory-metal alloys by utilizing molten salt electrodeposition.

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

Ligand‐Induced Crystallization Control in MAPbBr 3 Hybrid Perovskites for High Quality Nanostructured Films

AbstractControlling the formation of hybrid perovskite thin films is crucial in obtaining high‐performance optoelectronic devices, since factors like morphology and film thickness have a profound impact on a film's functionality. For light‐emitting applications grain sizes in the sub‐micrometer‐range have previously shown enhanced brightness. It is therefore crucial to develop simple, yet reliable methods to produce such films. Here, a solution‐based synthesis protocol for the on‐substrate formation of MAPbBr3 (MA = methylammonium) nanostructures by adding the bifunctional rac‐3‐aminobutyric acid to the precursor solution is reported. This synthesis route improves key optical properties such as photoluminescence quantum yields and life times of excited states by inducing a controlled slow‐down of the film formation and suppressing agglomeration effects. In situ spectroscopy reveals a delayed and slowed down crystallization process, which achieves synthesis of perovskite structures with much reduced defect densities. Further, aggregation can be controlled by the amount of amino acid added and adjusting the synthesis protocol allows to produce cubic crystallites with targeted size from nanometer to micrometer scales. The nanocrystalline MAPbBr3 samples show enhanced amplified spontaneous emission (ASE) intensities, reduced ASE thresholds and purer ASE signals, compared to pristine films, even under intense optical driving, making them promising structures for lasing applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Shape Anisotropy-Dependent Leaking in Magnetic Neurons for Bio-Mimetic Neuromorphic Computing

Spiking neural networks seek to emulate biological computation through interconnected artificial neuron and synapse devices. Spintronic neurons can leverage magnetization physics to mimic biological neuron functions, such as integration tied to magnetic domain wall (DW) propagation in a patterned nanotrack and firing tied to the resistance change of a magnetic tunnel junction (MTJ), captured in the domain wall-magnetic tunnel junction (DW-MTJ) device. Leaking, relaxation of a neuron when it is not under stimulation, is also predicted to be implemented based on DW drift as a DW relaxes to a low energy position, but it has not been well explored or demonstrated in device prototypes. Here, in this work, we study DW-MTJ artificial neurons capable of leaky integrate-and-fire (LIF) behavior and demonstrate geometry-dependent leaking dynamics that results in repeatable, tunable LIF operation. Studying the behavior of five different device designs, we show tuning the geometry, stimulating fields and currents, and location of electrical contacts results in a wide range of neuron behavior. Additionally, implementation of an asymmetric notch allows for nonlinear pinning which increased expressivity without sacrificing leaking. The measured behavior is implemented in a simulated spiking neural network that outperforms a 1D model of continuous DW motion and approaches the performance of an ideal LIF activation function. The results show that the analog LIF capability of DW-MTJ neurons combines many desirable neuron functions into a single device, which can result in varied forms of multifunctional neuromorphic computing.

42 ENGINEERING↗