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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Work Function Modification via Combined Charge-Based Through-Space Interaction and Surface Interaction

Work function modification of electrodes is an important factor to achieve high performance in organic electronics. However, a clear explanation of the origin of work function modification has remained elusive. Here, it is investigated how the work function of electrodes is affected by the charge-based through-space interaction with the well-known surface interaction. The studies reveal that the formation of a surface dipole leads to a work function shift, even when the work function modifying layer and substrate are separated. A work function shift is also demonstrated by electrophoretic deposition of ionic polyelectrolytes while the same polyelectrolytes do not cause any work function shift when they are spin cast. More noteworthy is that a neutral (nonionic) polymer which has no specific surface-interacting functional groups can induce work function shift of its substrate by a charge-based through-space interaction when deposited by electrospraying. These results provide a more comprehensive understanding of work function modification and motivate the design and selection of a wide range of effective work function modifying layers for organic electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Plasma Surface Interactions: Bridging from the Surface to the Micron Frontier through Leadership Class Computing (Final Technical Progress Report)

The performance demands on plasma-facing components (PFCs) in future fusion power plants are beyond the capability of current materials. In defining the plasma-surface interaction (PSI), it is evident that three coupled spatial regions influence PFC materials evolution and performance. These regions consist of (1) the edge and scrape-off layer region of the plasma, (2) the near-surface material response to extreme thermal and particle fluxes under the influence of, and feedback to, the plasma sheath, and (3) the structural material’s response to an intense, 14 MeV peaked neutron spectrum, which produces very high concentrations of transmuted elements through (n,p) and (n,α) reactions and structural material property degradation. The objective of this project is to develop and deploy validated, high-performance simulation tools capable of predicting the performance of tungsten-based plasma-facing components (PFCs) in a burning fusion plasma environment, which includes modeling surface morphology evolution in either erosion or re-deposition regimes, and the recycling of hydrogen species. This requires the development of a leadership-scale computational code to predict PFC behavior that is well integrated to a suite of multiscale modeling techniques to bridge the scales needed to address complex physical and computational issues at the plasma surface interface and the transition region below the surface where neutron damage processes in the bulk dominate material behavior. Successful completion of this project will provide PFC simulation tools to evaluate steady-state performance of tungsten-based PFC and divertor components in burning plasma environments. This will enable the identification of critical experiments to confirm whether practical PFC solutions exist for magnetic fusion energy beyond ITER. More specifically, the research activities within this project focus on two broadly defined research thrusts: 1) Developing a new simulation code, Xolotl-PSI to predict PFC operating lifetime and performance, that is specifically designed to take advantage of leadership class computing facilities; and 2) Integrating and applying discrete particle-based, as well as continuum-based, multiscale modeling techniques to provide scientific discovery of the mechanisms controlling PFC and bulk materials evolution under fusion plasma and 14-MeV neutron exposure; in this thrust, the challenge of scale-bridging between atomistic/microstructural modeling and the continuum-scale of PFC device performance is achieved through multiscale modeling techniques. Throughout the grant period, research at UMass Amherst focused on the atomic-scale analysis of the dynamics and kinetics (transport and reactions) of small mobile helium clusters near surfaces and grain boundaries in plasma-exposed tungsten, as well as the proper parameterization and incorporation of these processes into our SciDAC team’s continuum-level cluster dynamics code (Xolotl). Our work also included characterization of large-scale molecular-dynamics (MD) simulation results of helium implantation into tungsten based on the findings of our analysis and comparisons of Xolotl simulation predictions with the large-scale MD simulation results for Xolotl validation purposes; emphasis was placed on the impact of helium cluster dynamics/kinetics on tungsten surface morphology, near-surface tungsten structure, and helium retention. Furthermore, our work included initiation of a research program on evaluating the impact of structural defects in tungsten due to plasma exposure (such as helium nanobubbles) on tungsten’s thermophysical properties, focusing on lattice thermal conductivity. Our studies contributed to a fundamental understanding of the effects of plasma-surface interactions on the dynamical response of plasma-facing materials in nuclear fusion devices and the development of predictive hierarchical multiscale computational tools for the quantitative description of the material’s dynamical response to plasma exposure.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Development and transferability of neural-network models for plasma-surface interactions

Plasma-surface interactions are increasingly critical to modern technologies; yet, accurate molecular dynamics simulations remain limited by the capabilities of interatomic potentials. Deep Potentials (DPs) promise to revolutionize the field by providing a systematic method for producing accurate interatomic potentials. The primary challenge of DP development is selecting a dataset, which efficiently spans the set of atomic environments one expects to encounter in the subsequent molecular dynamics simulations. The computational cost of density functional theory calculations, which are the typical basis for DP development, makes it impossible to directly verify the quality of a given DP. To address this challenge, we explore the development of a deep-learned interatomic potential, “DeepREBO,” trained to reproduce the behavior of the REBO2 empirical potential, enabling direct validation of training methodology and transferability. Using an active learning framework, we begin with a minimal dataset and iteratively expand it to train a Deep Potential-Smooth Edition model that faithfully reproduces REBO2 results for 25 eV hydrogen bombardment of diamond (001), a particularly challenging case. We show that small, carefully curated datasets can outperform large, unguided ones, with effective models requiring fewer than 15 000 snapshots. Subsequent transferability tests demonstrate that while DeepREBO generalizes well to diamond (111) surfaces, performance degrades for amorphous carbon or higher-energy impacts, highlighting the need for use-case-specific training data. We also evaluate methods to improve short-range repulsion. This study outlines best practices for training robust deep potentials and underscores the importance of dataset design for predictive plasma simulations.

Ab-initio molecular dynamics↗
DOE OSTI2022

Boron adatom adsorption on graphene: A case study in computational chemistry methods for surface interactions

Though weak surface interactions and adsorption can play an important role in plasma processing and materials science, they are not necessarily simple to model. A boron adatom adsorbed on a graphene sheet serves as a case study for how carefully one must select the correct technique from a toolbox of computational chemistry methods. Using a variety of molecular dynamics potentials and density functional theory functionals, we evaluate the adsorption energy, investigate barriers to adsorption and migration, calculate corresponding reaction rates, and show that a surprisingly high level of theory may be necessary to verify that the system is described correctly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Plasma Surface Interactions: Predicting the Performance and Impact of Dynamic PFC Surfaces

Interactions of plasma with material surfaces in tokamaks have long been recognized as crucial for development of practical fusion energy production. Such interactions can adversely affect both plasma performance and properties of tokamak materials by means of a large variety of physical phenomena involved. Among such phenomena attracting researchers’ attention are various mechanisms of erosion of plasma-facing components (PFCs) and resulting contamination of plasma with impurities, tritium retention in the first wall material, radiation damage and modification of mechanical properties of the tokamak structural materials, dust production, thermal loading limits and possibility of PFCs melting failure, etc. Aside from these phenomena, one of the main mechanisms strongly affecting fusion plasma discharge conditions is plasma recycling. The recycling taking place on PFCs, most importantly on divertor plates where the plasma fluxes are very large, is a major source of neutrals sustaining plasma pressure in scrape-off-layer (SOL) and contributing to SOL power dissipation by forming so-called detached plasma conditions in the divertor. Recycled neutrals can also play an important role in the edge plasma transport and stability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

A physical-based gas–surface interaction model for rarefied gas flow simulation

Empirical gas–surface interaction models, such as the Maxwell model and the Cercignani–Lampis model, are widely used as the boundary condition in rarefied gas flow simulations. The accuracy of these models in the prediction of macroscopic behavior of rarefied gas flows is less satisfactory in some cases especially the highly non-equilibrium ones. Molecular dynamics simulation can accurately resolve the gas–surface interaction process at atomic scale, and hence can predict accurate macroscopic behavior. They are however too computationally expensive to be applied in real problems. In this work, a statistical physical-based gas–surface interaction model, which complies with the basic relations of boundary condition, is developed based on the framework of the washboard model. In virtue of its physical basis, this new model is capable of capturing some important relations/trends for which the classic empirical models fail to model correctly. As such, the new model is much more accurate than the classic models, and in the meantime is more efficient than MD simulations. Therefore, it can serve as a more accurate and efficient boundary condition for rarefied gas flow simulations. - Highlights: • The new physical-based gas–surface interaction model satisfies the basic relations of boundary condition so that it can be used in rarefied gas flow simulations. • The new physical model possesses several advantages comparing to the empirical gas–surface interaction models, hence it's a more accurate boundary condition for rarefied gas flow study. • The new physical model is a statistical model which can be efficiently implemented by Monte Carlo method. It's much more efficient comparing to the MD simulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Plasma Surface Interactions: Predicting the Performance and Impact of Dynamic PFC Surfaces

The objective of this project is to develop, and integrate, high-performance simulation tools capable of predicting plasma-facing component (PFC) operating lifetime and the impact of the evolving surface morphology of tungsten-based PFCs on plasma contamination, including the dynamic recycling of fuel species and tritium retention, in future magnetic fusion devices. Establishing a fundamental physical understanding and developing predictive capabilities of plasma-surface interactions (PSI) requires simultaneously addressing complex and diverse physics occurring over a wide range of length (Angstroms to meters) and time (femtoseconds to years) scales, as well as integrating extensive physical processes across the plasma–surface interface. This requires development of not only detailed physics models and computational strategies at each scale, but also algorithms and methods to couple them effectively in a way that can be robustly validated. Deploying these tools requires the continued development and coupling of leadership-scale computational codes to describe the boundary plasma and the evolving PFC surface, as well as a host of simulations that bridge disparate scales to address complex physical and computational issues at the plasma–surface interface in multi-component materials systems for magnetic fusion energy development beyond ITER.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Final Progress Report The U.S. Department of Energy Research Grant No. DE-SC0008660 Plasma Surface Interactions: Bridging from the Surface to the Micron Frontier through Leadership Class Computing

The choice of material for the plasma facing components (PFC), in particular, for divertor targets, is one of the main issues for future tokamak reactors. There are two major requirements for the PFC’s material: acceptable level of tritium retention and durability in a harsh environment of fusion grade plasma. Based on these criteria, some years ago it was decided that tungsten is an acceptable material for divertor targets in ITER. However, further experimental studies reveal that the irradiation of tungsten even with low energetic (well below sputtering threshold!) He containing plasma causes significant modification of surface morphology, formation of the layer of He nano-bubbles (in the temperature range T<1000 K), “fuzz” (for 1000 K 2000 K) (e.g. see Fig. 1). Recall that He, being an ash of D-T fusion reactions, is an inherent impurity in fusion plasma. The goals of the UCSD Applied Plasma Theory Group was: i) investigate the mechanisms of the formation of He nano-bubble layer and fuzz growth under He irradiation, as well as the physics of transport of hydrogen species in tungsten lattice, and ii) develop physics understanding of the models suitable for the incorporation into the Xolotl-PSI code based on the reaction-diffusion approach, which is the flagship of the whole SciDAC project [8], which can guide both numerical simulations and experimental studies. Here we just highlight our major accomplishments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Optimal sample formulations for DNP SENS: The importance of radical-surface interactions

The efficacy of dynamic nuclear polarization (DNP) surface-enhanced NMR spectroscopy (SENS) is reviewed for alumina, silica, and ordered mesoporous carbon (OMC) materials, with vastly different surface areas, as a function of the biradical concentration. Importantly, our studies show that the use of a “one-size-fits-all” biradical concentration should be avoided when performing DNP SENS experiments and instead an optimal concentration should be selected as appropriate for the type of material studied as well as its surface area. In general, materials with greater surface areas require higher radical concentrations for best possible DNP performance. This result is explained with the use of a thermodynamic model wherein radical-surface interactions are expected to lead to an increase in the local concentration of the polarizing agent at the surface. We also show, using plane-wave density functional theory calculations, that weak radical-surface interactions are the cause of the poor performance of DNP SENS for carbonaceous materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Recollections for the 50th anniversary of the plasma surface interactions (PSI) in controlled fusion devices conference

The Plasma Surface Interactions in Controlled Fusion Devices (PSI) conference reached an important milestone in 2024 with its 50th anniversary. It was celebrated at its venue in Marseille by a special round table discussion gathering 6 former chairmen of its Programme Committees, who gave some highlights presented at the conference during the five decades. The article provides a summary of this overview.

Plasma Surface Interactions Conference↗
DOE OSTI2017

Time-Domain Modeling of RF Antennas and Plasma-Surface Interactions

Recent advances in finite-difference time-domain (FDTD) modeling techniques allow plasma-surface interactions such as sheath formation and sputtering to be modeled concurrently with the physics of antenna near- and far-field behavior and ICRF power flow. Although typical sheath length scales (micrometers) are much smaller than the wavelengths of fast (tens of cm) and slow (millimeter) waves excited by the antenna, sheath behavior near plasma-facing antenna components can be represented by a sub-grid kinetic sheath boundary condition, from which RF-rectified sheath potential variation over the surface is computed as a function of current flow and local plasma parameters near the wall. These local time-varying sheath potentials can then be used, in tandem with particle-in-cell (PIC) models of the edge plasma, to study sputtering effects. Particle strike energies at the wall can be computed more accurately, consistent with their passage through the known potential of the sheath, such that correspondingly increased accuracy of sputtering yields and heat/particle fluxes to antenna surfaces is obtained. The new simulation capabilities enable time-domain modeling of plasma-surface interactions and ICRF physics in realistic experimental configurations at unprecedented spatial resolution. We will present results/animations from high-performance (10k-100k core) FDTD/PIC simulations of Alcator C-Mod antenna operation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Data-Driven Modeling and Control of Systems with Plasma-Surface Interactions (Final Technical Report)

This final technical report summarizes the activities and accomplishments in the period from February 2023 thru January 2026. The objective of the proposed research is to investigate the physical mechanisms and processes underlying the formation of structures and patterns in systems with plasma-surface interactions. In the past decades, there have been extensive studies on the interaction of glow discharges, dielectric barrier discharges, and arc discharges with confining or intervening surfaces. The advancement of the understanding of these phenomena is not only of fundamental scientific interest and relevance to the knowledge of the plasma state, but also with profound implications in various technological applications. The research will integrate theoretical, computational, and experimental work within an innovative framework of data assimilation, i.e., optimally combining model predictions with measurements. The scientific merit of this research has three aspects. Firstly, it extends the studies of plasma-surface interactions to systems with insulator surfaces and multi-layer systems, while existing studies are predominantly on electrode surfaces. Secondly, it expects to develop a novel data-driven modeling approach based on data assimilation to enhance the predictive and control capabilities, which could make transformative contributions to basic plasma research. Thirdly, it will shed new light on outstanding problems related to formation of patterns interfacing plasmas. This project also aims to launch an education and outreach initiative at Texas A&M University-Kingsville, a non-R1, minority-serving institution in South Texas. The initiative is structured as a four-tier pyramid. Tier one will be a webinar series for culture and capacity building to inform broader audience in the region about the research fields of plasma science and engineering. Tier two will be the creation and offering of an upper-level undergraduate course on introductory plasma physics, which will help with the recruitment for the upper tiers. On tier three, we will engage and mentor senior design students to conduct work toward the research goal of this project. There will also be a certificate program on general plasma science for undergrad and graduate students, part of which will be lab training at Princeton University. Tier four will be the supervision and mentoring of Ph.D. students. Therefore, this project will systematically expand the talent pipeline, broaden participation from communities historically and geographically underrepresented in DOE SC research portfolio, significantly improve the research and education capacity at the PI’s institution, and contribute to developing a diverse workforce in plasma science and engineering.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Dataset, Code, and Models for Training Deep Learning Potentials for Low Temperature Plasma-Surface Interactions

This repository contains datasets, training scripts, and finished models, and test simulations used in the development of DeepREBO— a machine-learned interatomic potential trained to emulate the REBO2 empirical potential. The data was generated to study deep potential development for simulations of plasma-surface interactions. It uses an active learning framework, starting from a minimal dataset and iteratively expanding it. Included are those generated datasets, the trained models, and simulations used to evaluate the performance of the training process. This resource supports reproducibility and provides a reference framework for training deep potentials in plasma-surface interaction studies.

active learning↗
DOE OSTI2018

Suggestion of an Indicator to Evaluate Material Deposition in Resistance Spot Welding: Weld–Surface Interaction Index

Resistance spot welding (RSW) is still leading joining process in the automotive industry due to the simplicity and speed of the process. On the other hand, galvanized steel sheets provide improvement in corrosion resistance of the auto body. Material deposition has an influence on the corrosion resistance and weld strength; however, in the literature very little effort has been made to identify any weld–surface interaction numerically. In this study, a numerical approach called “Weld–Surface Interaction Index” (I{sub WSI}) has been introduced to investigate the effect of material deposition on the corrosion sensitivity of the welding zone and its periphery. A systematic investigation was carried out to better understand the effects of an electrode cap–galvanized steel sheet interface on the corrosion resistance of spot-welded steel. The chemical composition of DP600 steel sheet and Z-Trode electrode cap was analyzed by using a spectrometer. The specimens were then joined by using same caps up to 1200 welds. SEM–EDS analysis was also performed on the chosen specimens to determine the weight percentages (wt.%) of Fe, Zn and Cu. EDS analysis results and coefficient of variation wt.% of Fe, Zn and Cu were used to compose I{sub WSI} formula. In the proposed formula, wt.% of Zn represented resistivity of the cover to corrosion, while wt.% of Fe represents the vulnerability.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Protein-Glass Surface Interactions and Ion Desalting in Electrospray Ionization with Submicron Emitters

Theta glass electrospray emitters can rapidly mix solutions to investigate fast reactions that occur as quickly as 1 μs, but emitters with submicron tips have the unusual properties of desalting protein ions and affecting the observed abundances of some proteins as a result of protein–surface interactions. The role of protein physical properties on ion signal was investigated using 1.7 ± 0.1 μm and 269 ± 7 nm emitters and 100 mM aqueous ammonium acetate or ammonium bicarbonate solutions. Protein ion desalting occurs for both positive and negative ions. The signal of a mixture of proteins with the 269 nm tips is time-dependent and the order in which ions of each protein is observed is related to the expected strengths of the protein–surface interactions. These results indicate that it is not just the high surface-to-volume ratio that plays a role in protein adsorption and reduction or absence of initial ion signal, but the small diffusion distance and extremely low flow rates of the smaller emitters can lead to complete adsorption of some proteins and loss of signal until the adsorption sites are filled and the zeta potential is significantly reduced. After about 30 min, signals for a protein mixture from the two different size capillaries are similar. These results show the advantages of submicron emitters but also indicate that surface effects must be taken into account in experiments using such small tips or that coating the emitter surface to prevent adsorption should be considered. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Data from "Deep Potential Molecular Dynamics Simulations of Low-Temperature Plasma-Surface Interactions"

Data and input files related to the paper "Deep Potential Molecular Dynamics Simulations of Low-Temperature Plasma-Surface Interactions" (https://doi.org/10.1116/6.0004027). This includes the final DP model used in all simulations, training data set, example input files to run DeepMD (with LAMMPS), and data tables summarizing the results obtained from the simulations.

machine learning models↗