Search NASA⌕ Search

SEARCH · Search NASA

Results for “surface optimization”

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 109 records · Page 6

Advancing Multiscale Simulation of Plasma-Surface Interfaces

We report the development of an atomistic-informed, surface-state-dependent predictive model for particle exchange in a carbon-tungsten plasma-surface interface. The predictive model uses machine learning (ML) techniques to learn the energy and angular distributions for particle exchange and rate functions for surface state evolution from molecular dynamics simulations of cumulative bombardment of tungsten by energetic carbon ions. Each predictive component is sensitive to the energy and trajectory of incident plasma species and the surface state. The surface state is represented by a set of surface state descriptors, which were derived from the atomistic surface state for each independent carbon bombardment event. These descriptors are representative of the composition and degree of amorphization of the outermost angstrom of surface material and were chosen to optimize predictive performance for particle exchange at the interface. The distributions for particle exchange (reflection/sputtering) are demonstrated to vary with each surface state descriptor, motivating the development of surface-state-dependent particle exchange models for plasma simulations. The performance of various ML methods was compared, including polynomial quantile regression, artificial neural networks, k-nearest neighbors, and random forest algorithms, with polynomial regression performing the best for interpolation and extrapolation of learned relationships. In addition to the particle exchange model, a neutral network was developed and used to identify data sufficiency throughout surface descriptor space, which will enable real-time feedback during future data production to ensure data is produced where it is most needed, and we provide commentary on improvements to the data production workflow for future endeavors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Harnessing Quantum Information Science for Enhancing Sensors in Harsh Fossil Energy Environments

The main goals of this project are to utilize real-time quantum dynamics simulations and quantum optimal control algorithms to (1) harness near-surface nitrogen vacancy (NV) centers to detect chemical analytes in harsh fossil energy environments, and (2) design optimally constructed electromagnetic fields for initializing these near-surface NV center spins for efficient sensor performance and detectivity.

20 FOSSIL-FUELED POWER PLANTS↗

Global stellarator coil optimization with quadratic constraints and objectives

Most present stellarator designs are produced by costly two-stage optimization: the first for an optimized equilibrium, and the second for a coil design reproducing its magnetic configuration. Few proxies for coil complexity and forces exist at the equilibrium stage. Rapid initial state finding for both stages is a topic of active research. Most present convex coil optimization codes use the least square winding surface method by Merkel (NESCOIL), with recent improvements in conditioning, regularization, sparsity, and physics objectives. While elegant, the method is limited to modeling the norms of linear functions in coil current. We present QUADCOIL, a global coil optimization method that targets combinations of linear and quadratic functions of the current. It can directly constrain and/or minimize a wide range of physics objectives unavailable in NESCOIL and REGCOIL, including the Lorentz force, magnetic energy, curvature, field-current alignment, and the maximum density of a dipole array. QUADCOIL requires no initial guess and runs nearly $10$ 2 x faster than filament optimization. Integrating it in the equilibrium optimization stage can potentially exclude equilibria with difficult-to-design coils, without significantly increasing the computation time per iteration. QUADCOIL finds the exact, global minimum in a large parameter space when possible, and otherwise finds a well-performing approximate global minimum. It supports most regularization techniques developed for NESCOIL and REGCOIL. We demonstrate QUADCOIL’s effectiveness in coil topology control, minimizing non-convex penalties, and predicting filament coil complexity with three numerical examples.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Glancing Angle Deposition in Gas Sensing: Bridging Morphological Innovations and Sensor Performances

Glancing Angle Deposition (GLAD) has emerged as a versatile and powerful nanofabrication technique for developing next-generation gas sensors by enabling precise control over nanostructure geometry, porosity, and material composition. Through dynamic substrate tilting and rotation, GLAD facilitates the fabrication of highly porous, anisotropic nanostructures, such as aligned, tilted, zigzag, helical, and multilayered nanorods, with tunable surface area and diffusion pathways optimized for gas detection. This review provides a comprehensive synthesis of recent advances in GLAD-based gas sensor design, focusing on how structural engineering and material integration converge to enhance sensor performance. Key materials strategies include the construction of heterojunctions and core–shell architectures, controlled doping, and nanoparticle decoration using noble metals or metal oxides to amplify charge transfer, catalytic activity, and redox responsiveness. GLAD-fabricated nanostructures have been effectively deployed across multiple gas sensing modalities, including resistive, capacitive, piezoelectric, and optical platforms, where their high aspect ratios, tailored porosity, and defect-rich surfaces facilitate enhanced gas adsorption kinetics and efficient signal transduction. These devices exhibit high sensitivity and selectivity toward a range of analytes, including NO2, CO, H2S, and volatile organic compounds (VOCs), with detection limits often reaching the parts-per-billion level. Emerging innovations, such as photo-assisted sensing and integration with artificial intelligence for data analysis and pattern recognition, further extend the capabilities of GLAD-based systems for multifunctional, real-time, and adaptive sensing. Finally, current challenges and future research directions are discussed, emphasizing the promise of GLAD as a scalable platform for next-generation gas sensing technologies.

Chemistry↗

Improved Representations of Longwave Surface Emissivity to Reduce Surface and Atmospheric Heating Biases in Earth System Models

Abstract Many Earth system models (ESMs) approximate surface emissivity as a broadband constant. This approximation reduces the computational burden, yet omits the spectral structure of emissivity and atmospheric absorption. Neglecting spectral variation in surface emission introduces biases in longwave (LW) atmospheric fluxes and heating. Biases are strongest over surfaces with strongly varying emissivity and minimal atmospheric opacity. We examine these biases over water, ice, and snow surfaces. We partition spectral emissivity into the 16 spectral bands utilized by a single‐column atmospheric radiative transfer model (RRTMG_LW) commonly used in ESMs. We quantify flux and heating biases introduced by broadband assumptions relative to the spectrally resolved case for standard atmospheric profiles over each surface type. Current assumptions tend to overestimate upwelling surface fluxes; for example, the greybody assumption overestimates flux by 1.6 W/m 2 (0.52%) at the bottom of a mid‐latitude winter atmosphere over ice, and by 2.33 (1.0%) at the top of atmosphere. The blackbody assumption tends to artificially cool Earth's surface, stabilizing the lower troposphere. Interestingly, the optimal broadband emissivity can deviate from the Planck‐weighted mean by up to 3% depending on surface type and atmospheric profile. We investigate bias sensitivity to surface temperature, cloud water path, and atmospheric water vapor. Bias is most sensitive to water vapor content, and least sensitive to cloud water path. Lastly, we show that a modified greybody method with updated broadband values can reduce total surface flux bias up to 1.69 , comparable to a five‐band approach and at a fraction of the computational cost.

Manzo, L. [Department of Earth System Science Univ↗

Optimized Tandem Catalyst Patterning for CO 2 Reduction Flow Reactors

Tandem catalysis involves two or more catalysts arranged in proximity within a single reaction vessel, with the aim of synergistically aligning the catalysts’ reaction pathways to maximize overall system performance. This study presents a proof of concept showing the integration of continuum transport modeling with design optimization in a simplified two-dimensional flow reactor setup for electrochemical CO 2 reduction. Ag catalysts provide the CO 2 ⟶ CO reaction capability, and Cu catalysts provide the CO ⟶ high-value products reaction capability. Given a set of input parameters, the optimization algorithm uses adjoint methods to modify the Ag/Cu surface patterning in order to maximize the current density toward high-value products, such as ethylene. The optimized designs yield significant performance enhancement especially at more negative applied voltages (i.e., stronger surface reactions) and for larger numbers of patterning sections. For an applied voltage of −1.7 V vs. SHE, the 12-section optimized design increases the current density toward ethylene by up to 65% compared to the unoptimized 2-section design. For the optimized cases, observed differences in the production and consumption of CO (the key intermediate species) and minimized zones of low CO reactant surface concentration on Cu sections explain the improved reactor performance.

CO2 reduction↗

CO (2) Electroreduction on Borated Copper Surfaces: Boron Active Sites, Not Copper

Boron-doped copper has recently emerged as an active and stable catalyst for the electrochemical reduction of CO 2 to value-added C 2 products. Here, in this work, we develop a realistic model of CO electroreduction on surface borides of copper under operational conditions, taking into account the effects of electrode potential, electrolyte environment, and pH. We study the possible reconstruction of the electrocatalyst surface using grand canonical DFT and global optimization to obtain a potential-dependent grand canonical ensemble description of metastable, hydrogen-covered catalyst surfaces. Two key surface configurations, low H coverage (LC, −0.6 V SHE ) and high H coverage (HC, −0.8 V SHE ), dominate this ensemble, with the former being kinetically persistent and C 2 selective under strongly reducing conditions. Nonmetallic boron sites on the surface copper boride are found to bind CO more strongly than copper sites, and mechanistic investigation of CO electroreduction pathways presents a surprisingly unconventional case of boron-centered reactivity in contrast to typical copper-centered reactivity. Neighboring boron sites present along boron chains on the surface copper boride are found to facilitate C−C coupling, thereby driving the high C 2 selectivity of this electrocatalyst.

boron-doped copper↗

Multi‐Objective Optimization for Rapid Identification of Novel Compound Metals for Interconnect Applications

Abstract Interconnect materials play the critical role of routing energy and information in integrated circuits. However, established bulk conductors, such as copper, perform poorly when scaled down beyond 10 nm, limiting the scalability of logic devices. Here, a multi‐objective search is developed, combined with first‐principles calculations, to rapidly screen over 15,000 materials and discover new interconnect candidates. This approach simultaneously optimizes the bulk electronic conductivity, surface scattering time, and chemical stability using physically motivated surrogate properties accessible from materials databases. Promising local interconnects are identified that have the potential to outperform ruthenium, the current state‐of‐the‐art post‐Cu material, and also semi‐global interconnects with potentially large skin depths at the GHz operation frequency. The approach is validated on one of the identified candidates, CoPt, using both ab initio and experimental transport studies, showcasing its potential to supplant Ru and Cu for future local interconnects.

Chemistry↗

Synergizing superwetting and architected electrodes for high-rate water splitting

Water splitting is one of the most promising technologies for generating green hydrogen. To meet industrial demand, it is essential to boost the operation current density to industrial levels, typically in the hundreds of mA cm -2 . However, operating at these high current densities presents significant challenges, with bubble formation being one of the most critical issues. Efficient bubble management is crucial as it directly impacts the performance and stability of the water splitting process. Superwetting electrodes, which can enhance aerophobicity, are particularly favorable for facilitating bubble detachment and transport. By reducing bubble contact time and minimizing the size of detached bubbles, these electrodes help prevent blockage and maintain high catalytic efficiency. Here, in this review, we aim to provide an overview of recent advancements in tackling bubble-related issues through the design and implementation of superwetting electrodes, including surface modification techniques and structural optimizations. We will also share our insights into the principles and mechanisms behind the design of superwetting electrodes, highlighting the key factors that influence their performance. Our review aims to guide future research directions and provides a solid foundation for developing more efficient and durable superwetting electrodes for high-rate water splitting.

36 MATERIALS SCIENCE↗

Python-EPICS RF Conditioning Automatic Control System at the Spallation Neutron Source

The RF Test Facility (RFTF) at the Spallation Neutron Source (SNS) is used for the conditioning of RF compo-nents such as ceramic vacuum windows and power cou-plers prior to their installation in the H- ion linear accel-erator. This process exposes components to high-power RF fields and thermal cycling to improve performance and remove surface impurities. To automate and optimize this process, a Python-based EPICS control system was developed alongside targeted hardware upgrades. The system enables real-time monitoring and control of RF power levels, temperature, and vacuum pressure. A user-friendly graphical interface was implemented using CS-Studio (Phoebus), allowing operators to adjust parameters and collect data efficiently. The system integrates a High-Power Protection Module (HPM) for interlocks based on vacuum and arc detection, ensuring safe operation. These upgrades have significantly improved the efficiency, accuracy, and safety of RF conditioning at the SNS RFTF. This paper describes the updated RF conditioning sys-tem, highlighting the software and hardware develop-ments and their application in support of the Proton Pow-er Upgrade (PPU) project.

Lee, Sung-Woo [ORNL] (ORCID:000000030915835X)↗

Atomic structure of different surface terminations of polycrystalline ZnPd

The intermetallic compound ZnPd has been found to have desirable characteristics as a catalyst for the steam reforming of methanol. The understanding of the surface structure of ZnPd is important to optimize its catalytic behavior. However, due to the lack of bulk single-crystal samples and the complexity of characterizing surface properties in the available polycrystalline samples using common experimental techniques, all previous surface science studies of this compound have been performed on surface alloy samples formed through thin-film deposition. In this study, we present findings on the chemical and atomic structure of the surfaces of bulk polycrystalline ZnPd studied by a variety of complementary experimental techniques, including scanning tunneling microscopy (STM), x-ray photoelectron spectroscopy (XPS), low energy electron microscopy (LEEM), photoemission electron microscopy (PEEM), and microspot low-energy electron diffraction ( μ -LEED). These experimental techniques, combined with density functional theory (DFT)-based thermodynamic calculations of surface free energy and detachment kinetics at the step edges, confirm that surfaces terminated by atomic layers composed of both Zn and Pd atoms are more stable than those terminated by only Zn or Pd layers. DFT calculations also demonstrate that the primary contribution to the tunneling current arises from Pd atoms, in agreement with the STM results. The formation of intermetallics at surfaces may contribute to the superior catalyst properties of ZnPd over Zn or Pd elemental counterparts. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗

Surface Atomic Rearrangement with High Cation Ordering for Ultra-Stable Single-Crystal Ni-Rich Co-Less Cathode Materials

It is crucial to minimize cobalt content in Ni-rich layered single-crystal cathodes due to their high price and limited availability, yet it will inevitably lead to cation disordering, capacity degradation, and thermal issues. Herein, to overcome the intrinsic trade-off between performance and composition of Ni-rich Co-less single-crystal cathodes, a precursor engineering strategy with an epitaxially grown cobalt enrichment on the surface is innovatively proposed. In contrast to traditional coating modifications with random orientation and rigid surface-bulk boundary, the epitaxially enriched surface cobalt layer on the precursor undergoes rapid interdiffusion with the internal Ni 3+ during the optimized sintering process. This interdiffusion eliminates the surface-bulk boundary, promoting the uniform distribution of cobalt and synergistically addressing the Li/Ni intermixing. Moreover, an enhanced surface Li + diffusion is obtained, thereby suppressing the Li + concentration gradient and intragranular cracks generation. Consequently, the modified LiNi 0.7 Co 0.07 Mn 0.23 O 2 exhibits impressive cycling stability with increased capacity retention in both coin-type half-cells and pouch-type full-cells (91% after 1000 cycles), even under the harsh condition of high-temperature, surpassing the majority of previously reported Ni-rich cathodes. Finally, this work opens new avenues toward the low cost, high energy density, thermal stability, and long cyclic life for Ni-rich Co-less cathodes and sheds light on large-scale commercial production.

25 ENERGY STORAGE↗

Effect of Carbon Support Heat Treatment on the Performance of Ion-Pair High-Temperature PEM Fuel Cells

Heat treatment can significantly alter the physical and chemical properties of carbon supports, thereby influencing the performance of proton exchange membrane (PEM) fuel cells. This study explores how varying carbon heat treatment temperatures—from 1,000 °C to 2,200 °C—affect the structure and performance of platinum-based catalysts in high-temperature PEM fuel cells. Increasing the heat treatment temperature led to a notable decrease in surface area, along with increases in carbon grain size and hydrophobicity. Although the catalyst supported on carbon treated at 1,000 °C exhibited the highest catalyst activity, the MEA using carbon treated at 1,500 °C delivered the best overall fuel cell performance. This is attributed to an optimized balance between hydrophobicity and accessible surface area, which enhances water management and catalyst utilization. These findings underscore the importance of carbon support engineering in improving the efficiency of ion-pair high-temperature PEM fuel cells.

08 HYDROGEN↗

Understanding the Unique Reactivity of Cu for Electrochemical CO 2 Reduction with a 3-Site Model

Cu-based catalysts for the electrochemical reduction of CO 2 and CO exhibit a perplexingly unique reactivity toward multicarbon based products compared to other studied electrocatalysts. Here, in this study, we use insights gained from a recent phenomenological 3-site microkinetic model and grand-canonical density functional theory calculations to clarify the importance of an underemphasized aspect critical to Cu’s unique reactivity: a population of so-called “reservoir” sites. Using model Cu surface motifs, we discuss how these types can be represented by undercoordinated structural defects like step edges and grain boundaries which form a network of highly anisotropic migration channels. These pathways are found to be amenable for feeding *CO over time to reactive sites like Cu adatoms more active toward C–C coupling. These results highlight an often overlooked aspect of catalyst optimization: reservoir site engineering, which exploits surface mobility and presents an equally important avenue for electrocatalyst engineering oversimply maximizing active site densities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Designing Antifouling and Antimicrobial Interfaces: Structural Characterization using CryoEM, Automated Microscopy, and AI Image Segmentation

The design of functionalized surfaces for interactions with biological systems is critical across sectors such as healthcare, energy, and agriculture. Tailoring materials for specific applications, such as antifouling and antimicrobial surfaces, demands a comprehensive understanding of topology and chemistry across multiple length and time scales on both biological and materials systems. This work presents the development and characterization of nanostructured surfaces with controlled topographies and chemistries that enhance bacterial membrane disruption, reduce biofilm formation, and improve antimicrobial and antifouling capabilities. Two specific use cases will be presented - the use of cellulose nanocrystals (CNCs) for bacterial growth inhibition and the development of antifouling surfaces to prevent protein and bacterial adsorption [1-4]. By leveraging large language models (LLMs) for image segmentation and training [5], we enable automated analysis of terabyte-scale cryogenic electron microscopy (cryoEM) datasets. This analysis provides statistical insights into the biotic/abiotic interface and facilitates automated electron microscopy experiments to mitigate time and dose. The integration of cryogenic electron tomography (cryoET) and cryogenic focused ion beam (cryoFIB) milling enables high-resolution, near-native-state imaging and 3D reconstructions of bio/material interfaces [6]. Orthogonal characterization techniques and computational modeling further enhances our understanding, offering a robust platform for the design and optimization of next-generation functional surfaces [7].

Williams, Alexis [ORNL] (ORCID:0000000252835822)↗

Epitaxial 2D Magnet and Topological Insulator Heterostructures

I will discuss our latest advances on the epitaxial growth of 2D van der Waals (vdW) magnets and their integration with topological insulators (TI). This work is motivated by the realization of topological phases such as the quantum anomalous Hall effect and highly efficient spin-orbit torque produced by TIs. Our initial studies of MnSe2 growth on Bi2Se3 showed a tendency for the interdiffusion of Mn into the Bi2Se3. This ultimately led to the synthesis of MnBi2Se4 (MBS), a new magnetic TI. Interestingly, the vdW phase is not the thermodynamically stable phase and bulk crystals do not exist, so the epitaxial stabilization of MBS creates the opportunity to explore the magnetic and topological properties of this material. We find that MBS is a layered antiferromagnet, similar to MnBi2Te4, but a difference is that the magnetic moments lie in the plane of the film. Angle resolved photoemission experiments show the presence of a topological surface state with Dirac dispersion. For bilayers of 2D magnets and TIs, we have developed FGT films on Bi2Te3. We first optimized FGT by studying its growth on Ge(111) substrates, where we find that kinetic considerations play a major role. Using cross-sectional scanning transmission electron microscopy and scanning tunneling microscopy, we optimize the FGT films to have atomically smooth surfaces and abrupt interfaces with the Ge(111). Subsequently, we have developed the growth of FGT on Bi2Te3 for the integration of 2D magnets with Tis. Interestingly, we observe room temperature ferromagnetism in FGT/Bi2Te3 heterostructures by varying the growth conditions.

Kawakami, Roland↗

Friction surface layer deposition of triple-phase Al 10 Cr 12 Fe 35 Mn 23 Ni 20 high entropy alloy: Process optimization and microstructural evolution

A high-strength Co-free triple-phase Al 10 Cr 12 Fe 35 Mn 23 Ni 20 high-entropy alloy (HEA) was successfully fabricated using Friction Surface Layer Deposition (FSLD), a bulk manufacturing method. Multiple single-layer deposits were produced by varying forging force (F) and traverse speeds (T r ) to optimize the process parameters. The optimized conditions (F = 40 kN & T r = 200 mm/min) were then applied to manufacture a scaled-up multi-layer specimen. The initial microstructure of the HEA consisted of coarse grains of the soft FCC-phase, long columnar dendrites of the hard BCC-phase, and small precipitates of the harder B2-phase within the BCC-dendrites. During FSLD, the FCC-matrix underwent continuous dynamic recrystallization due to high-temperature severe plastic deformation, forming finer equiaxed grains. Simultaneously, the BCC-dendrites fractured into smaller fragments, some of which experienced partial growth and coarsening under applied stress, resulting in an hourglass morphology. In contrast, the small B2-precipitates within the BCC-fragments dissolved during the elevated temperatures of FSLD and reprecipitated as substantially finer precipitates during continuous cooling post-FSLD. Additionally, the orientation relationships between the FCC and BCC/B2 phases were completely destroyed by the severe thermoplastic deformation inherent to FSLD. The microstructural refinements led to a substantial improvement in hardness from 177 HV to 283 HV, driven by Hall-Petch strengthening. The increased number of interfaces, including coherent BCC-B2 interfaces, potentially enhances the sink strength and radiation tolerance of the HEA, making it a promising candidate for nuclear applications. In conclusion, this study also highlights FSLD as a versatile technique for achieving tunable properties in HEAs, with detailed schematics illustrating the complex mechanisms of phase transformations during processing.

Additive Manufacturing↗

Unequal {110} Facets: The Potential Role of Intraparticle Heterogeneity and Facet Termination in Photoelectrochemical Activity of Single BiVO 4 Particles

BiVO 4 photoanodes are promising for solar water splitting, with photogenerated electrons and holes preferentially reacting at top {010} and lateral {110} facets, respectively. However, the mechanisms driving this facet-dependent reactivity remain unclear. Here, in this study, we investigate facet-dependent photocurrent and material heterogeneity using correlative scanning photoelectrochemical microscopy (SPCM), electron beam induced current (EBIC) mapping, and mid-IR scattering scanning near-field optical microscopy (s-SNOM). SPCM measurements of 62 BiVO 4 particles confirmed higher photocurrents at lateral {110} facets compared to top {010} facets, but unexpectedly revealed variations in photocurrent among lateral facets within the same particle. Variations in lateral facet surface termination could explain the intraparticle-level reactivity heterogeneity, consistent with theoretical predictions. Nano-FTIR spectroscopy and Raman microspectroscopy indicated significant materials chemistry heterogeneity within individual particles and facets that could be attributed to variations in lattice vibration distortions that enhance the overlap between Bi 6s and O 2p orbitals. The increased orbital overlap is significant as it potentially increases hole mobility in the valence band and potentially explains the lateral facet-dependent charge separation efficiency observed in photocurrent maps. Facet-dependent electrical and EBIC measurements showed no space charge regions at interfacet junctions or metal-BiVO 4 contacts under vacuum, suggesting that photogenerated holes beneath top {010} facets are unlikely to transport to lateral {110} facets to drive water/sulfite oxidation. These findings indicate the potential influence of distinct bulk properties and surface termination chemistries across different particles and facets, highlighting the importance of carefully controlling defects and surface chemistry during sample growth to optimize photocatalytic performance.

BiVO4↗