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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 1,549 records · Page 86
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Bioalcohol production from acidogenic products via a two-step process: A case study of butyric acid to butanol

This article presents the full study (lab-scale experimental study and large-scale techno-economic analysis) results of a two-step catalytic process for the conversion of organic waste–derived butyric acid to butanol. Butanol from biomass resources like organic waste promise to become an attractive and sustainable fuel and industrial precursor due to an increase in greenhouse gas content in the atmosphere. Therefore, research in this field is important for energy applications and reduction in greenhouse gas emissions. In this regard, a two-step process was applied in this study to produce butanol from butyric acid that can potentially be derived from organic waste. The two-step process consists of the (1) esterification of butyric acid to methyl butyrate and (2) hydrogenolysis of this methyl butyrate to butanol. The first reaction, esterification of butyric acid, was optimized using carbon-based catalysts. The production of butanol from methyl butyrate via hydrogenolysis was investigated using bimetallic Pt–Co catalysts. The hydrogenolysis of methyl butyrate on these catalysts under optimal conditions of 250 °C, 5 MPa H 2 , and a feed/catalyst weight ratio of 11.2 led to 54.1% selectivity toward 1-butanol. Based on the experimental results, an integrated process simulation model was developed to determine the economic potential of the two-step production of butanol from butyric acid. Using this model, the techno-economic feasibility of the two-step process was analyzed. Here, the minimum selling price (MSP) of 1-butanol produced from butyric acid using this process was US dollars 3.388 per gallon of gasoline equivalent (GGE). This MSP is in the range of recent biofuel market prices of US dollars 2.03/GGE to US dollars 3.83/GGE.

09 BIOMASS FUELS↗
DOE OSTI2019

Friction stir processing of dual certified 304/304L austenitic stainless steel for improved cavitation erosion resistance

Cavitation phenomenon is known to be prevalent in equipment in hydraulic environments. Understanding cavitation and improving the cavitation resistance of commonly used materials is of interest for both scientific and economic reasons. In this study, friction stir processing was employed to modify commercial dual certified AISI 304/304L austenitic stainless steel plates. The cavitation erosion resistance of the processed plates was evaluated and compared to that of the unprocessed steel. A temperature control algorithm was employed to maintain a target tool temperature during the processing. The cross sections of the processed nuggets were evaluated using optical microscopy, scanning electron microscopy and Vickers hardness testing. Cavitation testing was performed conforming to ASTM G134 on specimens cut out of the nuggets of the commercially unprocessed and the processed 304/304L steel. The tool temperature was found to affect the microstructure and the cavitation performance. Friction stir processed steel showed 3 times better cavitation resistance than the unprocessed 304/304L. Surface cavitation patterns and cavitation rates were characterized and the mechanisms of material removal were discussed.

Jiang, Xiujuan↗
DOE OSTI2018

Weighted gene co-expression network analysis reveals potential genes involved in early metamorphosis process in sea cucumber Apostichopus japonicus

Highlights: • Gene expression profiles of sea cucumber were systematically examined. • Gene co-expression modules of sea cucumber were analyzed for the first time. • The module MEdarkmagenta is highly related to the early metamorphosis process. • Genes associated with the early metamorphosis process were identified. Sea cucumbers, one main class of Echinoderms, have a very fast and drastic metamorphosis process during their development. However, the molecular basis under this process remains largely unknown. Here we systematically examined the gene expression profiles of Japanese common sea cucumber (Apostichopus japonicus) for the first time by RNA sequencing across 16 developmental time points from fertilized egg to juvenile stage. Based on the weighted gene co-expression network analysis (WGCNA), we identified 21 modules. Among them, MEdarkmagenta was highly expressed and correlated with the early metamorphosis process from late auricularia to doliolaria larva. Furthermore, gene enrichment and differentially expressed gene analysis identified several genes in the module that may play key roles in the metamorphosis process. Our results not only provide a molecular basis for experimentally studying the development and morphological complexity of sea cucumber, but also lay a foundation for improving its emergence rate.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Increasing ethanol yield through fiber conversion in corn dry grind process

Conversion of corn fiber to ethanol in the dry grind process could increase ethanol yields, reduce downstream processing costs and improve overall process profitability. In this work, we investigate the in-situ conversion of corn fiber into ethanol (cellulase addition during simultaneous saccharification and fermentation) during dry grind process. Addition of 30 FPU/g fiber cellulase resulted in 4.6% increase in ethanol yield compared to the conventional process. Use of excess cellulase (120 FPU/g fiber) resulted in incomplete fermentation and lower ethanol yield compared to the conventional process. Lastly, multiple factors including high concentrations of ethanol and phenolic compounds were responsible for yeast stress and incomplete fermentation in excess cellulase experiments.

09 BIOMASS FUELS↗
DOE OSTI2022

Model quantification of the effect of coproducts and refinery co-hydrotreating on the economics and greenhouse gas emissions of a conceptual biomass catalytic fast pyrolysis process

Here we present model results for a scaled-up conceptual process informed by bench scale biomass catalytic fast pyrolysis (CFP) and hydrotreating experimental data. This process uses a Pt/TiO 2 catalyst during CFP, which produces a partially deoxygenated organic biocrude intermediate that is then hydroprocessed to a hydrocarbon fuel blendstock; the catalyst also enables high yields of acetone and methyl-ethyl-ketone (MEK) coproducts. Two options for hydroprocessing were modeled: (A) co-hydrotreating at a petroleum refinery using hydrogen sourced from steam reforming of natural gas and (B) standalone hydrotreating at a biorefinery using hydrogen sourced from CFP off gases. The results revealed that Case A was economically advantageous with a modeled minimum fuel selling price (MFSP) of $\$$2.83/GGE or gallon gasoline equivalent (in 2016 US dollars), while the additional cost of standalone hydrotreating facilities in Case B increased the MFSP to $3.13/GGE. Conversely, greenhouse gas (GHG) emissions were lower for Case B (3.9 g CO 2 e/MJ) compared to Case A (21.5 g CO 2 e/MJ) due to the use of biogenic (Case B) and fossil-derived (Case A) hydrogen. In a third option (Case C), the requirements for separation and purification of acetone and MEK were removed from the refinery co-processing scenario (Case A) to evaluate the impacts of this process simplification. Elimination of these coproducts increased the MFSP to $3.21/GGE and GHG emissions to 35 g CO 2 e/MJ. These comparisons based on our detailed conceptual models provide economic and sustainability guidance regarding processing choices for future biorefineries. While refinery coprocessing using existing equipment and the production of relatively valuable coproducts can benefit the economics, the hydrogen-source and biogenic coproducts can have significant impacts on the sustainability of the process, and feasibility to use CFP off-gases or other renewable sources for hydrogen production can help lower GHG emissions.

09 BIOMASS FUELS↗
DOE OSTI2023

Pore-scale simulation of multiphase flow and reactive transport processes involved in geologic carbon sequestration

Multiphase flow and reactive transport are two essential physicochemical processes that govern the effectiveness of geological carbon sequestration (GCS). The interaction and feedback among different phases and components during intricate physicochemical processes hold great significance in understanding CO 2 sequestration. Pore-scale simulations can account for multiphase flow and reactive transport processes in porous media and obtain spatial distributions of parameters (density, velocity, concentration, etc.) in the pore space as well as their temporal evolutions. This proves especially valuable considering that experiments can be hindered by constraints in spatial and temporal resolution. The comprehensive insights garnered from pore-scale research can be leveraged for continuum modeling using the representative elementary volume (REV) concept. In this contribution, four sequential mechanisms of CO 2 -brine-rock interaction in three zones delineated by CO 2 saturation are elaborated to elucidate complicated physicochemical processes involved in GCS, which are followed by general descriptions of mathematical equations and pore-scale numerical methods. In addition, as interested and commonly encountered processes, leakage risks during GCS and CO 2 -enhanced oil recovery (CO 2 -EOR) processes are presented. The existing challenges and future directions are discussed for both the performance of the pore-scale models and the current gaps in the field of GCS. Importantly, we expect that this review will prove beneficial for researchers interested in pore-scale simulations, GCS, and related disciplines.

58 GEOSCIENCES↗
DOE OSTI2017

Co-optimization of CO 2 -EOR and Storage Processes under Geological Uncertainty

This paper presents an integrated numerical framework to co-optimize EOR and CO 2 storage performance in the Farnsworth field unit (FWU), Ochiltree County, Texas. The framework includes a field-scale compositional reservoir flow model, an uncertainty quantification model and a neural network optimization process. The reservoir flow model has been constructed based on the field geophysical, geological, and engineering data. A laboratory fluid analysis was tuned to an equation of state and subsequently used to predict the thermodynamic minimum miscible pressure (MMP). A history match of primary and secondary recovery processes was conducted to estimate the reservoir and multiphase flow parameters as the baseline case for analyzing the effect of recycling produced gas, infill drilling and water alternating gas (WAG) cycles on oil recovery and CO 2 storage. A multi-objective optimization model was defined for maximizing both oil recovery and CO 2 storage. The uncertainty quantification model comprising the Latin Hypercube sampling, Monte Carlo simulation, and sensitivity analysis, was used to study the effects of uncertain variables on the defined objective functions. Uncertain variables such as bottom hole injection pressure, WAG cycle, injection and production group rates, and gas-oil ratio among others were selected. The most significant variables were selected as control variables to be used for the optimization process. A neural network optimization algorithm was utilized to optimize the objective function both with and without geological uncertainty. The vertical permeability anisotropy (Kv/Kh) was selected as one of the uncertain parameters in the optimization process. The simulation results were compared to a scenario baseline case that predicted CO 2 storage of 74%. The results showed an improved approach for optimizing oil recovery and CO 2 storage in the FWU. The optimization process predicted more than 94% of CO 2 storage and most importantly about 28% of incremental oil recovery. The sensitivity analysis reduced the number of control variables to decrease computational time. A risk aversion factor was used to represent results at various confidence levels to assist management in the decision-making process. The defined objective functions were proved to be a robust approach to co-optimize oil recovery and CO 2 storage. The Farnsworth CO 2 project will serve as a benchmark for future CO 2 –EOR or CCUS projects in the Anadarko basin or geologically similar basins throughout the world.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

A screening-level life cycle greenhouse gas analysis of CO 2 enhanced oil recovery with CO 2 sourced from the Shute Creek natural gas-processing facility

This life cycle analysis (LCA) evaluates life cycle greenhouse gas (GHG) emissions associated with a system that produces both natural gas and crude oil. Two systems are defined: System 1, which independently produces natural gas and oil, and System 2, which captures carbon dioxide (CO 2 ) from the natural gas-processing plant and utilizes this captured CO 2 for enhanced oil recovery (EOR). The LCA uses customized spreadsheet models with emission factors from peer-reviewed literature and publications of the National Energy Technology Laboratory of the U.S. Department of Energy. The modeling results show that the CO 2 EOR scenario using captured CO 2 produces both natural gas and oil with lower life cycle GHG emissions than alternative systems producing natural gas and oil independently. Sensitivity analyses show that the model results are most sensitive to the fraction of CO 2 captured (or equivalently, the fraction of CO 2 vented) at the natural gas-processing facility and the incremental oil recovery factor and net CO 2 utilization factor of the EOR operations. The input variable driving the relative difference in life cycle GHG emissions between these two systems is the fraction of CO 2 captured at the natural gas-processing facility (i.e., the capture rate). Here, the results of this study highlight the necessity of linking processes in the life cycle modeling, as a change to one process can affect other processes within the coupled energy system comprised of natural gas and oil. In addition, this analysis shows, as prior work has also suggested, that CO 2 EOR using captured anthropogenic CO 2 provides a viable means for offsetting carbon emissions from oil production and combustion via the associated storage of CO 2 that occurs incidentally during this tertiary method of oil recovery.

02 PETROLEUM↗
DOE OSTI2016

Two-sided friction stir riveting by extrusion: A process for joining dissimilar materials

Two-sided friction stir riveting (FSR) by extrusion is an innovative process developed to rapidly, efficiently, and securely join dissimilar materials. This process extends a previously developed one sided friction stir extrusion process to create a strong and robust joint by producing a continuous, rivet-like structure through a preformed hole in one of the materials with a simultaneous, two-sided friction stir spot weld. The two-sided FSR by extrusion process securely joins the dissimilar materials together and effectively locks them in place without the use of any separate materials or fasteners. Lastly, in this paper we demonstrate the process by joining aluminum to steel and illustrate its potential application to automotive and aerospace manufacturing processes.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Nanoscale MnO 2 cathodes for Li-ion batteries: effect of thermal and mechanical processing

This study investigates the effect of thermal and mechanical processing of MnO 2 nanoparticle cathodes on the electrochemical performance, ion intercalation mechanism and structural changes upon cycling. Specifically, thermal processing at different temperatures is utilized to tune the sub-nanoparticle polymorph composition, while mechanical processing (high energy ball-milling) is used to change the particle size and create a better contact between active material and conductive graphite additive. The combination of thermal and mechanical processing is also investigated for possible synergistic effects. The structural changes due to processing suggest that thermal treatment of the MnO 2 nanoparticles at 400 °C forms a high concentration of pyrolusite domains (1 $\times$ 1 channels) leading to improved reversibility of lithium intercalation/de-intercalation and capacity retention. It is also found that ball-milling for a short time (20 min) leads to some amorphization and decrease of the crystallite sizes resulting in improved capacity. The structural changes and ion intercalation mechanism of the pristine and processed electrode materials during cycling are investigated by ex situ synchrotron x-ray diffraction (XRD) and ex situ and in situ x-ray absorption near edge structure (XANES) studies.

25 ENERGY STORAGE↗
DOE OSTI2013

Microstructure characterization of the stir zone of submerged friction stir processed aluminum alloy 2219

Aluminum alloy 2219-T6 was friction stir processed using a novel submerged processing technique to facilitate cooling. Processing was conducted at a constant tool traverse speed of 200 mm/min and spindle rotation speeds in the range from 600 to 800 rpm. The microstructural characteristics of the base metal and processed zone, including grain structure and precipitation behavior, were studied using optical microscopy (OM), scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Microhardness maps were constructed on polished cross sections of as-processed samples. The effect of tool rotation speed on the microstructure and hardness of the stir zone was investigated. The average grain size of the stir zone was much smaller than that of the base metal, but the hardness was also lower due to the formation of equilibrium θ precipitates from the base metal θ′ precipitates. Stir zone hardness was found to decrease with increasing rotation speed (heat input). The effect of processing conditions on strength (hardness) was rationalized based on the competition between grain refinement strengthening and softening due to precipitate overaging. - Highlights: • SZ grain size (∼ 1 μm) is reduced by over one order of magnitude relative to the BM. • Hardness in the SZ is lower than that of the precipitation strengthened BM. • Metastable θ′ in the base metal transforms to equilibrium θ in the stir zone. • Softening in the SZ results from a decrease of precipitation strengthening.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Effects of rolling processes on ridging generation of ferritic stainless steel

Highlights: • The effects of microstructural refinement and texture on ridging are analysed. • Optimal reduction during cold rolling benefits the enhancement of ridging resistance. • A Steckel-mill rolling method is proposed to improve ridging resistance of FSS 430. • 30% of ridging height reduction can be achieved with proposed rolling method. - Abstract: In order to reduce the ridging generation of ferritic stainless steel (FSS) during forming process, the crystallographic texture of the FSS was modified by optimisation of both rolling and annealing processes. A systematic study was carried out to improve the ridging resistance of the FSS by investigating the sequential changes in microstructure and texture during different rolling and annealing processes. The results show that the surface roughness of the final sheet strained by 20% along the rolling direction is decreased by 20% to 30% using Steckel-mill rolling compared to traditional tandem rolling. A direct correlation is found between the ridging resistance of the FSS and the rolling routines. It has been observed that an optimal reduction value during cold rolling process is critical to the microstructural refinement and surface quality improvement of the FSS. Reduction of the fraction of {001} <110> component by optimisation of the rolling processes is found to be effective in reducing the ridging height of the FSS during the formation process.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Effects of processing defects on the dynamic tensile mechanical behavior of laser-solid-formed Ti-6Al-4 V

Highlights: • Tensile tests are conducted under coupled effects of strain rate and temperature. • Defects act as crack initiation and propagation sites for dynamic tensile fracture. • Dynamic tension-compression asymmetry is due to different behaviors of defects. • Different deformation of defects results in tensile mechanical anisotropy. • Mechanical anisotropy and asymmetry are sensitive to strain rate and temperature. - Abstract: The initial processing defects, i.e. voids, lack-of-fusion pores and inclusions, are the inevitable and unique microstructural features in the Ti-6Al-4 V (Ti64) alloy manufactured by laser solid forming (LSF). This study was to gain insight into the influences of these processing defects on the tensile thermomechanical response of the material under various strain rates of 0.001/s, 500/s, 1000/s and 3000/s, and under a wide range of temperatures from 298 K to 1273 K. The drastic effects of processing defects on the flow stress were founded to be susceptible to tensile loading and increase with the increasing strain rate. The SEM analysis was carried out to further understand the effect of initial processing defects on the dynamic fracture behavior. These processing defects, such as voids and lack-of-fusion pores, are the most vulnerable position to release impact energy instantaneously and then evolve into the initiation site and propagation path for dynamic tensile crack. The tensile crack under high strain rate and high temperature propagates through the columnar prior-β grain boundary α colony. It was analyzed that the typical tension-compression asymmetry in strength is positively associated with the strain rate in the Ti64 alloy by LSF. Such asymmetry is due to the differences in the deformation mechanism of processing defects and in the activated slip system under tensile and compressive loading. Additionally, the anisotropy of the mechanical property was discussed by examining the positive strain rate effects in two orientations (i.e., perpendicular and parallel to the crystal growth direction). This anisotropy is caused by different mechanical behaviors of lack-of-fusion defects and β grain boundary α colony in different orientations.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Development of microstructure and texture during single and multiple pass friction stir processing of a strain hardenable aluminium alloy

Highlights: • Development of microstructure and texture during single and multiple pass FSP of a strain hardenable aluminium alloy • Strain induced boundary migration (SIBM) is the dominant nucleation mechanism for recrystallization • Weak crystallographic texture development influenced by SIBM with the relative dominance of shear texture components • Stable microstructure and texture development after multiple pass FSP • FSP is a promising method for the secondary processing of strain hardenable aluminium alloys - Abstract: In the present study, microstructure and texture development during single and multiple pass friction stir processing (FSP) of a strain hardenable wrought AlMg alloy (AA5086) was investigated. Subtle differences were observed while comparing with heat treatable alloys in the nucleation mechanism of the recrystallized microstructure observed in the nugget zone. Strain induced boundary migration was the dominant mechanism of microstructure evolution in the alloy, which influenced the crystallographic texture development by weakening it. Micro-texture measurements reveal variations in the crystallographic texture along the thickness of the sample. Recrystallization texture components were observed in the nugget zone indicative of a pronounced static recrystallization in the alloy as compared to the heat treatable alloys. Bulk texture measurements within the nugget zone of the optimally processed sample reveal a relatively dominant C component of shear texture. Average grain size in the nugget zone remained the same and the bulk crystallographic texture components were retained during multiple-pass FSP. The lower strain energies involved and the enhanced recovery processes due to the high temperature materials processing of the alloy during FSP resulted in a stable microstructure and texture. In summary, FSP could be promoted as a competent and suitable secondary processing technique for the bulk production of ultra-fine-grained materials in strain hardenable aluminium alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Relationship between microstructure and mechanical properties of M50 ultra-high strength steel via quenching-partitioning-tempering process

Highlights: • The impact energy of M50 steels treated by QPT process increases by 35–93% than QT. • Cracks distribution inside impact fracture specimens is studied by 3D X-ray tomography. • The work indicates that QPT process can be applied to high-C steel with little Si. Novel quenching-partitioning-tempering (Q-P-T) and traditional quenching-tempering (Q-T) processes are conducted for M50 ultra-high strength steel. An excellent combination of strength and toughness is obtained via the Q-P-T process. The highest impact absorption energy of the Q-P-T specimen increases by 93% compared to the Q-T specimen. However, the yield and ultimate tensile strength of Q-P-T specimens are almost the same as those of Q-T specimens. Microstructure analysis indicates that the maximum fraction of retained austenite in the Q-P-T specimen is 7.5%, which is much higher than that in the Q-T (2.0%) specimen. Meanwhile, more fine cracks appear in the fracture Q-P-T specimen. The precipitation of fine and diffuse ω phase, Fe{sub 3}C and Cr{sub 23}C{sub 6} is observed during the partitioning process. The present work also reveals that the Q-P-T/Q-P process can be applied to high‑carbon steel with little Si or Al.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Microstructural and micro-mechanical analysis of 14YWT nanostructured Ferritic alloy after varying thermo-mechanical processing paths into tubing

Microstructural analyses and micro-pillar compression were conducted on 14YWT nanostructured ferritic alloy (NFA) to compare different processing pathways: hydrostatic extrusion and Pilger processing with varying annealing temperatures into thin walled tubing, and after hot extrusion and cross-rolling into a plate. Hydrostatic extrusion at 815 °C resulted in the smallest grain sizes and highest yield strength of 1.20 GPa. Pilger processing with annealing at 800 °C had fine grained regions and bands of coarse grains, leading to a large variation in yield strength of 0.9–1.40 GPa. Higher annealing temperatures of 1200 °C after pilger processing significantly increased the grain size and lowered the yield strength to 1.01 GPa. These tubes showed a stronger (111) crystallographic texture in the normal direction and elongated grains in the extrusion direction. Characterization of the nano-oxides using TEM reveals more numerous, smaller oxides present in tubing processed at lower temperatures. Overall, this work shows NFA tubing after hydrostatic extrusion and pilger processing can lead to fine grained microstructures and texturing leading to higher yield strengths at lower annealing temperatures (e.g. 800 °C).

14YWT↗
DOE OSTI2022

Multi phenomena melt pool sensor data fusion for enhanced process monitoring of laser powder bed fusion additive manufacturing

Finding actionable trends in laser-based metal additive manufacturing process monitoring data is challenging owing to the diversity and complexity of the underlying physical interactions. A single monitoring solution that captures a particular process phenomenon, such as a photodiode that tracks melt pool intensity, is not alone capable of evaluating process stability or detecting flaw formation with sufficient precision for routine application in industry. In this work, to improve flaw detection performance, we adopted a data fusion approach that captures multiple process phenomena. To demonstrate this, we acquired data from laser powder bed fusion (LPBF) builds of cylindrical specimens produced with different laser spot sizes, emulating defocusing due to process faults such as thermal lensing. The resulting specimens had porosity of varying types and severity, quantified by post-build non-destructive X-ray computed tomography, Archimedes density measurements, and destructive metallographic characterization. During the build, the melt pool state was monitored with two coaxial high-speed video cameras and a temperature field imaging system. Physically intuitive low-level melt pool signatures, such as melt pool temperature, shape and size, and spatter intensity were extracted from this high-dimensional, image-based sensor data. These process signatures were subsequently used as input features in relatively simple machine learning models, such as a support vector machine, which were trained to detect laser defocusing, and in addition, predict porosity type and severity. The results show that the data fusion approach significantly enhanced system performance by reducing the overall false positive rate from ~ 0.1 to ~ 0.001 without sacrificing the true positive rate (~0.90). These results were at par with a black-box, deep machine learning approach (convolutional neural network).

36 MATERIALS SCIENCE↗
DOE OSTI2024

Navigating high-dimensional process-structure–property relations in nanocrystalline Pt-Au alloys with machine learning

For decades, materials scientists have relied on the process-structure–property paradigm to guide investigations into material behaviors. Traditional studies often examine a limited number of process-structure–property variables, striving to elucidate mechanisms governing material response. However, this approach is time consuming and can limit exploration, as well as the discovery of process-structure–property relations in novel materials. In this paper, we combined combinatorial sputter deposition and multi-modal high-throughput materials characterization with feedforward neural networks to establish high-dimensional process-structure–property relations in Pt-Au alloys, yielding nanocrystalline alloys with high hardness and low resistivity relevant to electrical contact switch applications. We mapped three indicators of process conditions (composition and two atomic deposition characteristics) onto four indicators of material structure (X-ray diffraction, film thickness, density, and surface roughness) and two indicators of material properties (hardness and resistivity), resulting in 784 unique combinations evaluated over a 13-dimensional space. The neural networks predicted Pt-Au alloys with 18–24 at.% Au, when deposited at specific conditions, to have a nanoindentation hardness up to 7.2 GPa. This high hardness value, comparable to some steels, represents a 3-fold improvement in hardness over “hard gold”, a commonly used electrical contact alloy, while maintaining requisite electrical conductivity. The neural network models provide an avenue to identify expected process windows capable of maximizing material performance.

Electrical contact materials↗