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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Combining phase-field crystal methods with a Cahn-Hilliard model for binary alloys

Diffusion-induced phase transitions typically change the lattice symmetry of the host material. In battery electrodes, for example, Li ions (diffusing species) are inserted between layers in a crystalline electrode material (host). This diffusion induces lattice distortions and defect formations in the electrode. The structural changes to the lattice symmetry affect the host material’s properties. We propose a 2D theoretical framework that couples a Cahn-Hilliard (CH) model, which describes the composition field of a diffusing species, with a phase-field crystal (PFC) model, which describes the host-material lattice symmetry. We couple the two continuum models via coordinate transformation coefficients. We introduce the transformation coefficients in the PFC method to describe affine lattice deformations. These transformation coefficients are modeled as functions of the composition field. Using this coupled approach, we explore the effects of coarse-grained lattice symmetry and distortions on a diffusion-induced phase transition process. In this paper, we demonstrate the working of the CH-PFC model through three representative examples: First, we describe base cases with hexagonal and square symmetries for two composition fields. Next, we illustrate how the CH-PFC method interpolates lattice symmetry across a diffuse phase boundary. Finally, we compute a Cahn-Hilliard type of diffusion and model the accompanying changes to lattice symmetry during a phase transition process.

25 ENERGY STORAGE↗
DOE OSTI2019

EFFICIENT SURROGATE FOR LOW ENERGY DAMAGE EFFECTS IN POLYATOMIC MATERIALS

We present an efficient surrogate for binary-collision Monte-Carlo (BCMC) calculations in polyatomic materials for low ion energies based on Parkin and Coulter’s net displacement function. Most of BCMC’s execution time is spent on the low energy tail of cascades when recoils’ residual travel distance is small compared to the desired resolution of the damage calculation. We propose to curtail an ions’ random walk if its energy reduces below a threshold Et and locally deposit an estimate of the expected number of defects it creates; the estimate of the number of defects is obtained from Parkin and Coulter’s net displacement functions. We find that results obtained with the BCMC code MyTRIM with and without truncation of the random walks compare well for large energy thresholds Et > 5 keV. For Et = 5 keV larger discrepancies are observed because of large differences between the net displacement function and MyTRIM for very low energy recoils. Future work will investigate and resolve this discrepancy. The energy threshold should be chosen so that ions’ average distance to next nuclear scattering is small compared to the desired resolution. A reduction of execution time of damage cascades by over 90 % is observed for an energy threshold of Et = 5 keV and a 1 MeV Xe-135 primary impinging on UO2. The desired application of this surrogate model are coupled FEM-BCMC calculations with varying compositions where net displacement functions are tabulated by composition. For reducing the number of required net displacement functions, derivatives of the net displacement function with respect to number fraction are computed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

EFFICIENT SURROGATE FOR LOW ENERGY DAMAGE EFFECTS IN POLYATOMIC MATERIALS

We present an efficient surrogate for binary-collision Monte-Carlo (BCMC) calculations in polyatomic materials for low ion energies based on Parkin and Coulter’s net displace- ment function. Most of BCMC’s execution time is spent on the low energy tail of cascades when recoils’ residual travel distance is small compared to the desired resolution of the damage calculation. We propose to curtail an ions’ random walk if its energy reduces below a threshold Et and locally deposit an estimate of the expected number of defects it creates; the estimate of the number of defects is obtained from Parkin and Coulter’s net displacement functions. We find that results obtained with the BCMC code MyTRIM with and without truncation of the random walks compare well for large energy thresholds Et > 5 keV. For Et = 5 keV larger discrepancies are observed because of large differ- ences between the net displacement function and MyTRIM for very low energy recoils. Future work will investigate and resolve this discrepancy. The energy threshold should be chosen so that ions’ average distance to next nuclear scattering is small compared to the desired resolution. A reduction of execution time of damage cascades by over 90 % is observed for an energy threshold of Et = 5 keV and a 1 MeV Xe-135 primary impinging on UO2. The desired application of this surrogate model are coupled FEM-BCMC cal- culations with varying compositions where net displacement functions are tabulated by composition. For reducing the number of required net displacement functions, derivatives of the net displacement function with respect to number fraction are computed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Quantitative proteomic analyses of the response of acidophilic microbial communities to different pH conditions

Extensive genomic characterization of multi-species acid mine drainage microbial consortia combined with laboratory cultivation has enabled the application of quantitative proteomic analyses at the community level. In this study, quantitative proteomic comparisons were used to functionally characterize laboratory-cultivated acidophilic communities sustained in pH 1.45 or 0.85 conditions. The distributions of all proteins identified for individual organisms indicated biases for either high or low pH, and suggests pH-specific niche partitioning for low abundance bacteria and archaea. Although the proteome of the dominant bacterium, Leptospirillum group II, was largely unaffected by pH treatments, analysis of functional categories indicated proteins involved in amino acid and nucleotide metabolism, as well as cell membrane/envelope biogenesis were overrepresented at high pH. Comparison of specific protein abundances indicates higher pH conditions favor Leptospirillum group III, whereas low pH conditions promote the growth of certain archaea. Thus, quantitative proteomic comparisons revealed distinct differences in community composition and metabolic function of individual organisms during different pH treatments. Proteomic analysis revealed other aspects of community function. Different numbers of phage proteins were identified across biological replicates, indicating stochastic spatial heterogeneity of phage outbreaks. Additionally, proteomic data were used to identify a previously unknown genotypic variant of Leptospirillum group II, an indication of selection for a specific Leptospirillum group II population in laboratory communities. Our results confirm the importance of pH and related geochemical factors in fine-tuning acidophilic microbial community structure and function at the species and strain level, and demonstrate the broad utility of proteomics in laboratory community studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Ecosystem heterogeneity and diversity mitigate Amazon forest resilience to frequent extreme droughts

The impact of increases in drought frequency on the Amazon forest's composition, structure and functioning remain uncertain. We used a process- and individual-based ecosystem model (ED2) to quantify the forest's vulnerability to increased drought recurrence. We generated meteorologically realistic, drier-than-observed rainfall scenarios for two Amazon forest sites, Paracou (wetter) and Tapajós (drier), to evaluate the impacts of more frequent droughts on forest biomass, structure and composition. The wet site was insensitive to the tested scenarios, whereas at the dry site biomass declined when average rainfall reduction exceeded 15%, due to high mortality of large-sized evergreen trees. Biomass losses persisted when year-long drought recurrence was shorter than 2–7 yr, depending upon soil texture and leaf phenology. From the site-level scenario results, we developed regionally applicable metrics to quantify the Amazon forest's climatological proximity to rainfall regimes likely to cause biomass loss >20% in 50 yr according to ED2 predictions. Nearly 25% (1.8 million km 2 ) of the Amazon forests could experience frequent droughts and biomass loss if mean annual rainfall or interannual variability changed by 2σ. At least 10% of the high-emission climate projections (CMIP5/RCP8.5 models) predict critically dry regimes over 25% of the Amazon forest area by 2100.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Understanding Twinning and Deformation in High Entropy Alloys

A combination of high strength and high ductility has been observed in multi-principal element alloys due to twin formation attributed to low stacking fault energy (SFE). In the pursuit of low SFE alloys, a key bottleneck is the lack of understanding of the composition–SFE cor- relations that would guide tailoring SFE via alloy composition. Using density functional theory (DFT), we show that dopant radius, which have been postulated as a key descriptor for SFE in dilute alloys, does not fully explain SFE trends across different host metals. Instead, charge density is a much more central descriptor. It allows us to (1) explain contrasting SFE trends in Ni and Cu host metals due to various dopants in dilute concentrations, (2) explain the large SFE variations observed in the literature even within a given alloy composition due to the nearest neighbor environments in “model” concentrated alloys, and (3) develop a machine learning model that can be used to predict SFEs in multi-elemental alloys. This model opens a possibility to use charge density as a descriptor for predicting SFE in alloys. Furthermore, a descriptor-less machine learning (ML) model based only on charge density images extracted from density functional theory (DFT) is developed to predict stacking fault energies (SFE) in concentrated alloys. The model is based on convolutional neural networks (CNNs) as one of the promising ML techniques for dealing with complex images and data. Identification of correct descriptors is a key bottleneck to develop ML models for predicting materials properties. Often, in most ML models, textbook physical descriptors such as atomic radius, valence charge and electronegativity are used as descriptors which have limitations because these properties change in concentrated alloys when multiple elements are mixed to form a solid solution. We illustrate that, within the scope of DFT, the search for descriptors can be circumvented by electronic charge density, which is the backbone of the Kohn-Sham DFT and describes the system completely. The performance of our model is demonstrated by predicting SFE of concentrated alloys with an RMSE and R2 of 6.18 mJ/m2 and 0.87, respectively, validating the accuracy of the proposed approach.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Polymer composites for fused filament fabrication and methods of making the same

Disclosed are compositions of a fused filament fabrication (FFF) composite filament having embedded functional materials in a thermoplastic matrix. Methods of making the composite filaments are also disclosed. In one example, a FFF composite filament incorporates a MOF, in an amount greater than 10% by mass, dispersed in a matrix polymer. One example of a method of synthesizing FFF composite filaments involves mixing a suspension that has a MOF with a matrix polymer solution to yield a polymer-MOF mixture. The mixture is cast and dried into a solid composite material, which is formed a FFF composite filament having the MOF in an amount greater than 10% by mass.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Minority carrier lifetime and photoluminescence of mid-wave infrared InAsSbBi

Time-resolved photoluminescence measurements are reported for InAsSbBi alloys grown by molecular beam epitaxy with Bi mole fractions ranging from 0 to 0.8%, yielding minority carrier lifetimes on the order of hundreds of nanoseconds. The minority carrier lifetimes extracted from the time-resolved photoluminescence measurements are comparable to those of lattice-matched InAsSb grown at the same respective temperatures. Nomarski imaging shows that smooth, droplet-free surface morphologies are obtained in 1 μm thick InAsSbBi epilayers grown at temperatures between 360 and 380 °C. The alloy composition-dependent bandgap energies for the InAsSbBi samples are determined from temperature-dependent steady-state photoluminescence measurements and compared with the tetragonal distortion measured by x-ray diffraction to determine the Sb and Bi mole fractions of each sample. The minority carrier lifetime and the achievable extension of the InAsSb(Bi) cut-off wavelength are analyzed as functions of alloy composition and compared with the performance of InAsSb layers with similar growth parameters.

Petluru, Priyanka (ORCID:0000000257154284)↗
DOE OSTI2015

Optical constants of Cu(In, Ga)Se{sub 2} for arbitrary Cu and Ga compositions

The optical constants of Cu(In, Ga)Se{sub 2} (CIGS)-based polycrystalline layers with different Cu and Ga compositions are parameterized completely up to a photon energy of 6.5 eV assuming several Tauc-Lorentz transition peaks. Based on the modeled optical constants, we establish the calculation procedure for the CIGS optical constants in a two-dimensional compositional space of (Cu, Ga) by taking the composition-induced shift of the critical point energies into account. In particular, we find that the variation of the CIGS optical constants with the Cu composition can be modeled quite simply by a spectral-averaging method in which the dielectric function of the target Cu composition is estimated as a weighted average of the dielectric functions with higher and lower Cu compositions. To express the effect of the Ga composition, on the other hand, an energy shift model reported earlier is adopted. Our model is appropriate for a wide variety of CIGS-based materials having different Cu and Ga compositions, although the modeling error increases slightly at lower Cu compositions [Cu/(In + Ga) < 0.69]. From our model, the dielectric function, refractive index, extinction coefficient, and absorption coefficient for the arbitrary CIGS composition can readily be obtained. The optical database developed in this study is applied further for spectroscopic ellipsometry analyses of CIGS layers fabricated by single and multi-stage coevaporation processes. We demonstrate that the compositional and structural characterizations of the CIGS-based layers can be performed from established analysis methods.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Molecular dynamics simulation for arrangement of nickel atoms filled in carbon nanotubes

Carbon Nanotubes (CNTs) filled with metals can be used in capacitors, sensors, rechargeable batteries, and so on. Atomic arrangement of the metals has an important role in the function of the composites. The tips of CNTs were opened, and then nickel was filled by means of hydrothermal oxidation/ultrasonic vibration method. The tests of TEM, HREM, and EDX (energy-dispersive X-ray spectroscopy) analysis showed that Ni was filled in CNTs successfully. The atomic arrangement of nickel filled into single wall carbon nanotubes was investigated by molecular dynamics simulation. The radial distribution function and bond orientation order were established to analyze the atomic arrangement of nickel filled in carbon nanotubes during the cooling process. The results show that nickel atoms became in order gradually and preferably crystallized on the inner wall of carbon nanotubes when the temperature decreased from 1600 K. After it cooled to 100 K, the arrangement of nickel atoms in outermost circle was regular and dense, but there were many defects far from the wall of CNTs. According to the calculation of bond orientation order parameters Q{sub 6} and its visualization, the structure of nickel is Face-centered cube (f.c.c). (1,1,1){sub Ni} was close on the inner surface of carbon nanotubes. Radial direction of CNTs was [1,1,1] crystal orientation. Axial direction of CNTs, namely, filling direction, was [1{sup ¯}, 1{sup ¯},2] crystal orientation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Compositional dependence of optical band gap and refractive index in lead and bismuth borate glasses

Highlights: • Refractive indices increase with increasing PbO/Bi{sub 2}O{sub 3} content. • Optical band gap arises due to direct forbidden transition. • Optical band gaps decrease with increasing PbO/Bi{sub 2}O{sub 3} content. • New empirical relation between the optical band gap and the refractive index. - Abstract: We prepared a series of lead and bismuth borate glasses by varying PbO/Bi{sub 2}O{sub 3} content and studied refractive index and optical band gap as a function of glass composition. Refractive indices were measured very accurately using a Brewster’s angle set up while the optical band gaps were determined by analyzing the optical absorption edge using the Mott–Davis model. Using the Lorentz–Lorentz method and the effective medium theory, we calculated the refractive indices and then compared them with the measured values. Bismuth borate glasses show better agreement between the calculated values of the refractive index and experimental values. We used a differential method based on Mott–Davis model to obtain the type of transition and optical band gap (E{sub opt}) which in turn was compared with the value of E{sub opt} obtained using the extinction coefficient. Our analysis shows that in both lead and bismuth borate glasses, the optical band gap arises due to direct forbidden transition. With increasing PbO/Bi{sub 2}O{sub 3} content, the absorption edge shifts toward longer wavelengths and the optical band gap decreases. This behavior can be explained in terms of changes to the Pb−O/Bi−O chemical bonds with glass composition. We obtained a new empirical relation between the optical band gap and the refractive index which can be used to accurately determine the electronic oxide polarizability in lead and bismuth oxide glasses.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Coupled high-throughput functional screening and next generation sequencing for identification of plant polymer decomposing enzymes in metagenomic libraries

Recent advances in sequencing technologies generate new predictions and hypotheses about the functional roles of environmental microorganisms. Yet, until we can test these predictions at a scale that matches our ability to generate them, most of them will remain as hypotheses. Function-based mining of metagenomic libraries can provide direct linkages between genes, metabolic traits and microbial taxa and thus bridge this gap between sequence data generation and functional predictions. Here we developed high-throughput screening assays for function-based characterization of activities involved in plant polymer decomposition from environmental metagenomic libraries. The multiplexed assays use fluorogenic and chromogenic substrates, combine automated liquid handling and use a genetically modified expression host to enable simultaneous screening of 12,160 clones for 14 activities in a total of 170,240 reactions. Using this platform we identified 374 (0.26%) cellulose, hemicellulose, chitin, starch, phosphate and protein hydrolyzing clones from fosmid libraries prepared from decomposing leaf litter. Sequencing on the Illumina MiSeq platform, followed by assembly and gene prediction of a subset of 95 fosmid clones, identified a broad range of bacterial phyla, including Actinobacteria, Bacteroidetes, multiple Proteobacteria sub-phyla in addition to some Fungi. Carbohydrate-active enzyme genes from 20 different glycoside hydrolase (GH) families were detected. Using tetranucleotide frequency (TNF) binning of fosmid sequences, multiple enzyme activities from distinct fosmids were linked, demonstrating how biochemically-confirmed functional traits in environmental metagenomes may be attributed to groups of specific organisms. Overall, our results demonstrate how functional screening of metagenomic libraries can be used to connect microbial functionality to community composition and, as a result, complement large-scale metagenomic sequencing efforts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Thermal characterization and properties of a copper-diamond composite

The thermal properties of a commercial copper-diamond composite were measured from below -50°C to above 200°C. The results of thermal expansion, heat capacity, and thermal diffusivity were reported. These data were used to calculate the thermal conductivity of the composite as a function of temperature in the thickness direction. These results are compared with estimated values based on a simple mixing rule and the temperature dependence of these physical properties is represented by curve fitting equations. These fitting equations can be used for thermal modeling of practical devices/systems at their operation temperatures. The results of the mixing rule showed a consistent correlation between the amount of copper and diamond in the composite, based on density, thermal expansion, and heat capacity measurements. However, there was a disparity between measured and estimated thermal diffusivity and thermal conductivity. These discrepancies can be caused by many intrinsic material issues such as lattice defects and impurities, but the dominant factor is attributed to the large uncertainty of the interfacial thermal conductance between diamond and copper.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Dynamic microbial assembly processes correspond to soil fertility in sustainable paddy agroecosystems

1. Microorganisms underpin the sustainability of agroecosystems, but we have a poor understanding of how the assembly processes that govern microbial community structure interact through time to maintain soil fertility. 2. Ancient rice paddies have a history of cultivation spanning hundreds or thousands of years and provide an ideal opportunity to explore relationships between community assembly processes and long-term agroecosystem sustainability. We used statistical null models to evaluate temporal patterns of bacterial community assembly processes across rice cultivation years and their associations with increases in soil fertility in paddy agroecosystems. 3. We found that stochasticity was a persistent force structuring paddy soil microbial communities, putatively due to frequent flooding that facilities dispersal. However, determinism gradually increased over centuries of agriculture and corresponded to increases in soil fertility. Accordingly, multifunctionality, calculated using enzymes catalyzing key soil functions in carbon, nitrogen, phosphorous and sulfur cycling significantly increased along rice cultivation years. We therefore propose that balanced assembly processes preserve a diverse array of traits that can dominate under various circumstances (stochasticity) while allowing for traits relevant to soil fertility to be selected for by soil fertility (determinism), thus supporting multifunctionality that underlies sustainable agroecosystems. 4. In total, our results highlight that knowledge on temporal microbial assembly processes, community composition, and ecological function in context of soil fertility is key to understanding ecological mechanisms maintaining agroecosystems sustainability.

Liu, Wenjing↗
DOE OSTI2014

Next Generation Solvent Development for Caustic-Side Solvent Extraction of Cesium

This report summarizes the FY 2010 and 2011 accomplishments at Oak Ridge National Laboratory (ORNL) in developing the Next Generation Caustic-Side Solvent Extraction (NG-CSSX) process, referred to commonly as the Next Generation Solvent (NGS), under funding from the U.S. Department of Energy, Office of Environmental Management (DOE-EM), Office of Technology Innovation and Development. The primary product of this effort is a process solvent and preliminary flowsheet capable of meeting a target decontamination factor (DF) of 40,000 for worst-case Savannah River Site (SRS) waste with a concentration factor of 15 or higher in the 18-stage equipment configuration of the SRS Modular Caustic-Side Solvent Extraction Unit (MCU). In addition, the NG-CSSX process may be readily adapted for use in the SRS Salt Waste Processing Facility (SWPF) or in supplemental tank-waste treatment at Hanford upon appropriate solvent or flowsheet modifications. Efforts in FY 2010 focused on developing a solvent composition and process flowsheet for MCU implementation. In FY 2011 accomplishments at ORNL involved a wide array of chemical-development activities and testing up through single-stage hydraulic and mass-transfer tests in 5-cm centrifugal contactors. Under subcontract from ORNL, Argonne National Laboratory (ANL) designed a preliminary flowsheet using ORNL cesium distribution data, and Tennessee Technological University confirmed a chemical model for cesium distribution ratios (DCs) as a function of feed composition. Inter laboratory efforts were coordinated with complementary engineering tests carried out (and reported separately) by personnel at Savannah River National Laboratory (SRNL) and Savannah River Remediation (SRR) with helpful advice by Parsons Engineering and General Atomics on aspects of possible SWPF implementation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Next Generation Solvent (NGS): Development for Caustic-Side Solvent Extraction of Cesium

This report summarizes the FY 2010 and 2011 accomplishments at Oak Ridge National Laboratory (ORNL) in developing the Next Generation Caustic-Side Solvent Extraction (NG-CSSX) process, referred to commonly as the Next Generation Solvent (NGS), under funding from the U.S. Department of Energy, Office of Environmental Management (DOE-EM), Office of Technology Innovation and Development. The primary product of this effort is a process solvent and preliminary flowsheet capable of meeting a target decontamination factor (DF) of 40,000 for worst-case Savannah River Site (SRS) waste with a concentration factor of 15 or higher in the 18-stage equipment configuration of the SRS Modular Caustic-Side Solvent Extraction Unit (MCU). In addition, the NG-CSSX process may be readily adapted for use in the SRS Salt Waste Processing Facility (SWPF) or in supplemental tank-waste treatment at Hanford upon appropriate solvent or flowsheet modifications. Efforts in FY 2010 focused on developing a solvent composition and process flowsheet for MCU implementation. In FY 2011 accomplishments at ORNL involved a wide array of chemical-development activities and testing up through single-stage hydraulic and mass-transfer tests in 5-cm centrifugal contactors. Under subcontract from ORNL, Argonne National Laboratory (ANL) designed a preliminary flowsheet using ORNL cesium distribution data, and Tennessee Technological University confirmed a chemical model for cesium distribution ratios (DCs) as a function of feed composition. Interlaboratory efforts were coordinated with complementary engineering tests carried out (and reported separately) by personnel at Savannah River National Laboratory (SRNL) and Savannah River Remediation (SRR) with helpful advice by Parsons Engineering and General Atomics on aspects of possible SWPF implementation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Complex oxides: Intricate disorder

In this study, complex oxides such as pyrochlores have a myriad of potential technological applications, including as fast ion conductors and radiation-tolerant nuclear waste forms. They are also of interest for their catalytic and spin ice properties. Many of these functional properties are enabled by the atomic structure of the cation sublattices. Pyrochlores (A2B2O7) contain two different cations (A and B), typically a 3+ rare earth and a 4+ transition metal such as Hf, Zr, or Ti. The large variety of chemistries that can form pyrochlores leads to a rich space in which to search for exotic new materials. Furthermore, how cations order or disorder on their respective sublattices for a given chemical composition influences the functional properties of the oxide. For example, oxygen ionic conductivity is directly correlated with the level of cation disorder — the swapping of A and B cations 1 . Further, the resistance of these materials against amorphization has also been connected with the ability of the cations to disorder 2, 3 . These correlations between cation structure and functionality have spurred great interest in the structure of the cation sublattice under irradiation, with significant focus on the disordering mechanisms and disordered structure. Previous studies have found that, upon irradiation, pyrochlores often undergo an order-to-disorder transformation, in which the resulting structure is, from a diffraction point of view, indistinguishable from fluorite (AO2) (ref. 3). Shamblin et al. now reveal that the structure of disordered pyrochlore is more complicated than previously thought 4 .

36 MATERIALS SCIENCE↗
DOE OSTI2026

Benchtop Autonomous Electrochemical Characterization System for Combinatorial Thin-Film Solid Oxide Electrodes

The design of materials for electrochemical energy conversion is complicated by a vast search space of candidate materials and multifaceted property requirements: multicarrier conductivity, stability, and catalytic activity are all necessary but rarely intersect. Although self-driving laboratories are rapidly rising to address such material optimization problems, the required infrastructure for integrated, large-scale robotic facilities can be cost-prohibitive. Here we develop and evaluate a closed-loop measurement system for efficient screening of proton-conducting oxide electrodes for ceramic fuel cells and electrolyzers, building on top of an existing benchtop instrument and integrating techniques for rapid impedance measurement and automated analysis. This system exemplifies a “minimum viable” self-driving implementation that can deliver substantial benefits with relatively simple infrastructure. Combinatorial thin-film microelectrode libraries are characterized with a recently developed joint time-domain and frequency-domain impedance measurement technique, which provides an order-of-magnitude acceleration relative to conventional impedance spectroscopy. The distribution of relaxation times is extracted from impedance data and analyzed without human intervention. These results feed an active learning and Bayesian optimization process that learns to predict electrochemical impedance as a function of material composition, measurement temperature, oxygen partial pressure, and electrical bias, which further reduces the screening time by tenfold with optimized experimental sequences. We apply this system to Ba⁡(Co,Fe,Zr,Y)⁢O 3−𝛿 combinatorial libraries and evaluate its effectiveness for learning material property trends and optimizing expensive-to-evaluate properties such as activation energy. This offers insights into key methodological aspects of practical autonomous experimentation, including surrogate model validation, cost-aware acquisition functions, and high-throughput data interpretation. Our results demonstrate the efficacy of the system for rapidly gathering information, but also highlight real-world experimental challenges of thin-film degradation and numerical instability in surrogate models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗