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At least 289 records · Page 16

Managing Sn-supply to tune surface characteristics of vapor-diffusion coating of Nb3Sn

Nb₃Sn promises better RF performance (Q and E_{acc}) than niobium at any given temperature because of superior superconducting properties. Nb₃Sn-coated SRF cavities are now produced routinely by growing a few microns thick Nb₃Sn films inside Nb cavities via the tin vapor diffusion technique. Sn evaporation and consumption during the growth process notably affect the quality of the coating. Aiming at favorable surface characteristics that could enhance the RF performance, many coatings were produced by varying Sn sources and temperature profiles. Coupon samples were examined using different material characterization techniques, and a selected few sets of coating parameters were used to coat 1.3 GHz single-cell cavities for RF testing. The Sn supply’s careful tuning is essential to manage the microstructure, roughness, and overall surface characteristics of the coating. We summarize the material analysis of witness samples and discuss the performance of several Nb₃Sn-coated single-cell cavities linked to Sn-source characteristics and observed Sn consumption during the film growth process.

Pudasaini, U.↗

Quantification of room temperature strengthening of laser shock peened Ni-based superalloy using synchrotron microdiffraction

Laser shock peening (LSP), a surface modification technique, is promising to enhance the strength and wear resistance for Ni-based superalloys. To understand the strengthening mechanism in a laser shock peened Ni-based superalloy DZ417G, we utilize synchrotron poly- and monochromatic X-ray microdiffraction, as well as electron microscopy and microhardness to quantify the local microstructures and mechanical properties at various depths. In the 1.2-mm-deep hardened layer, the microhardness increases monotonically by ~50% from the unaffected interior to the surface. Quantitative microdiffraction analysis shows that large amounts of dislocations are introduced by LSP. High densities of 7.1 × 10 15 m -2 and 11.8 × 10 15 m -2 are seen close to the peened surface for the γ- and γ'-phases, respectively, which are 5 and 20 times of those in the unaffected region. Different gradients of dislocation density are observed for the two phases from interior to surface, and their combined effect accounts well for the hardness increment. Due to the unaltered γ'-precipitates and chemical composition in the LSP affected zone, the large density of dislocations dominates the observed strengthening. Combined poly- and monochromatic X-ray microdiffraction allows quantifying the local microstructures of plastic deformation over a large sampling scale that can hardly be achieved using other materials characterization techniques.

36 MATERIALS SCIENCE↗

Investigation of Lubricant Additive Interactions on Gasoline Particulate Filters

To understand how the composition of novel lubricant additives and their ash interact with gasoline particulate filters (GPFs), an accelerated aging protocol was conducted using three lubricant additive formulations and two GPF types. The additive packages (adpaks) consisted of Ca+Mg detergent in a 3:1 or 0:1 ratio and an anti-wear component—either zinc dialkyl dithiophosphate (ZDDP) or a novel phosphonium-phosphinate ionic liquid (IL) substitute. The particulate sampling captured amount/compositions of particulate matter (PM) generated, total particulate number, and size distribution. Five ash loadings were completed. GPF position and adpak composition affected the backpressure, ash composition, ash morphology, and captured mass. The particulate sampling indicated that the ash component consisted primarily of particles less than 50 nm in size and that the Mg-only adpak resulted in more particulate of 50–400 nm in size. Postmortem materials characterization indicated GPFs in the underfloor position had deeper penetration of ash into the walls compared to the close-coupled position. Additionally, the Mg-only adpak had a higher filter collection efficiency (>90%) and the ash particles consisted of a higher concentration of dense ash material. In contrast, four of the 3:1 Ca:Mg lubricant adpaks resulted in a collection efficiency of only 40–50%. Although the collection efficiency was higher with the Mg-only adpak, the ash layer in the GPF was not thicker, nor was the penetration into the wall more significant, and surprisingly the full useful life (FUL) backpressure was lower than with Ca:Mg adpaks. The higher density of the Mg-derived ash was the only detectable difference. A possible explanation of this observation is that Mg ash has a lower melting point and is more susceptible to densification during combustion or GPF regeneration. The substitution of IL in place of the ZDDP did not lead to any notable changes in collection efficiency or location of the ash.

42 ENGINEERING↗

Interplay Between Strain and Thickness on the Effective Carrier Lifetime of Buffer-Mediated Epitaxial Germanium Probed by the Photoconductance Decay Technique

We report contactless effective minority carrier lifetime of epitaxially grown unstrained and in-plane <110> biaxially tensile-strained (001) germanium (..epsilon..-Ge) epilayers measured using microwave-reflectance photoconductance decay measurements. Strained Ge epilayers were grown using InxGa1-xAs linearly graded buffers on (001) GaAs substrates. Using homogeneous excitation of unstrained Ge epilayers, thickness-dependent separation of minority carrier lifetime components under low injection conditions yielded a bulk lifetime of 114 +/- 2 ns and low surface recombination velocity of 21.3 +/- 0.04 cm/s. More notably, an effective minority carrier lifetime of >100 ns obtained from sub-50 nm 1.6% tensile-strained Ge epilayers showed no degradation relative to the unstrained counterpart. Detailed material characterization using X-ray diffractometry revealed successful strain transfer of 0.61 and 0.89% to the Ge epilayers via InxGa1-xAs metamorphic buffers and confirms pseudomorphic growth. Lattice coherence observed at the e-Ge epilayer and InxGa1-xAs buffer heterointerfaces via transmission electron microscopy substantiates the prime material quality achieved. The relatively high carrier lifetimes achieved are an indicator of excellent material quality and provide a path forward to realize low-threshold Ge laser sources.

bulk lifetime↗

DuraMAT: Building a Consortium to Accelerate the Photovoltaic Module Reliability Learning Cycle

Durable and reliable photovoltaic (PV) modules are critical to enabling an efficient transition to sustainable energy generation. The rate at which new module designs and materials are developed and deployed currently outpaces the rate at which we can identify failure mechanisms and understand degradation rates. Increasing the service life of PV modules, and our ability to predict performance over time, requires more durable materials and designs, better durability testing, more extensive material characterization, robust modeling, and methods to cross-examine historical performance data to extract meaningful results. This is a multidisciplinary challenge that requires expertise from a broad range of fields and, therefore, benefits significantly from a collaborative approach. In this Perspective, we outline the approach taken by the Durable Module Materials Consortium (DuraMAT), present a few case studies where our approach was successful, and provide an outlook on where this approach might be applied as the PV technology landscape continues to rapidly evolve. Published by the American Physical Society 2024

14 SOLAR ENERGY↗

High-Strength, High-Ductility, High Entropy Alloys with High-Efficiency Native Oxide Solar Absorbers for Concentrating Solar Power Systems

This EPSCoR Project has been investigating the synergy between the excellent high-temperature mechanical behavior of FeMnNiAlCr high entropy alloys (HEA) and the high solar absorptance of their native oxides for high efficiency concentrated solar thermal power (CSP) systems working at >700°C. While HEAs have attracted substantial interest in recent years, most investigations have focused on their applications as structural materials rather than functional materials. This EPSCoR project discovered that FeMnNiAlCr HEAs can potentially be applied synergistically as both a structural and functional material for high-efficiency concentrating solar thermal power (CSP) systems working at >700°C. The HEA itself would be used in high-temperature tubing to carry molten salts or supercritical CO 2 , while its surface oxide would act as a high-efficiency solar thermal absorber. With Fe and Mn being the major components in these HEAs (adding up to ~70 at.% of the alloy), these materials are much more cost-effective than the Ni-based superalloys currently being investigated for high-temperature CSP systems. Through this research, these Fe-Mn based HEAs have demonstrated yield strengths 2-3x greater than that of stainless steel at 700°C and a creep lifetime >800 h at 700ºC under a typical CSP tubing mechanical load of 35 MPa. Their Mn-rich surface oxides maintain a high optical-to-thermal conversion efficiency of ~87% under 1000x solar concentration ratio for 20 simulated day-night thermal cycles between 750ºC and room temperature. In preliminary corrosion studies, these HEAs have sustained immersion in unpurified bromide molten salts for 14 days at 750°C with <2% weight loss, in contrast to 70% weight loss from a 316 stainless steel reference. The simultaneous achievement of promising mechanical, optical, and thermochemical properties in this FeMnNiAlCr system opens the door to new applications of HEAs in solar energy harvesting. Partnerships with Ames Laboratory and Oak Ridge National Laboratory (ORNL) also advanced our understanding of the fundamental structure-property relationships through atomic scale material characterization and first-principles computational modeling. The key research results in this project can potentially be extended to other HEAs and their native oxides. In terms of applications, the proposed FeMnNiAlCr HEA/native oxide system could potentially exceed the mechanical and the optical performance of existing tubing and solar coating materials under EERE’s CSP program at lower cost, which also aligns well with the EPSCoR Science and Technology strategies of New Hampshire in boosting the deployment of renewable energy.

14 SOLAR ENERGY↗

Artificial neural network approach for multiphase segmentation of battery electrode nano-CT images

The segmentation of tomographic images of the battery electrode is a crucial processing step, which will have an additional impact on the results of material characterization and electrochemical simulation. However, manually labeling X-ray CT images (XCT) is time-consuming, and these XCT images are generally difficult to segment with histographical methods. We propose a deep learning approach with an asymmetrical depth encode-decoder convolutional neural network (CNN) for real-world battery material datasets. This network achieves high accuracy while requiring small amounts of labeled data and predicts a volume of billions voxel within few minutes. While applying supervised machine learning for segmenting real-world data, the ground truth is often absent. The results of segmentation are usually qualitatively justified by visual judgement. We try to unravel this fuzzy definition of segmentation quality by identifying the uncertainty due to the human bias diluted in the training data. Further CNN trainings using synthetic data show quantitative impact of such uncertainty on the determination of material’s properties. Nano-XCT datasets of various battery materials have been successfully segmented by training this neural network from scratch. We will also show that applying the transfer learning, which consists of reusing a well-trained network, can improve the accuracy of a similar dataset.

25 ENERGY STORAGE↗

Tailored Fiber Placement for Complex Preforms

Tailored Fiber Placement (TFP) offers a novel approach to optimize fiber architecture for the fabrication of complex, structural parts not traditionally suitable for advanced composites. This technology not only offers new routes for weight reduction via metal substitution, it also offers cost reduction through minimization of material scrap and reduced labor. This reduction in component weight leads to increased fuel efficiency, and reduced production energy consumption, thereby, helping to achieve the stated IACMI technical goals. This technology leverages centuries of manufacturing development in support of the textile and embroidery industry. One major drawback to this technology is the lack of commercial or non- proprietary structural performance data and robust analytical tools used to optimize fiber architecture and predict performance. This project was structured to utilize common sub-element features to validate analytical performance tools, generate performance data, and gather cost and performance data on components of interest. This project was designed to give industry sponsors the confidence and ability to take full advantage of TFP to fabricate primary, highly loaded structure and integrate features such as metallic fasteners. The project focused principally on the use of high strength carbon fiber, such as T700, and the use of aerospace epoxy resin matrix to primarily support development of new composite applications in vehicle, aerospace, and industrial markets. This project applied previously developed analytical tools to predict the performance of TFP produced parts. This work focused on developing the pipeline to characterize material in order to accurately predict component performance when modifying the TFP print paths and stitch density. This focused on experimental characterization via standardized ASTM testing, alongside experimental testing of more representative service components by testing curved beam strength, beam shear performance, a large scale TFP lug, and ultimately designing a fully TFP clip bracket that reduced weight and cost compared to a traditional metallic component. The new knowledge gained from this program included: 1) development and demonstration of novel analytical tools applied to analysis of TFP preforms; 2) development and demonstration of a building block approach using coupons and sub-elements to optimize the design of a more complex component; 3) demonstration that optimized fiber orientation using TFP can exceed performance of conventional textile composite materials and can open new applications currently limited to metallic components; 4) Demonstration of performance and cost benefits of the TFP process as compared to metallic and conventional textile composites. Recommendations for follow-on work include development of design allowables to assess the impact of high temperature/moisture exposure or saturation during loading, tracking the impact of stitching needle wear on the performance of parts and ability to stitch thicker preforms, using TFP preforms as local reinforcement at areas of bearing or complex loading, and topology optimization of components by tow steering. The expertise developed during the course of this project can be leveraged to provide commercial engineering design and fabrication services using TFP. UDRI is in the process of formalizing their partnership with Spintech, who will serve as the commercialization partner for this technology and provide molding services and deliver finished components to the end user. UDRI will continue to produce the preforms until the economics allow Spintech to procure its own TFP equipment or lease UDRI equipment, at which point UDRI will step away from manufacture and serve as the engineering and design lead on product development.

36 MATERIALS SCIENCE↗

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↗

Accelerating Additive Manufacturing Process Design for Energy Conversion Materials using In-situ Sensing and Machine Learning

One promising candidate for manufacturing of the bismuth Telluride thermoelectric legs is laser powder bed fusion (LPBF) additive Manufacturing (AM). AM processing parameters highly influence the material properties, however current processing parameter development methods in AM are costly and time consuming. In-situ sensors allow for the capture of physically relevant process information on a layer-by-layer basis and will be used to aide process development. To optimize the AM process for the best thermoelectric performance, process variables, in-situ process sensor data and ex-situ material characterization data are collected. Several different interpretable machine learning (ML) approaches are used, and the performance of each method are assessed. Significant input process variables include laser focus, hatch spacing and laser power. The best performing models are used to determine the manufacturing parameters that maximize the power factor. AM of bismuth telluride material provides the ability to create complex geometries enabling more efficient energy conversion.

30 DIRECT ENERGY CONVERSION↗

Cadmium Magnesium Telluride for Next Generation X-Ray Free Electron Laser, Synchrotron and Many Other Applications

We developed a picosecond photodetector based on our Bridgman grown and specially engineered Cadmium Magnesium Telluride (Cd 1-x Mg x Te) single crystal that is sensitive to both optical and x-ray pulses for coarse timing in Free Electron Laser applications. Cd 1-x Mg x Te is a wide bandgap semiconductor material with potential applications, not only in optoelectronics, but also in particle physics as an intense pulse radiation detector for bremsstrahlung, X-ray/gamma ray radiation, thermal neutrons, and medical imaging. However, for femtosecond optical and x-ray cross correlation, the material has to have very short lifetime, a condition that is opposite to that required for nuclear spectroscopy applications. At the same time, the material also needs to have very low bulk leakage current, in the 0.10 pA range. Hence the ability to tailor or engineer the material is very crucial. In this paper, picosecond response and the crystal growth of this specially engineered cadmium magnesium telluride material will be presented. Other material characterization and transient measurements will also be discussed along with room temperature semiconductor detector performance for other nuclear radiation detection applications.

36 MATERIALS SCIENCE↗

Atom Probe characterization of neutron irradiated commercial ZIRLO® and AXIOM X2® alloys

As part of the Mechanistic Understanding of ZIrconium Corrosion (MUZIC) program, this team has been instrumental to obtain EPRI and Westinghouse sponsorships to prepare the neutron irradiated ZIRLO® and X2® from Vogtle nuclear power plant and ship them from Studsvik’s (Sweden) hot cells to Idaho National Laboratory (INL) to be part of the NSUF library. The uniqueness of these sets of neutron irradiated alloys is that they are at the same two extremes of the fuel cycles, allowing us to study the microchemistry evolution as a function of irradiation doses, exposure time and solute content. Advanced commercial Zirconium-Niobium (Zr-Nb) alloys, such as ZIRLO® and AXIOM®, have been developed by Westinghouse to enhance the corrosion resistance of fuel cladding material for longer service time. This study specifically aims at investigating the neutron irradiation induced Nb redistribution in AXIOM® X2® to understand the effect of neutron irradiation induced microchemistry changes and the irradiation enhanced corrosion resistance observed in ZrNb alloys. The detailed sample information on chemical composition and irradiation is given in shown in Table 1a and 1b respectively. To study the neutron IIP/nanoclusters and Nb concentration in the solid solution, atom probe tomography (APT) is the primary tool to obtain reliable chemical information. APT specimens were prepared in shielded focused ion beam (FIB) at the Irradiated Materials Characterization Laboratory (IMCL) at INL followed by APT analysis at CAES facility using LEAP 4000XR

36 MATERIALS SCIENCE↗

Characterization of Aluminum Metal Powders for Plutonium-238 Program

As part of radioisotope thermoelectric generator (RTG) production for power sources in deep space exploration, Oak Ridge National Laboratory (ORNL) produces plutonium-238 ( 238 Pu). To produce 238 Pu, neptunium-237 ( 237 Np) targets are fabricated at ORNL and subsequently irradiated at the High Flux Isotope Reactor (HFIR) at ORNL and the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). Specifically, current flowsheets utilize neptunium dioxide ( 237 NpO 2 ) targets. Aluminum (Al) powder is blended with 237 NpO 2 target material to improve thermal conductivity during irradiation. The current composition of 237 NpO 2 /Al pellets (i.e., cermets, or ceramic–metallics) is 20% 237 NpO 2 , 70% Al, and 10% void space. Al powders utilized by the 238 Pu program are high-fired under vacuum before blending into targets. The primary objective of this work is to measure the physical, chemical, and thermal properties of Al before and after the high-firing process. Properties of interest include the morphology, surface texture, particle size, crystal phase(s), and thermal conductivity of the material. These properties are measured with existing materials characterization equipment at ORNL, including powder x-ray diffraction (pXRD), scanning electron microscopy (SEM) with energy-dispersive spectroscopy (EDS), laser flash analysis (LFA), and thermogravimetric analysis (TGA). A secondary objective of this work is to compare the Al powders before and after the high-firing procedure to determine the effects of high-firing on chemical, physical, and thermal properties and to determine the efficacy of the high-firing process.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Development of a Laser Ultrasonics-based Approach for Rapid Screening of High Entropy Alloys

This project utilized a laser ultrasonic technique to systematically study temperature-induced evolution of material properties in a set of interrelated binary alloys and a high entropy alloy (HEA) fabricated using arc-melting and spark plasma sintering processes. This technique involved the use of a nanosecond duration, high-intensity pulsed laser to thermo-elastically generate ultrasonic waves that propagate in the bulk of the metal alloy. Sub-nanometer-scale displacements associated with the propagating bulk ultrasonic waves were detected along the epicenter on the opposite surface of the sample using a 1 GHz bandwidth photorefractive interferometer. Phase transformations and microstructural changes were inferred from the temperature-dependent trends in the bulk acoustic velocities and features in the ultrasonic epicentral waveforms measured in the binary alloys. These inferences were then correlated with electron/optical microscopy observations and predictions using calculations of phase diagrams (CALPHAD). The results showed that the laser-generated ultrasonic pulses were strongly influenced by changes in material microstructure and could accurately track thermally driven phase transformations and detect the presence of microscale heterogeneities (grain boundaries, dendritic structures, etc.) in the set of binary alloy samples. The measurement approach was then applied to a quinary HEA sample for estimating phase transition temperature and determining microstructural heterogeneity. The rapid, non-contact and non-destructive ultrasonic testing approach demonstrated here is amenable to high throughput combinatorial investigations that can be applied to graded composition HEAs produced using advanced manufacturing methods. When paired with atomistic simulations and CALPHAD modeling, this approach can overcome the bottlenecks faced by current material characterization methods in efficiently screening the vast discovery space of HEAs that spans over a hundred million unique quinary alloy compositions.

36 MATERIALS SCIENCE↗

Generation of macro- and microplastic databases by high-throughput FTIR analysis with microplate readers

Abstract FTIR spectral identification is today’s gold standard analytical procedure for plastic pollution material characterization. High-throughput FTIR techniques have been advanced for small microplastics (10–500 µm) but less so for large microplastics (500–5 mm) and macroplastics (> 5 mm). These larger plastics are typically analyzed using ATR, which is highly manual and can sometimes destroy particles of interest. Furthermore, spectral libraries are often inadequate due to the limited variety of reference materials and spectral collection modes, resulting from expensive spectral data collection. We advance a new high-throughput technique to remedy these problems using FTIR microplate readers for measuring large particles (> 500 µm). We created a new reference database of over 6000 spectra for transmission, ATR, and reflection spectral collection modes with over 600 plastic, organic, and mineral reference materials relevant to plastic pollution research. We also streamline future analysis in microplate readers by creating a new particle holder for transmission measurements using off-the-shelf parts and fabricating a nonplastic 96-well microplate for storing particles. We determined that particles should be presented to microplate readers as thin as possible due to thick particles causing poor-quality spectra and identifications. We validated the new database using Open Specy and demonstrated that additional transmission and reflection spectra reference data were needed in spectral libraries. Graphical abstract

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

FY 2024 Multidimensional Data Correlation Platform Data Management Infrastructure Progress: Materials Laboratory

This report provides an inventory of the equipment available at the ORNL Manufacturing Demonstration Facility (MDF) for sample preparation and material characterization, including both destructive and non-destructive techniques that generate critical data to support the development of the Multi-Dimensional Data Correlation (MDDC) framework. The success of the MDDC framework depends heavily on the quality and completeness of the data it can access. Therefore, it is essential to establish a comprehensive inventory of the technologies available to the Advanced Materials and Manufacturing Technologies (AMMT) multi-laboratory team. This starts by gathering information about the types of data they produce, the data collection and transfer protocols used, file formats, and data storage requirements for experiments. This information is then carefully evaluated to create the operations and trackables elements of the Damara Tern platform, which is the foundation of the MDDC framework.

36 MATERIALS SCIENCE↗

Sodium trithiocarbonate cathode for high-performance sodium–sulfur batteries

The high abundance and low cost of sodium and sulfur make room-temperature sodium-sulfur (RT Na-S) batteries an attractive technology compared to the current lithium-ion batteries for large-scale grid-storage applications. However, the commercialization of RT Na-S batteries is impeded by the slow kinetics of Na-S chemistry, severe sodium polysulfide shuttling, and uncontrollable growth of dendritic Na. Herein, sodium trithiocarbonate (Na 2 CS 3 ) is applied as a cathode material to facilitate concurrent improvement in both electrodes, leading to a high-rate performance with extended cycle life. The conductive characteristic of the carbon-sulfur resonance bond provides fast ion and electron transfer throughout the cathode, resulting in superior electrochemical reactivity. At the cathode, the presence of Na2CS3 forms an oligomer-structured layer to suppress the dissolution and shuttling of active materials. Meanwhile, when small portions of Na 2 CS 3 intermediates migrate to the anode, a stable solid electrolyte interphase (SEI) layer with uniform Na-ion flux is formed, enabling improved Na stripping and plating performance. A series of electrochemical and materials characterization, accompanied by density functional theory calculations demonstrate that Na 2 CS 3 is a promising candidate to realize high-rate performance long cycle life RT Na-S batteries.

25 ENERGY STORAGE↗

Mixed Ionic Electronic Conducting Quaternary Perovskites: Materials by Design for Solar Thermochemical Hydrogen

The innovative research conducted by Arizona State University and Princeton University in the project "Mixed Ionic-Electronic Conducting Quaternary Perovskites: Materials by Design for Solar Thermochemical Hydrogen" marks a significant stride forward in thermochemical water splitting. Through an intricate blend of computational design and experimental validation, the project delved into the promising potential of Mixed Ionic Electronic Conducting (MIEC) perovskites. These complex materials, characterized by their unique redox-active nature and adaptability in stoichiometry, present a promising frontier for efficient solar thermochemical hydrogen production. Firstly, the research enhanced the science by utilizing state-of-the-art computational methodologies to unravel the nuanced chemical potentials of MIEC perovskites. By simulating various off-stoichiometric scenarios and redox conditions, the team was able to predict material behaviors under diverse environmental conditions, a feat unachievable through conventional experimental methodologies alone. This approach not only fast-tracks the material screening process, significantly reducing the time from laboratory re-search to practical application, but also uncovers trends and correlations that are pivotal for future materials innovation. Regarding technical effectiveness, the project stands out in its economic feasibility. Traditional methods of materials discovery are often marred by high costs and extensive timeframes, owing to the iterative nature of experimental processes. However, by employing theoretical computations and validating these findings with targeted experiments, the project introduced a cost-effective paradigm for materials discovery and the first ever prediction, synthesis, and preliminary validation of a material solely from computational and theoretical considerations. This synergy between computation and experimentation expedites the discovery of optimal materials conducive to high-efficiency solar-to-hydrogen conversion processes. Furthermore, the public stands to benefit substantially from this research. The success of MIEC perovskites in solar thermochemical applications heralds a shift towards lower cost and lower electricity input for clean hydrogen production, hence potentially impacting climate and energy resilience. By improving the efficiency of solar-to-hydrogen conversions, the research paves the way for reduced dependency on fossil fuels, addressing the urgent global need for accessible and renewable energy sources. Moreover, the project's advancements contribute to scientific literacy in renewable energy technologies, empowering society through knowledge and spurring future innovations. In essence, this research project demonstrates significant progress in the realm of advanced water splitting through solar thermochemistry. Through its groundbreaking approaches in computational materials science and its implications for real-world applications, it holds the promise of a cleaner, more energy-resilient future.

08 HYDROGEN↗