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DOE OSTI2021

Combining Spectroscopic Ellipsometry with Transmission Spectroscopy to Derive Accurate Optical Constants for Organic Materials

A method for deriving the optical constants of organic powdered materials in the mid-infrared spectral range is introduced using variable angle spectroscopic ellipsometry and transmission spectroscopy. The approach uses pressed pellets of the powder and is applied to organic solids, which have both strong and weak infrared absorption features. Many powders have significant voids and do not press into smooth, homogenous pellets. To account for pellet non-idealities and to accurately measure both n and k, three different forms of pellets were pressed and measured: A pure analyte pellet, a mixed analyte/KBr pellet with a large analyte percentage, and a KBr transmission pellet with only a small analyte percentage. Using all three pellets in a multi-sample analysis involving both ellipsometric and transmission data, the complex refractive index (n/k) values can be derived for many organic compounds. This method is illustrated to calculate the optical constants for anhydrous lactose from 6000-400 cm-1. The transmission measurements improve the spectral fitting of weak absorption features, and the multi-sample analysis enables a better determination of the significant void space that is present in the pure pellet, leading to lower values for both n and k if not properly accounted for in the multi-oscillator model used to fit the ellipsometric data.

Optical constants, refractive index, extinction co↗

DOE OSTI2024

Designing Particle Morphologies for Materials with Solid Transport Limitations: A Case Study of Lithium and Manganese Rich Cathode Oxides

A lithium and manganese rich nickel-manganese-cobalt oxide (LMR-NMC) cathode is a promising candidate for next-generation batteries due to its high specific capacity, low cost, and low cobalt content. However, the material suffers from poor rate capability due to the diffusion limitations of lithium in the cathode particles. Understanding the material performance requires careful control of the morphology of the cathode particles, taking into account the primary and agglomerated diffusion pathways and the presence of pores, some of which could be closed from electrolyte infiltration. Here, in this study, we use a microstructure-based mathematical model combined with experimental data to understand the role of the complex cathode particle morphology in the rate performance of the material. Scanning electron microscopy images of cathodes made under different synthesis conditions, which results in different agglomerate morphologies, serve as the input into the mathematical model. The model is then compared to rate data to understand the controlling parameters. The presence of intra-agglomerate closed pores results in a large agglomerate diffusion length in comparison to the ideal condition, where the primary particles are agglomerated in an open and dispersed manner such that the entire interfacial area is available for electrochemical reaction. Smaller primary and agglomerate diffusion lengths result in better electrochemical performance. This points us toward designing the morphology of the cathode particles to compensate for the diffusion limitation of LMR-NMC while maximizing the density.

Tewari, Deepti↗

DOE OSTI2025

Microstructure‐Dependent Sodium Storage Mechanisms in Hard Carbon Anodes

Sustainable energy storage is essential to support the transition to renewables and meet the increasing demand for energy. Sodium‐ion batteries (NIBs) are attractive for grid‐scale energy storage due to the abundance and low cost of sodium, sustainability of other battery components, and electrochemical performance. Hard carbon (HC) is a leading anode material for NIBs, but its complex microstructure complicates the understanding of sodium storage mechanisms. Using X‐ray total scattering and density functional theory calculations, this study clarifies how HC's microstructural variations influence sodium storage across the slope (high potential) and plateau (low potential) regions of the potential capacity curve. In the slope region, sodium initially adsorbs at high‐binding energy defect sites and subsequently intercalates between graphene layers, adsorbing at low‐binding energy defect sites, correlating with different slopes observed during initial sodiation. Initial irreversibility arises from sodium trapping at surface defects and solid electrolyte interface formation. In the plateau region, sodium simultaneously intercalates and fills pores, influenced by pore size, interlayer spacing, and defect concentration. HCs with larger pore sizes form larger sodium clusters. In conclusion, the proposed mechanism underscores the role of microstructure engineering in enhancing HC performance and advancing NIBs for grid‐scale energy storage.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Influence of fuel ash on the recoverability of copper from the spent material of chemical looping combustion

Chemical looping combustion (CLC) is an advanced energy production technology that inherently separates the CO 2 generated. The oxygen needed for fuel conversion is supplied by the oxygen carrier. When using copper-based oxygen carriers, oxygen carrier attrition is a challenge to the process economics, unless the attrited copper that is mixed with fuel ash in the spent material can be recovered by, for instance, acid leaching. However, fuel ash may transform the attrited copper into certain complexes of low leachability (e.g., CuAl 2 O 4 ), hindering the copper recovery. In this study, the copper content in the spent material was first evaluated. The effects of ash composition and copper content on the occurrence mode of copper in spent material were predicted by thermodynamic modeling. Redox cycles of simulated spent materials based on various coal ashes were performed to reveal the characteristics of CuAl 2 O 4 /CuFe 2 O 4 formation. The CuO-Al 2 O 3 reaction was investigated under the temperatures and solid residence times experienced in CLC. The materials were analyzed by X-ray diffraction. The results suggest that the fuel ash with a high Al/Ca ratio may lower the recoverability of copper when the temperature is above 925 °C. The slow formation of CuFe 2 O 4 is not expected to affect the copper recovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Integrating computation and experiment to investigate photoelectrodes for solar water splitting at the microscopic scale.

CONSPECTUS: Photoelectrochemical water-splitting is a promising and sustainable way to store the energy of the sun in chemical bonds and use it to produce hydrogen gas, a clean fuel. The key components in photoelectrochemical cells (PECs) are photoelectrodes, including a photocathode that reduces water to hydrogen gas and a photoanode that oxidizes water to oxygen gas. Materials used in photoelectrodes for PECs must effectively absorb sunlight, yield photogenerated carriers, and exhibit electronic properties that enable the efficient shuttling of carriers to the surface to participate in relevant water-splitting reactions. Discovering and understanding the key characteristics of optimal photoelectrode materials is paramount to the realization of PEC technologies. Oxide-based photoelectrodes can satisfy many of these materials requirements, including stability in aqueous environments, band edges with reasonable alignment with the redox potentials for water splitting, and ease of synthesis. However, oxide photoelectrodes generally suffer from poor charge transport properties and considerable bulk electron-hole separation, and they have relatively large band gaps. Numerous strategies have been proposed to improve these aspects and understand how these improvements are reflected in the photoelectrochemical performance. Unfortunately, the structural and compositional complexity of multinary oxides accompanied by the inherent complexity of photoelectrochemical processes makes it challenging to understand the individual effects of composition, structure, and defects in the bulk and on the surface on a material's photoelectrochemical properties. The integration of experiment and theory has great potential to increase our atomic-level understanding of structure-composition-property relationships in oxide photoelectrodes. In this Account, we describe how integrating experiment and theory is beneficial for achieving scientific insights at the microscopic scale. We highlight studies focused on understanding the role of (i) bulk composition via solid-state solutions, intercalation, and comparison with isoelectronic compounds, (ii) dopants for both the anion and cation and their interactions with oxygen vacancies, and (iii) surface/interface structure in the photocurrent generation and photoelectrochemical performance in oxide photoelectrodes. In each instance, we outline strategies and considerations for integrating experiment and theory and describe how this integration led to valuable insights and new directions in uncovering structure-composition-property relationships. Our aim is to demonstrate the unique value of combining experiment and theory in studying photoelectrodes and to encourage the continued effort to bring experiment and theory in closer step with each other.

Wang, Wennie↗

DOE OSTI2023

Structural Investigation of Technetium Dibutylphosphate Species Using X-ray Absorption Fine Structure Spectroscopy

The speciation of Tc after the extraction of Tc(IV) from H 2 O and 1 M HNO 3 by dibutylphosphoric acid (HDBP) in dodecane has been studied by X-ray absorption fine structure (XAFS) spectroscopy. Results show the formation of dimeric species with Tc 2 O 2 and Tc 2 O units, and the formulas [Tc 2 O 2 (DBP·HDBP) 4 ] (1) and [Tc 2 O(NO 3 ) 2 (DBP) 2 (DBP·HDBP) 2 ] (2) were, respectively, proposed for the species extracted from H 2 O and 1 M HNO 3 . The interatomic Tc–Tc distances found in the Tc 2 O 2 and Tc 2 O units [2.55(3) and 3.57(4) Å, respectively] are similar to the ones found in Tc(IV) dinuclear species. It is likely that the speciation of Tc(IV) in dodecane is due to the extraction of a species with a Tc 2 O unit for (2) and to the redissolution of a Tc(IV)-DBP solid for (1). The XAFS results for (1) and (2) were compared to that obtained for the extraction of Tc(IV) with TBP/HDBP/dodecane from 0.5 M HNO 3 , (3) which highlight the formation of Tc mononuclear nitrate species {i.e. [Tc(NO 3 ) 3 (DBP)] or [Tc(NO 3 ) 2 (DBP·HDBP)]}. These results confirm the importance of the preparation and speciation of the Tc(IV) aqueous solutions prior to extraction and how much this influences and drives the final Tc speciation in organic extraction. Here, these studies outline the complexity of Tc separation chemistry and provide insights into the behavior of Tc during the reprocessing of used nuclear fuel.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Developing machine learning for heterogeneous catalysis with experimental and computational data

Machine learning techniques have emerged as a useful tool for identifying complex patterns and correlations in large datasets, such as associating catalyst performance to its physicochemical properties. In the heterogeneous catalysis communities, machine learning models have mostly been developed using high-throughput quantum chemistry calculations, with only a few case studies resulting in experimentally validated catalyst improvements. This limited success may be due to the use of simplified catalyst structures in computational studies and the lack of comprehensive experimental datasets. In this Review, we bring together studies integrating high-throughput approaches and machine learning for the advancement of solid heterogeneous catalysis, leveraging both experimental and computational data. We systematically analyze trends in the field, based on the descriptors used as model input and output; the materials, devices, or reactions investigated; the dataset size; and the overall achievements. Furthermore, for models reporting unitless R 2 values, we compare the performances based on these mentioned trends.

Computational chemistry↗

DOE OSTI2022

Materials research and development needs to enable efficient and electrified buildings

Because of the complexity of modern buildings—with many interconnected materials, components, and systems—fully electrifying buildings will require targeted R&D and efficient coordination across those material, component, and system levels. Because buildings that consume the smallest amount of energy are easier to electrify, energy efficiency is a crucial step toward fully electrified buildings. Materials advances will play an important role in both reducing the energy intensity of buildings and electrifying their remaining energy use. Materials are currently being explored, discovered, synthesized, evaluated, optimized, and implemented across many building components, including solid-state lighting; dynamic windows and opaque envelopes; cold climate heat pumps; thermal energy storage; heating, ventilating, and air conditioning (HVAC); refrigeration; non-vapor compression HVAC; and more. In this article, we review the current state-of-the-art of materials for various buildings end uses and discuss R&D challenges and opportunities for both efficiency and electrification.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Energy Frontier Research Centers: Center for the Computational Design of Functional Layered Materials (CCDM) August 1, 2014 - July 31, 2018; Center for Complex Materials from First Principles (CCM) August 1, 2018 - July 31, 2021 (Final Report)

The mission of the DOE Energy Frontier Research Centers CCDM (2014-2018) and CCM (2018-2021) was to theoretically develop, computationally apply, and experimentally validate electronic structure methods for all materials, with a focus on the complex materials, especially layered and two-dimensional materials, strongly-correlated materials, and liquid water. This was achieved by over 200 published journal articles authored by about 17 senior investigators from physics and chemistry and from theory, computation, and experiment, plus their collaborators. In particular, the Centers confirmed the predictive power of the SCAN (strongly constrained and appropriately normed) density functional, which was constructed to satisfy 17 known exact constraints and several appropriate norms. Without being fitted to real bonded systems, and at a modest computational cost, SCAN correctly predicted covalent, ionic, metallic, hydrogen, and van der Waals bonds in many challenging materials. SCAN gave an improved description of defects in semiconductors, surface properties of metals, seven phases of ice, liquid water, liquid and supercooled silicon, subtle structural distortions in ferroelectrics, formation energies and structural predictions for solids, and critical pressures for structural phase transitions. Perhaps most remarkably, SCAN correctly described some strongly-correlated materials that were previously believed to be beyond the reach of density-functional approximations. SCAN is the only density functional that correctly predicts the band gap closing under chemical doping of the cuprate high-temperature superconducting materials. SCAN also predicts a landscape of competing stripe and magnetic phases in the cuprates. For some materials with some codes, SCAN has convergence problems that are greatly reduced by the CCM-developed r 2 SCAN, without loss of accuracy or rigor. SCAN and r 2 SCAN still make some self-interaction error, which is greatly reduced by the CCDM/ CCM-developed local orbital scaling correction (LOSC). These Centers further proved that the fundamental energy gaps of a solid from an orbital energy difference and from total energy differences are the same for a large class of generalized Kohn-Sham (GKS) functionals, including SCAN and standard hybrid functionals, and that symmetry breaking arises when a dynamic density fluctuation drops to zero frequency. The Centers identified new mechanisms for catalysis in layered materials with ions intercalated between the layers, investigated charge density waves both in model systems and in real layered materials, studied changes of band gap with the number of layers, and explored topological ultrathin films, bent nanoribbons, and defects.

08 HYDROGEN↗

DOE OSTI2022

OLEDs on planarized light outcoupling-enhancing structures in plastic

Light extraction from OLEDs remains a challenge. While consumer demand for OLEDs in display technology continues to grow as prices decline, commercial use of OLEDs in solid state lighting (SSL) applications is lagging due to low light extraction, which results in low efficiency. Previous studies have been directed toward increasing the light extraction factor η out , but cost effective approaches that will enable high throughput and potential upscaling, as well as elucidation of the extraction process, are still lagging. One promising approach is the use of buried light extraction enhancing patterns that are planarized with a high refractive index (RI) layer. When adding substrate mode extracting means, the highest external quantum efficiencies (EQEs) were achieved using a complex approach of planarized vacuum nano holes. Here we present η out -enhancing planarized extraction structures (PES) in plastic. While plastic substrates currently present long-term stability issues and other drawbacks, as we show, they provide a tool for simple, inexpensive, and rapid generation of various enhancing structures that importantly can be transferred to the preferred rigid and flexible glass substrates. Moreover, plastic substrates are attractive for biomedical applications. The successful structures we present are easily scalable periodic corrugations, e.g., with pitch a ~ 4.25 µm and pitch/depth ratio a/h ~2.4 planarized by a layer of RI ~1.9, resulting in maximal EQEs exceeding 60% for a green OLED and 48.5% for a white OLED. Comparable increased EQEs were achieved for structures with a ~ 15 and 16 µm, and a/h ~ 2.1 and 4, respectively. Enhanced extraction was also observed with a very simply fabricated quasiperiodic nanohole array, and surprisingly, with a random shallow design. The latter is at variance with simulations based on diffraction only. Results are discussed in terms of a, h, and structural parameters together with scattering matrix simulations to assess the effect of various PES parameters and the nanoparticle-embedded planarizing layer on η out . The experiments and simulations indicate contributions of diffraction, reflection, and scattering to EQE enhancement.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Binary Cation Matrix Electrolyte and Its Effect on Solid Electrolyte Interphase Suppression and Evolution of Si Anode

An unstable solid electrolyte interphase (SEI) has been recognized as one of the biggest challenges to commercializing silicon (Si) anodes for high-energy-density batteries. This work thoroughly investigates a binary cation matrix of Mg 2+ +Li + electrolyte and its role in SEI development, suppression, and evolution of a Si anode. Findings demonstrate that introducing Mg ions dramatically reduces the SEI growth before lithiation occurs, primarily due to the suppression of solvent reduction, particularly ethylene carbonate (EC) reduction. The Mg 2+ alters the Li + cation solvation environment as EC preferably participates in the oxophyllic Mg 2+ solvation sheath, thereby altering the solvent reduction process, resulting in a distinct SEI formation mechanism. The initial SEI formation before lithiation is reduced by 70% in the electrolyte with the presence of Mg 2+ cations. While the SEI continues to develop in the postlithiation, the inclusion of Mg ions results in an approximately 80% reduction in the postlithiation SEI growth. Continuous electrochemical cycling reveals that Mg 2+ plays a crucial role in stabilizing the deep-lithiated Si phases, which effectively mitigates side reactions, resulting in controlled SEI growth and stable interphase while eliminating complex Li x Si y formation. Mg ions promote the development of a notably more rigid and homogeneous SEI, characterized by a reduced dissipation (ΔD) in the Mg 2+ +Li + ion matrix compared to the solely Li + system. In conclusion, this report reveals how the Mg 2+ +Li + ion matrix affects the SEI evolution, viscoelastic properties, and electrochemical behavior at the Si interface in real time, laying the groundwork for devising strategies to enhance the performance and longevity of Si-based next-generation battery systems.

25 ENERGY STORAGE↗

DOE OSTI2026

Comparative Dissolution of Iron-Bearing Minerals by Catecholate and Hydroxamate Siderophores under Oxic and Anoxic Conditions

Siderophores play a crucial role in biological iron (Fe) acquisition and mobilization by promoting Fe mineral and rock weathering. While the effects of the hydroxamate siderophore desferrioxamine B (DFOB) have been extensively studied, the role of catecholates in the dissolution of Fe mineral and rock under varying redox conditions remain limited. Moreover, despite Fe being one of the most redox-active metals, the siderophore-mediated redox transformations of solid-phase Fe and their impact on mineral dissolution are not well understood. Herein, this study systematically investigated dissolution behavior of both Fe(II) and Fe(III)-bearing minerals and rocks (Fe(II)- bearing basalt and olivine, and Fe(III)- bearing nontronite and goethite), by two structurally distinct biological siderophores, catecholate protochelin and hydroxamate DFOB, under both oxic and anoxic conditions. Batch experiments quantified Fe and transition metals (Mn, Ni, Zn, Mo) released from the tested minerals in the presence of siderophores. Throughout the dissolution experiments, siderophore concentrations and Fe-siderophore complexation in solutions were measured using UV-vis spectrometry. Fe redox changes under oxic and anoxic conditions by siderophores were determined, and mineral surface alterations following siderophore treatments were characterized through scanning electron microscopy (SEM) and time-of-flight secondary ion mass spectroscopy (ToF-SIMS). Results revealed distinct interplays of dissolution mechanisms, including ligand-exchange promoted dissolution and reductive dissolution, along with Fe(III) reduction and Fe(II) oxidation, contributing to the Fe(II)- and Fe(III)-rich mineral weathering under varying redox conditions. Under oxic conditions, both protochelin and DFOB enhanced Fe release from Fe(II)-rich basalt and olivine more effectively than from Fe(III)-rich minerals. DFOB induced greater Fe(II)-mineral dissolution than protochelin. This difference was attributed to a higher level of Fe(II) oxidation by DFOB in contrast to protochelin, as well as the protochelin oxidation with the loss of Fe binding groups (catechols). Under anoxic conditions, both siderophores significantly reduced Fe(III) in nontronite and goethite, with protochelin demonstrating substantially stronger Fe(III) reduction capacity than DFOB. However, Fe(III) reduction negatively impacted Fe release from Fe(III)-rich minerals. Instead, Fe release from Fe(II)-rich minerals was enhanced under anoxic conditions due to the absence of Fe(II) oxidation and labile Fe(II). Variations in siderophore adsorption also contributed to dissolution differences. Beyond iron, the release of transition metals from tested minerals was influenced by elemental contents, mineral compositions, and siderophore types, revealing distinct metal- and siderophore-dependent patterns. This systematic investigation highlights the roles of siderophores in Fe redox cycling and metal mobilization, enhancing our understanding of different siderophore behaviors in siderophore-mediated microbial metal acquisition within redox-dynamic environments, with implications for bioleaching industries and applications in agriculture and climate change mitigation.

Guo, Dongyi↗

DOE OSTI2022

Porting the Kitten Lightweight Kernel Operating System to RISC-V

Hardware design in high-performance computing (HPC) is often highly experimental. Exploring new designs is difficult and time-consuming, requiring lengthy vendor cooperation. RISC-V is an open-source processor ISA that improves the accessibility of chip design, including the ability to do hardware/software co-design using open-source hardware and tools. Co-design allows design decisions to easily flow across the hardware/software boundary and influence future design ideas. However, new hardware designs require corresponding software to drive and test them. Conventional operating systems like Linux are massively complex and modification is time-prohibitive. In this paper, we describe our port of the Kitten lightweight kernel operating system to RISC-V in order to provide an alternative to Linux for conducting co-design research. Kitten's small code base and simple resource management policies are well matched for quickly exploring new hardware ideas that may require radical operating system modifications and restructuring. Our evaluation shows that Kitten on RISC-V is functional and provides similar performance to Linux for single-core benchmarks. This provides a solid foundation for using Kitten in future co-design research involving RISC-V.

Gordon, Nick↗

DOE OSTI2023

Elongated galactan side chains mediate cellulose–pectin interactions in engineered Arabidopsis secondary cell walls

SUMMARY The plant secondary cell wall is a thickened matrix of polysaccharides and lignin deposited at the cessation of growth in some cells. It forms the majority of carbon in lignocellulosic biomass, and it is an abundant and renewable source for forage, fiber, materials, fuels, and bioproducts. The complex structure and arrangement of the cell wall polymers mean that the carbon is difficult to access in an economical and sustainable way. One solution is to alter the cell wall polymer structure so that it is more suited to downstream processing. However, it remains difficult to predict what the effects of this engineering will be on the assembly, architecture, and properties of the cell wall. Here, we make use of Arabidopsis plants expressing a suite of genes to increase pectic galactan chain length in the secondary cell wall. Using multi‐dimensional solid‐state nuclear magnetic resonance, we show that increasing galactan chain length enhances pectin–cellulose spatial contacts and increases cellulose crystallinity. We also found that the increased galactan content leads to fewer spatial contacts of cellulose with xyloglucan and the backbone of pectin. Hence, we propose that the elongated galactan side chains compete with xyloglucan and the pectic backbone for cellulose interactions. Due to the galactan topology, this may result in comparatively weak interactions and disrupt the cell wall architecture. Therefore, introduction of this strategy into trees or other bioenergy crops would benefit from cell‐specific expression strategies to avoid negative effects on plant growth.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Optimization of Solid Oxide Electrolysis Cell Systems Accounting for Long-Term Performance and Health Degradation

This study focuses on optimizing solid oxide electrolysis cell (SOEC) systems for efficient and durable long-term hydrogen (H2) production. While the elevated operating temperatures of SOECs offer advantages in terms of efficiency, they also lead to chemical degradation, which shortens cell lifespan. To address this challenge, dynamic degradation models are coupled with a steady-state, two-dimensional, non-isothermal SOEC model and steady-state auxiliary balance of plant equipment models, within the IDAES modeling and optimization framework. A quasi-steady state approach is presented to reduce model size and computational complexity. Long-term dynamic simulations at constant H2 production rate illustrate the thermal effects of chemical degradation. Dynamic optimization is used to minimize the lifetime cost of H2 production, accounting for SOEC replacement, operating, and energy expenses. Several optimized operating profiles are compared by calculating the Levelized Cost of Hydrogen (LCOH).

Giridhar, Nishant↗

DOE OSTI2024

Optimization of Solid Oxide Electrolysis Cell Systems Accounting for Long-Term Performance and Health Degradation

Giridhar, Nishant↗

DOE OSTI2024

Advanced thermal/environmental barrier coatings of high-entropy rare earth disilicates tuned by strong anharmonicity of Eu 2 Si 2 O 7

Advancing thermal/environmental barrier coating (TEBC) materials with integrated thermal-mechanical functions is paramount for safeguarding SiC-based ceramic matrix composites (CMCs) in high-efficiency gas turbines. Herein, we employ a synergistic approach, combining density functional theory (DFT) methods and combinatorial chemistry techniques, to design high-performance and low-cost RE 2 Si 2 O 7 (RE = rare earth elements) TEBC materials tailored for enhanced compatibility with SiC-based CMCs. Expanding on phase stability of alloying pure RE 2 Si 2 O 7 , the investigation extends to the mechanical and thermal properties of solid solution systems, including Er 1/2 Y 3/4 Yb 3/4 Si 2 O 7 , Gd 1/4 Er 1/4 Y 3/4 Yb 3/4 Si 2 O 7 , and Eu 1/4 Er 1/4 Y 3/4 Yb 3/4 Si 2 O 7 . The solid solution systems exhibit a major reduction in lattice thermal conductivity relative to their pure counterparts, achieving ultralow values of 0.25 to 0.39 W m −1 K −1 at 1500 K. Furthermore, the coefficients of thermal expansion (CTE) of these solid solutions are precisely tuned within the desired range for SiC (4.4 to 5.5 × 10 −6 K −1 ), while maintaining good mechanical properties. Here, in particular, the addition of Eu 2 Si 2 O 7 demonstrates to be an important variable to the tuning of CTE and lattice thermal conductivity by leveraging its strong anharmonicity, presenting a pioneering avenue for fine-tuning material properties. In summary, this research not only identifies promising TEBC materials with superior thermal properties, but also introduces a valuable computational material design methodology for the rapid discovery of complex materials for harsh environments.

36 MATERIALS SCIENCE↗

DOE OSTI2020

rlmolecule: A library for general-purpose material and molecular optimization using AlphaZero-style reinforcement learning

This library includes in-progress code for the optimization of materials and molecules using reinforcement learning. This project seeks to develop a generalized machine learning approach for optimizing targeted, and often complex, functional properties over the space of possible material structures, allowing faster identification of promising candidates. Electronic and transport properties of materials are determined by their molecular structure (for molecules) or their crystal structure (for in-organic crystalline materials). The atomic composition, bonding, and 3-D-spatial arrangement in these systems therefore represent a vast, discontinuous search space for optimal candidates. This library implements AlphaZero style reinforcement learning applied to two worked examples: the optimization of stable organic radicals for redox flow batteries, and the determination of stable electrolyte species for solid state batteries. The current code contains proof-of-concept results run on the Eagle HPC system, while the completed package will be a flexible tool for material optimization across of number of energy-relevant fields, which leverages cloud compute resources for the majority of the computational heavy lifting.

Biagioni, David↗