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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Artificial intelligence tools for enzyme engineering and metabolic engineering

Enzyme engineering and metabolic engineering drive innovation in energy biotechnology. In recent years, artificial intelligence (AI) has supported successful applications in designing effective enzymes and productive microbial cell factories. This review summarizes recent advances in enzyme redesign using protein language models, de novo enzyme design with generative models, and AI tools for engineering metabolism and related cellular phenotypes. Across these areas, AI models are shifting from single modality inputs to integrated representations of protein function, metabolic pathways, and cell states. We emphasize that unifying the diverse data representations across scales will be necessary for advancements in energy biotechnology.

Volk, Michael [Univ. of Illinois at Urbana-Champai↗
DOE OSTI2015

A Framework to Support the Fusion of Operation and Planning

The management of the nation’s power system has progressed to the point where the boundary lines between operations and planning are becoming blurred. The dynamic behavior of smart grid technologies brings pressures of incorporating the predictive capability from planning to enhance operations. These needs are requiring a smoother, better integrated interplay between the functional roles of planning and operations. This paper presents a framework to support the fusion of operation and planning. A case study of predicting the intra-hour deficiency in generation capability and ramping capacity and presenting the outputs to operators was conducted. The study shows the benefits of the fusion and the effectiveness of the framework. All the function blocks used in the study were built upon GridOPTICS Software System (GOSS), a software system middleware platform that facilitates deployment of new applications for the future power grid.

Framework↗
DOE OSTI2017

Implicit mesh discontinuous Galerkin methods and interfacial gauge methods for high-order accurate interface dynamics, with applications to surface tension dynamics, rigid body fluid–structure interaction, and free surface flow: Part I

In this two-part paper, a high-order accurate implicit mesh discontinuous Galerkin (dG) framework is developed for fluid interface dynamics, facilitating precise computation of interfacial fluid flow in evolving geometries. The framework uses implicitly defined meshes—wherein a reference quadtree or octree grid is combined with an implicit representation of evolving interfaces and moving domain boundaries—and allows physically prescribed interfacial jump conditions to be imposed or captured with high-order accuracy. Part one discusses the design of the framework, including: (i) high-order quadrature for implicitly defined elements and faces; (ii) high-order accurate discretisation of scalar and vector-valued elliptic partial differential equations with interfacial jumps in ellipticity coefficient, leading to optimal-order accuracy in the maximum norm and discrete linear systems that are symmetric positive (semi)definite; (iii) the design of incompressible fluid flow projection operators, which except for the influence of small penalty parameters, are discretely idempotent; and (iv) the design of geometric multigrid methods for elliptic interface problems on implicitly defined meshes and their use as preconditioners for the conjugate gradient method. Also discussed is a variety of aspects relating to moving interfaces, including: (v) dG discretisations of the level set method on implicitly defined meshes; (vi) transferring state between evolving implicit meshes; (vii) preserving mesh topology to accurately compute temporal derivatives; (viii) high-order accurate reinitialisation of level set functions; and (ix) the integration of adaptive mesh refinement. In part two, several applications of the implicit mesh dG framework in two and three dimensions are presented, including examples of single phase flow in nontrivial geometry, surface tension-driven two phase flow with phase-dependent fluid density and viscosity, rigid body fluid–structure interaction, and free surface flow. A class of techniques known as interfacial gauge methods is adopted to solve the corresponding incompressible Navier–Stokes equations, which, compared to archetypical projection methods, have a weaker coupling between fluid velocity, pressure, and interface position, and allow high-order accurate numerical methods to be developed more easily. Convergence analyses conducted throughout the work demonstrate high-order accuracy in the maximum norm for all of the applications considered; for example, fourth-order spatial accuracy in fluid velocity, pressure, and interface location is demonstrated for surface tension-driven two phase flow in 2D and 3D. Specific application examples include: vortex shedding in nontrivial geometry, capillary wave dynamics revealing fine-scale flow features, falling rigid bodies tumbling in unsteady flow, and free surface flow over a submersed obstacle, as well as high Reynolds number soap bubble oscillation dynamics and vortex shedding induced by a type of Plateau–Rayleigh instability in water ripple free surface flow. In conclusion, these last two examples compare numerical results with experimental data and serve as an additional means of validation; they also reveal physical phenomena not visible in the experiments, highlight how small-scale interfacial features develop and affect macroscopic dynamics, and demonstrate the wide range of spatial scales often at play in interfacial fluid flow.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Implicit mesh discontinuous Galerkin methods and interfacial gauge methods for high-order accurate interface dynamics, with applications to surface tension dynamics, rigid body fluid–structure interaction, and free surface flow: Part II

Here, in this two-part paper, a high-order accurate implicit mesh discontinuous Galerkin (dG) framework is developed for fluid interface dynamics, facilitating precise computation of interfacial fluid flow in evolving geometries. The framework uses implicitly defined meshes—wherein a reference quadtree or octree grid is combined with an implicit representation of evolving interfaces and moving domain boundaries—and allows physically prescribed interfacial jump conditions to be imposed or captured with high-order accuracy. Part one discusses the design of the framework, including: (i) high-order quadrature for implicitly defined elements and faces; (ii) high-order accurate discretisation of scalar and vector-valued elliptic partial differential equations with interfacial jumps in ellipticity coefficient, leading to optimal-order accuracy in the maximum norm and discrete linear systems that are symmetric positive (semi)definite; (iii) the design of incompressible fluid flow projection operators, which except for the influence of small penalty parameters, are discretely idempotent; and (iv) the design of geometric multigrid methods for elliptic interface problems on implicitly defined meshes and their use as preconditioners for the conjugate gradient method. Also discussed is a variety of aspects relating to moving interfaces, including: (v) dG discretisations of the level set method on implicitly defined meshes; (vi) transferring state between evolving implicit meshes; (vii) preserving mesh topology to accurately compute temporal derivatives; (viii) high-order accurate reinitialisation of level set functions; and (ix) the integration of adaptive mesh refinement. In part two, several applications of the implicit mesh dG framework in two and three dimensions are presented, including examples of single phase flow in nontrivial geometry, surface tension-driven two phase flow with phase-dependent fluid density and viscosity, rigid body fluid–structure interaction, and free surface flow. A class of techniques known as interfacial gauge methods is adopted to solve the corresponding incompressible Navier–Stokes equations, which, compared to archetypical projection methods, have a weaker coupling between fluid velocity, pressure, and interface position, and allow high-order accurate numerical methods to be developed more easily. Convergence analyses conducted throughout the work demonstrate high-order accuracy in the maximum norm for all of the applications considered; for example, fourth-order spatial accuracy in fluid velocity, pressure, and interface location is demonstrated for surface tension-driven two phase flow in 2D and 3D. Specific application examples include: vortex shedding in nontrivial geometry, capillary wave dynamics revealing fine-scale flow features, falling rigid bodies tumbling in unsteady flow, and free surface flow over a submersed obstacle, as well as high Reynolds number soap bubble oscillation dynamics and vortex shedding induced by a type of Plateau–Rayleigh instability in water ripple free surface flow. In these last two examples compare numerical results with experimental data and serve as an additional means of validation; they also reveal physical phenomena not visible in the experiments, highlight how small-scale interfacial features develop and affect macroscopic dynamics, and demonstrate the wide range of spatial scales often at play in interfacial fluid flow.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

An Immersed Boundary method with divergence-free velocity interpolation and force spreading

The Immersed Boundary (IB) method is a mathematical framework for constructing robust numerical methods to study fluid–structure interaction in problems involving an elastic structure immersed in a viscous fluid. The IB formulation uses an Eulerian representation of the fluid and a Lagrangian representation of the structure. The Lagrangian and Eulerian frames are coupled by integral transforms with delta function kernels. The discretized IB equations use approximations to these transforms with regularized delta function kernels to interpolate the fluid velocity to the structure, and to spread structural forces to the fluid. It is well-known that the conventional IB method can suffer from poor volume conservation since the interpolated Lagrangian velocity field is not generally divergence-free, and so this can cause spurious volume changes. In practice, the lack of volume conservation is especially pronounced for cases where there are large pressure differences across thin structural boundaries. The aim of this paper is to greatly reduce the volume error of the IB method by introducing velocity-interpolation and force-spreading schemes with the properties that the interpolated velocity field in which the structure moves is at least $\mathscr{C}$ 1 and satisfies a continuous divergence-free condition, and that the force-spreading operator is the adjoint of the velocity-interpolation operator. We confirm through numerical experiments in two and three spatial dimensions that this new IB method is able to achieve substantial improvement in volume conservation compared to other existing IB methods, at the expense of a modest increase in the computational cost. Further, the new method provides smoother Lagrangian forces (tractions) than traditional IB methods. Finally, the method presented here is restricted to periodic computational domains. Its generalization to non-periodic domains is important future work.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Development of a lab-scale, high-resolution, tube-generated X-ray computed-tomography system for three-dimensional (3D) materials characterization

The design and construction of a modular high resolution X-ray computed tomography (XCT) system is highlighted in this paper. The design approach is detailed for meeting a specified set of instrument performance goals tailored towards experimental versatility and high resolution imaging. The XCT tool is unique in the detector and X-ray source design configuration, enabling control in the balance between detection efficiency and spatial resolution. The system package is also unique: The sample manipulation approach implemented enables a wide gamut of in situ experimentation to analyze structure evolution under applied stimulus, by optimizing scan conditions through a high degree of controllability. The component selection and design process is detailed: Incorporated components are specified, custom designs are shared, and the approach for their integration into a fully functional XCT scanner is provided. Custom designs discussed include the dual-target X-ray source cradle which maintains position and trajectory of the beam between the two X-ray target configurations with respect to a scintillator mounting and positioning assembly and the imaging sensor, as well as a novel large-format X-ray detector with enhanced adaptability. The instrument is discussed from an operational point of view, including the details of data acquisition and processing implemented for 3D imaging via micro-CT. The performance of the instrument is demonstrated on a silica-glass particle/hydroxyl-terminated-polybutadiene (HTPB) matrix binder PBX simulant. Post-scan data processing, specifically segmentation of the sample's relevant microstructure from the 3D reconstruction, is provided to demonstrate the utility of the instrument. - Highlights: • Custom built X-ray tomography system for microstructural characterization • Detector design for maximizing polychromatic X-ray detection efficiency • X-ray design offered for maximizing X-ray flux with respect to imaging resolution • Novel lab-scale XCT data acquisition and data processing methods • 3D characterization of glass-bead mock plastic-bonded-explosive stimulant.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Note on the definitions of branching ratios of overlapping resonances

Branching ratios for the decay of hadrons with large width or near thresholds depend on their definition. We test different definitions and show that rather different branching ratios can be obtained. For wide resonances and for sequential decays with wide intermediate resonances, integration over the spectral functions is mandatory. The tests are performed exploiting the latest solution of the Bonn-Gatchina multi-channel analysis and published values for residues of light scalar mesons. For a resonance overlapping with a threshold, in case its pole lies in a non-adjacent sheet, we show how the total width, needed for the branching ratios, does not correspond to the imaginary part of the pole position. We use the Madrid-Krakow dispersive parameterizations to illustrate this situation with the f 0 (980).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Valued peaks: Sustainable water allocation for small hydropower plants in an era of explicit ecological needs

Optimizing hydropower operations to balance economic profitability and support functioning ecosystem services is integral to river management policy. In this article, we propose a dynamic, constrained optimization framework for small hydropower plants (SHPs) to evaluate trade-offs between economic profitability and socio-ecological requirements. Specifically, we examine the balance between short-term losses in hydropower generation and the potential for compensatory benefits in the form of revenue from recreational ecosystem services, irrespective of the direct beneficiary. Our framework integrates a fish habitat model, a hydropower optimization model, and a recreational ecosystem service estimate to evaluate different environmental flow scenarios. The optimization process gives three outflow release scenarios, informed by previous streamflow realisations (dam inflow), and designed environmental flow constraints. The framework is applied and tested for the river Kuusinkijoki in North-eastern Finland, which is a habitat for migratory brown trout and grayling populations. We show that the revenue loss due to the environmental flow constraints arises through a reduction in revenue per generated energy unit and through a reduction in turbine efficiency. Additionally, the simulation results reveal that all the designed environmental flow constraints cannot be met simultaneously. Under the environmental flow scenario with both minimum flow and flow ramping rate constraints, the annual hydropower revenue decreases by 16.5 %. An annual increase of 8 % in recreational fishing visits offsets the revenue loss. In conclusion, the developed framework provides knowledge of the costs and benefits of hydropower environmental flow constraints and guides the prioritizing process of environmental measures.

13 HYDRO ENERGY↗
DOE OSTI2024

Localized Conduction Channels in Memristors

Since the early 2000s, the impending end of Moore’s scaling, as the physical limits to shrinking transistors have been approached, has fueled interest in improving the functionality and efficiency of integrated circuits by employing memristors or two-terminal resistive switches. Formation (or avoidance) of localized conducting channels in many memristors, often called “filaments”, has been established as the basis for their operation. While we understand some qualitative aspects of the physical and thermodynamic origins of conduction localization, there are not yet quantitative models that allow us to predict when they will form or how large they will be. Here, in this work, we compile observations and explanations of channel formation that have appeared in the literature since the 1930s, show how many of these seemingly unrelated pieces fit together, and outline what is needed to complete the puzzle. This understanding will be a necessary predictive component for the design and fabrication of post-Moore’s-era electronics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Lasing from Finite Plasmonic Nanoparticle Lattices

Small lasers can generate coherent light for integrated photonics, in-vivo cellular imaging, and solid-state lighting. Unlike conventional lasers, plasmonic lasers can generate coherent light at sub-wavelength scales, although cavity architectures based on metal films and semiconducting gain exhibit large radiative losses and lack directional emission. In contrast, two-dimensional (2D) metal nanoparticle arrays surrounded by organic dyes can support lasing with high directionality at room temperature. Yet, the relationship between the number of nanoparticles in a finite lattice and their lasing emission characteristics is unknown. Here we show that the number of units in 2D gold nanoparticle lattices is critical to generate robust cavity resonances and lasing emission. Narrower lattice plasmons associated with stronger electromagnetic near fields are observed as nanoparticle number increases. Experimentally, we demonstrate lasing from a 30x30 nanoparticle lattice. Semi-quantum modeling indicates lower lasing thresholds and faster population inversion dynamics with higher nanoparticle numbers. These findings indicate that finite lattices of nanoparticles integrated with gain can function as independent, coherent light sources for optical multiplexing and lab-on-a-chip applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2013

Enhanced Photochemical Hydrogen Production by a Molecular Diiron Catalyst Incorporated into a Metal-Organic Framework

A molecular proton reduction catalyst [FeFe](dcbdt)(CO) 6 (1, dcbdt = 1,4-dicarboxylbenzene-2,3-dithiolate) with structural similarities to [FeFe]-hydrogenase active sites has been incorporated into a highly robust Zr(IV)-based metal–organic framework (MOF) by postsynthetic exchange (PSE). The PSE protocol is crucial as direct solvothermal synthesis fails to produce the functionalized MOF. The molecular integrity of the organometallic site within the MOF is demonstrated by a variety of techniques, including X-ray absorption spectroscopy. In conjunction with [Ru(bpy) 3 ] 2+ as a photosensitizer and ascorbate as an electron donor, MOF-[FeFe](dcbdt)(CO) 6 catalyzes photochemical hydrogen evolution in water at pH 5. The immobilized catalyst shows substantially improved initial rates and overall hydrogen production when compared to a reference system of complex 1 in solution. Improved catalytic performance is ascribed to structural stabilization of the complex when incorporated in the MOF as well as the protection of reduced catalysts 1 – and 1 2– from undesirable charge recombination with oxidized ascorbate.

Pullen, Sonja↗
DOE OSTI2014

Proteogenomic characterization of human colon and rectal cancer

We analyzed proteomes of colon and rectal tumors previously characterized by the Cancer Genome Atlas (TCGA) and performed integrated proteogenomic analyses. Protein sequence variants encoded by somatic genomic variations displayed reduced expression compared to protein variants encoded by germline variations. mRNA transcript abundance did not reliably predict protein expression differences between tumors. Proteomics identified five protein expression subtypes, two of which were associated with the TCGA "MSI/CIMP" transcriptional subtype, but had distinct mutation and methylation patterns and associated with different clinical outcomes. Although CNAs showed strong cis- and trans-effects on mRNA expression, relatively few of these extend to the protein level. Thus, proteomics data enabled prioritization of candidate driver genes. Our analyses identified HNF4A, a novel candidate driver gene in tumors with chromosome 20q amplifications. Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords novel insights into cancer biology.

: colorectal cancer, shotgun proteomics, proteogen↗
DOE OSTI2018

Recon3D enables a three-dimensional view of gene variation in human metabolism

Genome-scale network reconstructions have helped uncover the molecular basis of metabolism. Here we present Recon3D, a computational resource that includes three-dimensional (3D) metabolite and protein structure data and enables integrated analyses of metabolic functions in humans. We use Recon3D to functionally characterize mutations associated with disease, and identify metabolic response signatures that are caused by exposure to certain drugs. Recon3D represents the most comprehensive human metabolic network model to date, accounting for 3,288 open reading frames (representing 17% of functionally annotated human genes), 13,543 metabolic reactions involving 4,140 unique metabolites, and 12,890 protein structures. As a result, these data provide a unique resource for investigating molecular mechanisms of human metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Author Correction: Expanded encyclopaedias of DNA elements in the human and mouse genomes

In the version of this article initially published, two members of the ENCODE Project Consortium were missing from the author list. Rizi Ai (Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, USA) and Shantao Li (Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA) are now included in the author list. These errors have been corrected in the online version of the article.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A caloritronics-based Mott neuristor

Abstract Machine learning imitates the basic features of biological neural networks at a software level. A strong effort is currently being made to mimic neurons and synapses with hardware components, an approach known as neuromorphic computing. While recent advances in resistive switching have provided a path to emulate synapses at the 10 nm scale, a scalable neuron analogue is yet to be found. Here, we show how heat transfer can be utilized to mimic neuron functionalities in Mott nanodevices. We use the Joule heating created by current spikes to trigger the insulator-to-metal transition in a biased VO 2 nanogap. We show that thermal dynamics allow the implementation of the basic neuron functionalities: activity, leaky integrate-and-fire, volatility and rate coding. This approach could enable neuromorphic hardware to take full advantage of the rapid advances in memristive synapses, allowing for much denser and complex neural networks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

MISPR : an open-source package for high-throughput multiscale molecular simulations

Computational tools provide a unique opportunity to study and design optimal materials by enhancing our ability to comprehend the connections between their atomistic structure and functional properties. However, designing materials with tailored functionalities is complicated due to the necessity to integrate various computational-chemistry software (not necessarily compatible with one another), the heterogeneous nature of the generated data, and the need to explore vast chemical and parameter spaces. The latter is especially important to avoid bias in scattered data points-based models and derive statistical trends only accessible by systematic datasets. Here, we introduce a robust high-throughput multi-scale computational infrastructure coined MISPR (Materials Informatics for Structure–Property Relationships) that seamlessly integrates classical molecular dynamics (MD) simulations with density functional theory (DFT). By enabling high-performance data analytics and coupling between different methods and scales, MISPR addresses critical challenges arising from the needs of automated workflow management and data provenance recording. The major features of MISPR include automated DFT and MD simulations, error handling, derivation of molecular and ensemble properties, and creation of output databases that organize results from individual calculations to enable reproducibility and transparency. In this work, we describe fully automated DFT workflows implemented in MISPR to compute various properties such as nuclear magnetic resonance chemical shift, binding energy, bond dissociation energy, and redox potential with support for multiple methods such as electron transfer and proton-coupled electron transfer reactions. The infrastructure also enables the characterization of large-scale ensemble properties by providing MD workflows that calculate a wide range of structural and dynamical properties in liquid solutions. MISPR employs the methodologies of materials informatics to facilitate understanding and prediction of phenomenological structure–property relationships, which are crucial to designing novel optimal materials for numerous scientific applications and engineering technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

High-performance ammonia oxidation catalysts for anion-exchange membrane direct ammonia fuel cells

Low-temperature direct ammonia fuel cells (DAFCs) use carbon-neutral ammonia as a fuel, which has attracted increasing attention recently due to ammonia's low source-to-tank energy cost, easy transport and storage, and wide availability. However, current DAFC technologies are greatly limited by the kinetically sluggish ammonia oxidation reaction (AOR) at the anode. Herein, we report an AOR catalyst, in which ternary PtIrZn nanoparticles with an average size of 2.3 ± 0.2 nm were highly dispersed on a binary composite support comprising cerium oxide (CeO 2 ) and zeolitic imidazolate framework-8 (ZIF-8)-derived carbon (PtIrZn/CeO 2 -ZIF-8) through a sonochemical-assisted synthesis method. Additionally, the PtIrZn alloy, with the aid of abundant OH ad provided by CeO 2 and uniform particle dispersibility contributed by porous ZIF-8 carbon (surface area: ~600 m 2 g -1 ), has shown highly efficient catalytic activity for the AOR in alkaline media, superior to that of commercial PtIr/C. The rotating disk electrode (RDE) results indicate a lower onset potential (0.35 vs. 0.43 V), relative to the reversible hydrogen electrode at room temperature, and a decreased activation energy (~36.7 vs. 50.8 kJ mol -1 ) relative to the PtIr/C catalyst. Notably, the PtIrZn/CeO 2 -ZIF-8 catalyst was assembled with a high-performance hydroxide anion-exchange membrane to fabricate an alkaline DAFC, reaching a peak power density of 91 mW cm -2 . Unlike in aqueous electrolytes, supports play a critical role in improving uniform ionomer distribution and mass transport in the anode. PtIrZn nanoparticles on silicon dioxide (SiO 2 ) integrated with carboxyl-functionalized carbon nanotubes (CNT–COOH) were further studied as the anode in a DAFC. A significantly enhanced peak power density of 314 mW cm -2 was achieved. Density functional theory calculations elucidated that Zn atoms in the PtIr alloy can reduce the theoretical limiting potential of *NH 2 dehydrogenation to *NH by ~0.1 V, which can be attributed to a Zn-modulated upshift of the Pt–Ir d-band that facilitates the N–H bond breakage.

25 ENERGY STORAGE↗
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↗