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DOE OSTI2026

SEED: Semantic Energy Exploration and Discovery

The Bioenergy Knowledge Discovery Framework (KDF) hosts a vast repository of specialized data, yet traditional keyword-based search methods often struggle to provide direct answers, requiring significant domain expertise and manual effort to filter through raw documents. To overcome these barriers, this software introduces a semantic search engine that enables both specialists and non-specialists to query the KDF using natural language. By shifting from rigid keyword matching to intent-based retrieval, the tool automatically identifies and ranks the most relevant sources within the database. The system functions by processing natural language queries to extract the most pertinent information, delivering an AI-generated plain-language summary alongside exact supporting quotes from retrieved documents. This integrated approach provides users with immediate, evidence-based answers while eliminating the need for exhaustive manual review. By surfacing direct insights and contextual evidence, the software enhances the usability of existing KDF resources and democratizes access to complex bioenergy data. Ultimately, this semantic search solution accelerates the discovery process and supports faster, more informed decision-making across the bioenergy sector.

Pan, Meiyu (Melrose) [Oak Ridge National Laborator↗

DOE OSTI2025

Micro-Mechanically Guided High-Throughput Alloy Design Exploration Towards Metastability-Induced H Embrittlement Resistance

We develop a high-throughput approach for studying H embrittlement (HE)-resistance in alloys, which is based on combinatorial compositional screening of metastability effects by in situ scanning electron microscopy H-analyses. The project objective included: (i) technique development of high-throughput screening (HTS) for HE-resistance, (ii) discovery of new metallic materials with superior HE-resistance, (iii) Multiscale verification of HE-resistance of the new alloys and H-barrier layers, from atomic scale to an engineering scale. The investigation focused on a model system that enables exploration of different metastable states in Fe-based complex-concentrated alloys. Composition spread islands with hundreds of varying compositions are fabricated on a single substrate using a combinatorial co-sputtering technique. To screen these alloys, we developed and employed a home-built SEM-based integrated analysis system capable of characterizing H-permeability, H-trapping, H-influence on mechanical properties, and other material properties, as well as atomistic to continuum simulations to study the underlying physics.

08 HYDROGEN↗

DOE OSTI2023

Electronic Structure and Mechanical Properties of Solvated Montmorillonite Clay Using Large-Scale DFT Method

Montmorillonite clay (MMT) has been widely used in engineering and environmental applications as a landfill barrier and toxic waste repository due to its unique property as an expandable clay mineral that can absorb water easily. This absorption process rendered MMT to be highly exothermic due to electrostatic interactions among molecules and hydrogen bonds between surface atoms. A detailed study of a large supercell model of structural clay enables us to predict long-term nuclear waste storage. Herein, a large solvent MMT model with 4071 atoms is studied using ab initio density functional theory. The DFT calculation and analysis clarify the important issues, such as bond strength, solvation effect, elasticity, and seismic wave velocities. These results are compared to our previous study on crystalline MMT (dry). The solvated MMT has reduced shear modulus (G), bulk modulus (K), and Young’s modulus (E). We observe that the conduction band (CB) in the density of states (DOS) of solvated MMT model has a single, conspicuous peak at –8.5 eV. Moreover, the atom-resolved partial density of states (PDOS) summarizes the roles played by each atom in the DOS. These findings illuminate numerous potential sophisticated applications of MMT clay.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Silicon Dioxide Deposited Using Atmospheric Pressure Plasma Chemical Vapor Deposition for Improved Adhesion and Water Intrusion Resistance for Lightweight Manufacturing

This work aims to demonstrate the barrier coating, and adhesion promoting properties of silica-based coatings deposited using an atmospheric pressure plasma torch (APPT). This is achieved by applying an industrial grade adhesive to silica thin films deposited, on the surfaces to be joined, using atmospheric pressure plasma chemical vapor deposition (APP-CVD), to make single joint lap shear samples of different metal combinations commonly found in lightweight manufacturing such as aluminum and magnesium as well as steel. To deposit these thin films, two separate silicon based organic precursors, hexamethyldisiloxane (HMDSO), and tetraehylorthosilicate (TEOS), are used. Here, samples are bonded using DuPont Betamate 1486 adhesive, and the lap shear results for these films are compared to the lap shear results of a chemically cleaned control using the same adhesive. The APPT uses a microwave power supply and gas mixtures of N 2 and Ar. The adhesion of the films are tested using lap shear, and elevated temperature water soaks are conducted on the joints as well to simulate environmental exposure. Lap shear results from samples with silica thin films max shear stress are 25%-115% increase compared to control samples depending on material. After exposure to water soak the max shear strength of the joints decreased by less than 15%, which demonstrates the films capabilities as a water barrier. Film morphology is examined using Scanning Electron Microscopy (SEM), and the film’s composition and approximate thickness are obtained using Rutherford Backscattering Spectroscopy (RBS).

36 MATERIALS SCIENCE↗

DOE OSTI2020

High-energy X-ray phase analysis of CMAS-infiltrated 7YSZ thermal barrier coatings: Effect of time and temperature

Calcium–magnesium–alumino-silicate (CMAS) particulates enter the aero-engine in a sandy environment, melt and infiltrate into 7 wt% yttria-stabilized zirconia (7YSZ) thermal barrier coatings (TBCs), reducing their lifetime. This leads to chemical degradation in 7YSZ accompanied by tetragonal to monoclinic phase transformation upon cooling. In this work, electron-beam physical vapor deposition coatings were infiltrated with a synthetic CMAS. Here, synchrotron X-ray diffraction measurements show that CMAS infiltration at 1250 °C has about 43% higher monoclinic phase volume fraction (PVF) at the coating surface compared to 1225 °C and remains consistently higher throughout the coating depth. Additionally, the increase in annealing time from 1 to 10 h results in a 31% higher monoclinic phase at the surface. Scanning electron microscopy revealed the presence of globular monoclinic phases corresponding spatially with the above findings. These results resolve the impact of time and temperature on CMAS infiltration kinetics which is important for mitigation.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Experimental Demonstration of Charge-Balanced GaN Super-Heterojunction Schottky Barrier Diode Capable of 2.8 kV Switching

This letter reports an experimental demonstration of charge-balanced GaN super-heterojunction Schottky barrier diodes (SHJ-SBDs). Charge balance between the n-type delta-doping and the p-type doping was achieved by adjusting the thickness of the pGaN. Furthermore, this device structure enabled scaling of breakdown voltage to over 3 kV, and dynamic switching up to 2.8 kV without using any field-plate.

42 ENGINEERING↗

DOE OSTI2021

12.5 kV GaN Super-Heterojunction Schottky Barrier Diodes

In this work, we report GaN super-heterojunction Schottky barrier diodes (SHJ-SBDs) with substantially improved performance. Metal-2DEG sidewall n-ohmic contacts were deployed to achieve low contact resistance of 0.75 Ω · mm, avoiding the risk of abnormally high contact resistance caused by inaccurate etch depth control. A pGaN notch formed near the cathode successfully eliminated excessive hole conduction caused by the sidewall n-ohmic contact. Isolation was improved by a high-energy Al implantation step. The resulting SHJ-SBD exhibited a breakdown voltage (BV) of 12.5 kV and a specific ON-resistance of 100.8 mΩ · cm 2 .

42 ENGINEERING↗

DOE OSTI2025

A Markov chain Monte Carlo (MCMC) Bayesian inference approach to analyze apparent activation barriers and reaction orders from microreactor data

Statistical analysis of steady-state catalytic kinetic data is often limited by data sparsity due to the slow pace at which the data is collected. Data sparsity and limitations in statistical analysis make it difficult to differentiate between mechanistic models and catalytic sites. A Bayesian inference tool is reported for catalysis researchers to estimate error in the determination of reaction orders from steady state microreactor data. The benefits of a Bayesian inference approach are discussed, as an alternative to the more common frequentist approach. The approach incorporates prior knowledge of the system and the data collected to form an error estimate on reaction orders. We investigated the effects of three distinct data treatments—individual fitting of trials, pooled analysis, and constrained regression methods—on the precision and uncertainty of reaction order determinations. To assess the robustness of our findings, we conducted sensitivity analyses to evaluate the influence of Bayesian parameters on uncertainty estimation. Additionally, we utilized synthetic data to illustrate how data quality impacts the precision of uncertainty assessments. We show Bayesian analysis can obtain a more precise estimation of error with a sparse data set than a frequentist analysis. Finally, this work provides strong evidence that the adoption of Bayesian analysis of kinetic data may help researchers make more precise arguments as to the strength of their evidence for a particular mechanistic hypothesis, or in comparing across different catalysts.

42 ENGINEERING↗

DOE OSTI2022

Thermally Grown Oxide Stress in PS-PVD and EB-PVD Thermal Barrier Coatings Observed at Various Lifetimes Via Synchrotron X-ray Diffraction

The current standard application method for thermal barrier coatings (TBCs) on turbine blades for jet engines is electron-beam physical vapor deposition (EB-PVD) due to its high strain tolerance and low thermal conductivity. An emerging deposition method, plasma-spray physical vapor deposition (PS-PVD), presents an opportunity for a tailorable microstructure, and non-line-of-sight deposition that is faster and less expensive. To compare the lifetime behavior of both PS-PVD and EB-PVD coatings, samples subjected to 300 and 600 thermal cycles were measured during a 1 h thermal cycle to determine the strains, which were converted to stress, in the thermally grown oxide (TGO) layer of the TBCs using synchrotron X-ray diffraction (XRD). Room temperature XRD measurements indicated among samples that PS-PVD coatings experienced greater variation in in-plane room temperature strain in the TGO after cycling than the EB-PVD coatings. In-situ XRD measurements indicated similar high-temperature strain and no spallation after 600 thermal cycles for both coatings. Further, microscopy imaging after cycling showed greater rumpling in PS-PVD coatings that led to different failure modes between the two coatings’ TGO layers. The tailorability of PS-PVD coatings allows for adjustments in the processing parameters to improve their overall performance after aging and bridge the differences between the two deposition methods.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Theoretical Prediction of Thermal Expansion Anisotropy for Y 2 Si 2 O 7 Environmental Barrier Coatings Using a Deep Neural Network Potential and Comparison to Experiment

Environmental barrier coatings (EBCs) are an enabling technology for silicon carbide (SiC)-based ceramic matrix composites (CMCs) in extreme environments such as gas turbine engines. However, the development of new coating systems is hindered by the large design space and difficulty in predicting the properties for these materials. Density Functional Theory (DFT) has successfully been used to model and predict some thermodynamic and thermo-mechanical properties of high-temperature ceramics for EBCs, although these calculations are challenging due to their high computational costs. In this work, we use machine learning to train a deep neural network potential (DNP) for Y 2 Si 2 O 7 , which is then applied to calculate the thermodynamic and thermo-mechanical properties at near-DFT accuracy much faster and using less computational resources than DFT. We use this DNP to predict the phonon-based thermodynamic properties of Y 2 Si 2 O 7 with good agreement to DFT and experiments. We also utilize the DNP to calculate the anisotropic, lattice direction-dependent coefficients of thermal expansion (CTEs) for Y 2 Si 2 O 7 . Molecular dynamics trajectories using the DNP correctly demonstrate the accurate prediction of the anisotropy of the CTE in good agreement with the diffraction experiments. In the future, this DNP could be applied to accelerate additional property calculations for Y 2 Si 2 O 7 compared to DFT or experiments.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Characterization of SiO 2 Thermally Grown Oxide Stress Evolution of EBCs with Al-Containing Dopants

SiC/SiC ceramic matrix composites (CMCs) are desired for use in combustion environments to achieve higher turbine operating temperatures. However, CMCs require environmental barrier coatings (EBCs) for protection from the gas environment. EBC systems are known to primarily fail through coating delamination via growth of a thermally grown oxide (TGO) at the EBC—silicon bond coating interface when exposed to steam, which accelerates the TGO growth rate. The TGO undergoes a phase transformation during thermal cycling, which results in stresses that may encourage EBC spallation. Yb-silicate EBCs with mullite and yttrium aluminum garnet (YAG) dopant additions were deposited on SiC substrates with a Si intermediate bond coating and exposed to thermal cycling in steam at 1350 °C. The impact of Al dopant additions on the TGO growth rate and the SiO 2 phase transformation was assessed. Photo-stimulated luminescence spectroscopy (PSLS) was used to characterize the Al-containing phases and to measure stress evolution in the EBC following exposure using the stress-induced peak shift of the R-lines of mullite. Raman microscopy was used to map the stresses in the Si bond coating following exposure. It was found that the TGO phase transformation upon cooling increased compressive stress in the Si bond coating within 15 µm of the TGO.

Building Materials↗

DOE OSTI2021

Development of an Efficient Conjugate Heat Transfer Modeling Framework to Optimize Mixing-Limited Combustion of Ethanol in a Diesel Engine

Mixing controlled combustion of alcohol fuels has been identified as a promising technology based on their low propensity for particulate and NOx production, but the higher heats of vaporization and auto-ignition temperatures of these fuels make their direct use in diesel engine architectures a challenge. To realize the potential of alcohol-fueled combustion, a computational fluid dynamics (CFD) modeling framework is developed, validated, and exercised to identify designs that maximize engine thermal efficiency. To evaluate the use of thermal barrier coatings (TBCs), a simplified one-dimensional (1D) conjugate heat transfer (CHT) modeling framework is employed. The addition of the 1D CHT model only increases the computational expense by 15% relative to traditional approaches, yet offers more accurate heat transfer predictions over constant temperature boundary conditions. The validated model is then used to explore a range of injector orientations and piston bowl geometries. Using a design of experiments (DoE) approach, several designs were identified that improved fuel-air mixing, shortened the combustion duration, and increased thermal efficiency. The most promising design was fabricated and tested in a Caterpillar 1Y3700 single-cylinder oil test engine (SCOTE). Engine testing confirmed the findings from the CFD simulations and found that the co-optimized injector and piston bowl design yielded over 2-percentage point increase in thermal efficiency at the same equivalence ratio (0.96) and over 6-percentage point increase at the same engine load (10.1 bar indicated mean effective pressure (IMEP)), while satisfying design constraints for peak pressure and maximum pressure rise rate.

Magnotti, Gina M.↗

DOE OSTI2021

Nuclear and chloroplast genome engineering of a productive non-model alga Desmodesmus armatus: Insights into unusual and selective acquisition mechanisms for foreign DNA

Despite the tremendous potential of algae to contribute to a future bioeconomy, there are practical and theoretical limitations to how well naturally sourced species and strains can perform in an outdoor setting. The application of biotechnology to modulate and engineer algae metabolism or to increase performance, resilience, or produce novel compounds, offers opportunities to overcome some of the major commercialization barriers. There are numerous approaches reported in the literature having variable success on genetic engineering of algae with non-model algae often presenting unique challenges to genetic engineering. We report here on successful nuclear and chloroplast genomic integration of selection marker resistance in the non-model alga Desmodesmus armatus. Nuclear transformation was accomplished using both electroporation and Agrobacterium-mediated approaches. However, in all surviving transformants, DNA integration was accompanied by excision and/or rearrangement of the gene of interest and fluorescence reporter coding sequences. Similarly, chloroplast transformation was successfully accomplished using a biolistic DNA delivery method. For these transformants, we also observed off-target mutations in the chloroplast genome, not previously observed in other, more routinely used, algae species. Finally, we present insights into potential mechanisms for these observed truncations, rearrangements, and mutations in D. armatus.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Prototype Development for MBSE-Driven Digital Environment at Fermilab

Complex projects like Fermilab s accelerators and detectors involve thousands of interdependent components and requirements, making traditional documentation hard to keep consistent and often causing rework. Model-Based Systems Engineering (MBSE) tackles this by representing the system as a digital, queryable model. While widely used in aerospace and safety-critical industries, MBSE adoption has been limited elsewhere due to steep learning curves and high costs. This project investigates how a web-first, low-code MBSE stack can reduce those barriers and offer an accessible, unified source of truth for engineers and physicists.

Valle, Diego Pedro (ORCID:0009000865900663)↗

DOE OSTI2023

Toughening Brittle Bio‐P3HB with Synthetic P3HB of Engineered Stereomicrostructures

Abstract Poly(3‐hydroxybutyrate) (P3HB), a biologically produced, biodegradable natural polyester, exhibits excellent thermal and barrier properties but suffers from mechanical brittleness, largely limiting its applications. Here we report a mono‐material product design strategy to toughen stereoperfect, brittle bio or synthetic P3HB by blending it with stereomicrostructurally engineered P3HB. Through tacticity ([ mm ] from 0 to 100 %) and molecular weight ( M n to 788 kDa) tuning, high‐performance synthetic P3HB materials with tensile strength to ≈30 MPa, fracture strain to ≈800 %, and toughness to 126 MJ m −3 (>110× tougher than bio‐P3HB) have been produced. Physical blending of the brittle P3HB with such P3HB in 10 to 90 wt % dramatically enhances its ductility from ≈5 % to 95–450 % and optical clarity from 19 % to 85 % visible light transmittance while maintaining desirably high elastic modulus (>1 GPa), tensile strength (>35 MPa), and melting temperature (160–170 °C). This P3HB‐toughening‐P3HB methodology departs from the traditional approach of incorporating chemically distinct components to toughen P3HB, which hinders chemical or mechanical recycling, highlighting the potential of the mono‐material product design solely based on biodegradable P3HB to deliver P3HB materials with diverse performance properties.

Zhang, Zhen↗

DOE OSTI2023

Toughening Brittle Bio‐P3HB with Synthetic P3HB of Engineered Stereomicrostructures

Chemistry↗

DOE OSTI2021

Exploiting Fixed Charge to Control Schottky Barrier Height in Si|Al 2 O 3 |MoO x – based Tunnel Diodes

The insertion of a tunneling atomic layer deposited (ALD) Al 2 O 3 film between MoO x and p-type Si has been studied to investigate Schottky barrier height tunability with varied negative fixed charge density. This work seeks to increase the hole-selectivity of MoO x -based contacts through manipulation of interface fixed charge. Fixed charge density and interface trap state densities are determined as a function of alumina processing conditions in metal-oxide-semiconductor capacitors (MOSCAPs). Schottky barrier heights were determined from Mott-Schottky analysis of tunnel diodes. An alumina deposition temperature of 80°C and post-deposition annealing at 425°C yielded the highest magnitude of negative fixed charge density (-3.5 × 10 12 q . cm –2 ). High deposition temperature and/or post-deposition annealing produced the lowest interface trap state density (1 × 10 12 eV -1 . cm –2 ). On p-type silicon, Schottky barrier height minimization was not clearly correlated with increasing fixed charge density. However, on n-type silicon, a significant increase in Schottky barrier height was evident (~0.8 eV to > 1 eV) and is attributed to the large negative fixed charge. Here, the findings from this work indicate that Schottky barrier height in carrier selective contacts can be tuned by electrostatic engineering of the SiO x |Al 2 O 3 interface.

aluminum oxide↗

DOE OSTI2025

Prenol production in a microbial host via the “Repass” Pathways

Prenol and isoprenol are promising advanced biofuels and serve as biosynthetic precursors for pharmaceuticals, fragrances, and other industrially relevant compounds. Despite engineering improvements that circumvent intermediate cytotoxicity and lower energy barriers, achieving high titer ‘mevalonate (MVA)-derived’ prenol has remained elusive. Difficulty in selective prenol production stems from the necessary isomerization of isopentenyl diphosphate (IPP) to dimethylallyl diphosphate (DMAPP) as well as the intrinsic toxicity of these diphosphate precursors. Here, the expression of specific isopentenyl monophosphate kinases with model-guided enzyme substitution of diphosphate isomerases and phosphatases enabled selective cycling of monophosphates and diphosphates, dramatically improving prenol titers and selectivity in Escherichia coli. Pairing this approach with the canonical MVA pathway resulted in 300 mg/L prenol at a 30:1 ratio with isoprenol. Further pairing with the “IPP-Bypass” pathway resulted in 526 mg/L prenol at a 72:1 ratio with isoprenol, the highest and purest MVA-derived prenol titer to date. Additionally, modifying this “IPP-Repass” for DMAPP production and coexpressing the prenyltransferase acPT1 yielded 48.3 mg/L of the potential therapeutic precursor drupanin from p-coumarate. These novel repass pathways establish a unique strategy for tuning diphosphate precursors to drive isoprenoid biosynthesis and prenylation reactions.

59 BASIC BIOLOGICAL SCIENCES↗