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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Perspective on Scalable AI on High-Performance Computing and Leadership Class Supercomputing Facilities [Industrial and Governmental Activities]

Many scientific applications that support the mission of the US Department of Energy (US-DoE) require modeling complex engineering and/or physical systems. Here, examples of such complex systems arise from: (a) materials science to develop new compounds with exceptional mechanical and thermodynamical properties (e.g., resistance to mechanical stresses and high temperatures), (b) structural and nuclear engineering to model the temporal evolution of the structural damage of concrete shields exposed to continuous neutron and gamma radiations emitted by the nuclear reactor core, (c) urban sciences (e.g., transportation and smart buildings), and (d) power grid systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

TRACKING LIGNOCELLULOSIC BREAKDOWN BY ANAEROBIC FUNGI AND FUNGAL CELLULOSOMES

Anaerobic fungi degrade plant biomass through invasive, filamentous growth, and the secretion of multi-protein biomass-degrading complexes called fungal cellulosomes. This project developed new tools for anaerobic, non-destructive, real-time imaging of cellulosomes across spatial and temporal scales. Novel nanobody tools were synthesized and deployed to image native fungal cellulosomes. Antibodies raised against key fungal cellulosome components were also used to define the localization patterns of cellulosomes in mature fungal mats vs. fungal zoospores, and revealed direct connections between cellular life stage progression and the regulation of cellulosome production. New procedures were developed to purify native cellulosomes and study their morphology and sub-structures, and genetic engineering tools were also developed and applied to anaerobic fungi to advance in vivo labeling capabilities. A cryoEM structure of a native fungal cellulosome was achieved, as well as a proof of concept for transformation of fungi with flavin-based anaerobic reporter proteins for in vivo labeling of cellulosome components.

09 BIOMASS FUELS↗
DOE OSTI2024

Stable water splitting using photoelectrodes with a cryogelated overlayer

Hydrogen production techniques based on solar-water splitting have emerged as carbon-free energy systems. Many researchers have developed highly efficient thin-film photoelectrochemical (PEC) devices made of low-cost and earth-abundant materials. However, solar water splitting systems suffer from short lifetimes due to catalyst instability that is attributed to both chemical dissolution and mechanical stress produced by hydrogen bubbles. A recent study found that the nanoporous hydrogel could prevent the structural degradation of the PEC devices. In this study, we investigate the protection mechanism of the hydrogel-based overlayer by engineering its porous structure using the cryogelation technique. Tests for cryogel overlayers with varied pore structures, such as disconnected micropores, interconnected micropores, and surface macropores, reveal that the hydrogen gas trapped in the cryogel protector reduce shear stress at the catalyst surface by providing bubble nucleation sites. The cryogelated overlayer effectively preserves the uniformly distributed platinum catalyst particles on the device surface for over 200 h. Our finding can help establish semi-permanent photoelectrochemical devices to realize a carbon-free society.

42 ENGINEERING↗
DOE OSTI2024

Complete biosynthesis of QS-21 in engineered yeast

QS-21 is a potent vaccine adjuvant and remains the only saponin-based adjuvant that has been clinically approved for use in humans. However, owing to the complex structure of QS-21, its availability is limited. Today, the supply depends on laborious extraction from the Chilean soapbark tree or on low-yielding total chemical synthesis. Here we demonstrate the complete biosynthesis of QS-21 and its precursors, as well as structural derivatives, in engineered yeast strains. The successful biosynthesis in yeast requires fine-tuning of the host’s native pathway fluxes, as well as the functional and balanced expression of 38 heterologous enzymes. The required biosynthetic pathway spans seven enzyme families—a terpene synthase, P450s, nucleotide sugar synthases, glycosyltransferases, a coenzyme A ligase, acyl transferases and polyketide synthases—from six organisms, and mimics in yeast the subcellular compartmentalization of plants from the endoplasmic reticulum membrane to the cytosol. Finally, by taking advantage of the promiscuity of certain pathway enzymes, we produced structural analogues of QS-21 using this biosynthetic platform. This microbial production scheme will allow for the future establishment of a structure–activity relationship, and will thus enable the rational design of potent vaccine adjuvants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Heterogeneous Multilayer Nanopores via Chemically Tuned Dielectric Breakdown for Single‐Molecule Sensing

Solid-state nanopores are powerful platforms for single-molecule sensing, yet their performance is often constrained by fabrication complexity, noise, and limited control over surface properties. Here we report a direct method to fabricate heterogeneous multilayer nanopores using chemically tuned controlled dielectric breakdown (CT-CDB). We integrate hBN, MoS 2 , or graphene atop a silicon nitride membrane to form five distinct bilayer and tri-layer architectures, with bare SiN x nanopore as a control. CT-CDB achieves pore formation reproducibly through material-stacks with high efficiency, good pore size control, and strong yield, validated by various characterizations. Transferrin protein translocation experiments, supported by simulations, reveal that multilayer configurations modulate protein conformations, ionic current blockade and dwell time distributions, reflecting combined effects of membrane type, interfacial chemistry, and local electric field gradients. A supervised machine learning framework is implemented to assist identifying multilayer structure effects embedded in signal signatures, with over 96% accuracy. This work presents a modular and scalable framework for functional nanopore engineering with complex structural integration, thereby expanding the potential of 2D materials in single-molecule sensing applications.

2D materials↗
DOE OSTI2021

Ultra-low-density digitally architected carbon with a strutted tube-in-tube structure

Porous materials with engineered stretching-dominated lattice designs, which offer attractive mechanical properties with ultra-light weight and large surface area for wide-ranging applications, have recently achieved near-ideal linear scaling between stiffness and density. Here, rather than optimizing the microlattice topology, we explore a different approach to strengthen low-density structural materials by designing tube-in-tube beam structures. We develop a process to transform fully dense, three-dimensional printed polymeric beams into graphitic carbon hollow tube-in-tube sandwich morphologies, where, similar to grass stems, the inner and outer tubes are connected through a network of struts. Compression tests and computational modelling show that this change in beam morphology dramatically slows down the decrease in stiffness with decreasing density. In situ pillar compression experiments further demonstrate large deformation recovery after 30–50% compression and high specific damping merit index. Lastly, our strutted tube-in-tube design opens up the space and realizes highly desirable high modulus–low density and high modulus–high damping material structures.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The Local Electronic Structure of Supercritical CO 2 from X-ray Raman Spectroscopy and Atomistic-Scale Modeling

Supercritical CO 2 is encountered in several technical and natural systems related to biology, geophysics, and engineering. While the structure of gaseous CO 2 has been studied extensively, the properties of supercritical CO 2 , particularly close to the critical point, are not well-known. Here, in this work, we combine X-ray Raman spectroscopy, molecular dynamics simulations, and first-principles density functional theory (DFT) calculations to characterize the local electronic structure of supercritical CO 2 at conditions around the critical point. The X-ray Raman oxygen K-edge spectra manifest systematic trends associated with the phase change of CO 2 and the intermolecular distance. Extensive first-principles DFT calculations rationalize these observations on the basis of the 4sσ Rydberg state hybridization. X-ray Raman spectroscopy is found to be a sensitive tool for characterizing electronic properties of CO 2 under challenging experimental conditions and is demonstrated to be a unique probe for studying the electronic structure of supercritical fluids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Understanding the ignition process and flame structure of conventional and oxygenated fuels under engine relevant conditions – An optical study

Renewably generated synthetic fuels such as poly-oxymethylene ethers (OME) have a significant potential to effectively break the soot-NOX trade-off in compression ignition engines by using exhaust gas recirculation (EGR) to maintain low nitrogen oxide (NOX) emissions while maintaining good efficiency and simultaneously contributing to circular carbon economy. However, owing to the fundamental differences in properties of OME when compared to fossil-based diesel fuels, it is critical to fully understand its ignition and combustion phenomenology to take advantage of this fuel to its utmost potential. In this context, this work outlines the results of a systematic experimental study performed in a heavy-duty, single-cylinder, optical engine probing the spatial and temporal progression of fuel decomposition and ignition behavior of OME when compared to n-dodecane, a diesel-fuel surrogate. Thermodynamic analysis and optical diagnostics techniques including simultaneous HCHO-PLIF and OH-PLIF complemented by high-speed OH* chemiluminescence were employed along with parametric sweeps of intake temperature and EGR dilution rates. OME does not exhibit any observable low temperature heat release irrespective of the ambient oxygen concentration. Differences in the observed diffusive flame structure such as longer flame lift-off length, less pronounced combustion recession, faster premixed burn at ignition (“volumetric” ignition), non-sooting behavior suggest that the inherent presence of fuel-bound oxygen in OME can skew the air-fuel ratio (AFR) distribution within the jet thereby reducing the reliance of combustion on mixing and air entrainment. This leads to rapid late-cycle oxidation leading to shorter combustion duration and favorable combustion phasing. Results also suggest that OME exhibits relatively weak negative temperature coefficient (NTC) behavior, however, the OME fuel-decomposition kinetic-pathways produce significant concentration of HCHO, which might be erroneously interpreted as a product of cool-flames.

Air-fuel ratio↗
DOE OSTI2021

Structure-activity relationship of Pt catalyst on engineered ceria-alumina support for CO oxidation

In heterogeneous catalysis, the promotion of low temperature activity and enhancement of thermal stability simultaneously especially for precious metal catalysts is always highly demanded but very challenging. In this work, we report a novel Pt catalyst on ceria-alumina (CeO 2 /Al 2 O 3 ) support (Pt/CA-T) engineered by a two-step ceria deposition strategy, exhibiting superior thermal stability and low-temperature carbon monoxide (CO) oxidation activity after activation. Pt single sites anchored to engineered CeO 2 edge sites are much more stable than that to CeO 2 (111) surface, and such stable single sites can be transformed into highly active Pt clusters for efficient low-temperature CO oxidation. Active site identification indicates that the CO oxidation activity of different Pt sites follows such sequence: Pt cluster step sites ≈ Pt cluster terrace sites > Pt cluster corner sites $\gg$ Pt single sites on CeO 2 . The excellent low temperature activity of activated Pt/CA-T catalyst for CO oxidation is associated with its abundant Pt cluster step and terrace sites as well as rich Pt-CeO 2 interfaces, which facilitate the adsorption of active CO species and superior oxygen activation/transfer ability. The present study provides new insights into the structure–activity relationship of Pt-CeO 2 -Al 2 O 3 catalyst, which can also guide the preparation of other highly robust supported catalysts for important industrial applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Mechanical Engineering Safety Note 1012910313-AA: CEA LTIC Structural Integrity

The LRU Target Insert Cryostat (LTIC) is the end effector of the NIF Cryogenic Target Positioner (CryoTarpos), which houses a cooling system to support cryogenic target experiments at NIF. The LTIC maintains a target at micron level positional stability and millikelvin level temperature stability during a NIF shot and is also subject to a portion of the blast load governed by the solid angle subtended by the blast shield at the front of the system. This MESN evaluates loading of the CEA LTIC, a redesigned LTIC to be fielded at Laser Megajoule (LMJ) in France, which has been designed to lay out requirements agreed upon between LLNL and CEA personnel. The LMJ version of CryoTarpos is referred to as the PCC. A high-level system overview of the LTIC on the PCC is shown.

42 ENGINEERING↗
DOE OSTI2024

Opportunities and Challenges for Machine Learning-Assisted Enzyme Engineering

Enzymes can be engineered at the level of their amino acid sequences to optimize key properties such as expression, stability, substrate range, and catalytic efficiency or even to unlock new catalytic activities not found in nature. Because the search space of possible proteins is vast, enzyme engineering usually involves discovering an enzyme starting point that has some level of the desired activity followed by directed evolution to improve its “fitness” for a desired application. Recently, machine learning (ML) has emerged as a powerful tool to complement this empirical process. ML models can contribute to (1) starting point discovery by functional annotation of known protein sequences or generating novel protein sequences with desired functions and (2) navigating protein fitness landscapes for fitness optimization by learning mappings between protein sequences and their associated fitness values. In this Outlook, we explain how ML complements enzyme engineering and discuss its future potential to unlock improved engineering outcomes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Predicting non-linear stress–strain response of mesostructured cellular materials using supervised autoencoder

Recent breakthroughs in advanced manufacturing capabilities have made it possible to design and print sophisticated topologies of cellular structures using diverse engineering materials such as metals, polymers, and ceramics. In these architectured materials, it is often desirable to tailor the mechanical properties by altering the unit cell topology. This necessitates an in-depth understanding of how the topology of the unit cell structure affects the macroscopic behavior of the material in both the linear and the non-linear regimes encountered under large compression. Here, we have developed a machine learning (ML) approach capable of accelerating the prediction of the stress–strain response of a polymer-based cellular structure under uniaxial confined compression. As part of generating the training data for ML, 60,000 mesostructures were generated using a relatively novel approach based on cellular automata, and their corresponding stress–strain responses were obtained from the finite element simulations. Principal component analysis (PCA) was used to reduce the dimensionality of the stress–strain curves. With only 20 principal components, PCA captured 99.89% of the variance in the stress–strain curves while reducing the dimensionality by 5X. ML using supervised autoencoder was able to successfully speed up the prediction of the non-linear stress–strain response of a unit cell by up to 4600X. The proposed method can serve as an efficient data generation tool and a rapid means for predicting the structure–property relationship through accelerated forward modeling of cellular materials under compaction, in cases where the macroscopic stress–strain response is governed by the unit-cell topology.

36 MATERIALS SCIENCE↗
DOE OSTI2020

High Thermoelectric Performance in the New Cubic Semiconductor AgSnSbSe 3 by High-Entropy Engineering

We investigate the structural and physical properties of the AgSn m SbSe m+2 system with m = 1-20 (i.e., SnSe matrix and ~5-50% AgSbSe 2 ) from atomic, nano, and macro length scales. We find the 50:50 composition, with m = 1 (i.e., AgSnSbSe 3 ), forms a stable cation-disordered cubic rock-salt p-type semiconductor with a special multi-peak electronic valence band structure. AgSnSbSe 3 has an intrinsically low lattice thermal conductivity of ~0.47 W m -1 K -1 at 673 K owing to the synergy of cation disorder, phonon anharmonicity, low phonon velocity, and low-frequency optical modes. Furthermore, Te alloying on Se sites creates a quinary high-entropy NaCl-type solid solution AgSnSbSe 3-x Te x with randomly disordered cations and anions. The extra point defects and lattice dislocations lead to glass-like lattice thermal conductivities of ~0.32 W m -1 K -1 at 723 K and higher hole carrier concentration than AgSnSbSe 3 . Concurrently, the Te alloying promotes greater convergence of the multiple valence band maxima in AgSnSbSe 1.5 Te 1.5 , the composition with the highest configurational entropy. Facilitated by these favorable modifications, we achieve a high average power factor of ~9.54 μW cm -1 K -2 (400-773 K), a peak thermoelectric figure of merit ZT of 1.14 at 723 K, and a high average ZT of ~1.0 over a wide temperature range of 400-773 K in AgSnSbSe 1.5 Te 1.5 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Bacterial microcompartments: tiny organelles with big potential

Organization of metabolic processes within the space of a cell is critical for the survival of many organisms. In bacteria, spatial organization is achieved via proteinaceous organelles called bacterial microcompartments, which encapsulate pathway enzymes, substrates, and co-factors to drive the safe and efficient metabolism of niche carbon sources. Microcompartments are self-assembled from shell proteins that encapsulate a core comprising various enzymes. Here, this review discusses how recent advances in understanding microcompartment structure and assembly have informed engineering efforts to repurpose compartments and compartment-based structures for non-native functions. These advances, both in understanding of the native structure and function of compartments, as well as in the engineering of new functions, will pave the way for the use of these structures in bacterial cell factories.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Composite Lithium Metal Structure to Mitigate Pulverization and Enable Long‐Life Batteries

In lithium metal batteries, non‐uniform stripping of lithium results in pit formation, which promotes subsequent non‐uniform, dendritic deposition. This viscous cycle leads to pulverization of lithium which promotes cell shorting or capacity degradation, symptoms further exaggerated by high electrode areal loading and lean electrolytes. Here, to address this challenge, a composite lithium metal anode is engineered that contains uniformly distributed, nanometer‐sized carbon particles. This composite lithium is shown to strip more uniformly since the growth of non‐uniform pits is intercepted by the carbon particles. This mechanism is corroborated by a continuum electrochemical model. Subsequent lithium deposition on carbon particles is also found to be more uniform than on the surface with irregular pits. Notably, the pulverization rate of composite lithium is 26 times slower than that of commercial lithium. Moreover, in a Li‐S battery with sulfurized polyacrylonitrile cathode, the use of the composite anode extends the cycle life by three times when the areal capacity is 8 mAh cm −2 . The approach of using an engineered lithium composite structure to address challenges during both stripping and plating can inform future designs of lithium metal anodes for high areal capacity operations.

high areal capacity↗
DOE OSTI2020

In situ synchrotron pair distribution function analysis to monitor synthetic pathways under electromagnetic excitation

Electromagnetic (EM) fields, specifically microwave radiation (MWR), can significantly influence the synthesis of ceramic oxide materials and promote rapid, low-temperature growth. However, the mechanisms by which EM fields affect the phase formation process are not well understood. A major limitation to increasing this understanding has been the lack of information regarding dynamic changes in local atomic structure during MWR exposure compared to conventional hydrothermal synthesis routes. Here, we utilize in situ synchrotron X-ray pair distribution function (PDF) analysis to monitor MWR-assisted SnO 2 nanoparticle synthesis. A clear impact of the EM field is demonstrated, with MWR inducing changes in nearest neighbor distances and peaks in oxygen atomic displacement that do not occur during synthesis without MWR exposure. The observed local structural disorder serves as a precursor to rapid rutile SnO 2 nanoparticle crystallization, suggesting that EM field-assisted growth is mediated by changes to the oxygen sublattice. These findings further our understanding of the mechanisms underlying MWR-assisted synthesis and represent a step towards utilizing EM fields to engineer tailored atomic structures for a broad range of applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Model predictive control of mixing controlled compression ignition operation for low reactivity fuels

Using gasoline or other low reactivity fuels with a pilot injection or port fuel injection in a compression ignition engine has shown great potential in reducing NOx emissions while keeping high thermal efficiency compared to diesel. However, excessive combustion noise is caused by a high maximum pressure rise rate in the cylinder due to the higher fractions of premixed charge of the low-reactivity fuel. This noise can result in structural damage to engine components and as such, combustion noise limits the range of the operating parameters and makes the control of such engines challenging. In this study, a simulation environment was built up in MATLAB/Simulink leveraging a physics-based zero-dimension combustion model to capture the in-cylinder pressure time traces as well as metrics relevant to thermal efficiency and combustion noise. Here, in order to also facilitate the control of emissions, machine learning models were investigated to capture NOx emissions. A kernel-based extreme learning machine (K-ELM) performed best and had a coefficient of correlation (R-squared) of 0.998. The combustion and NOx emission models are valid for not only conventional gasoline fuel but also oxygenated alternative fuel blends at three different pilot injection strategies. In order to track key combustion metrics while keeping noise and emissions within constraints, a model predictive control (MPC) was applied for a compression ignition engine operating with a range of potential fuels and fuel injection strategies. The MPC is validated under different scenarios, including a load step change, fuel type change, and injection strategy change, with proportional–integral (PI) control as the baseline. The simulation results show that MPC reduces about 26% of ringing intensity in the transient process and 17% at the steady state for E30. Generally, MPC can optimize the overall performance through modifying the main injection timing, pilot fuel mass, and exhaust gas recirculation (EGR) fraction.

42 ENGINEERING↗