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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 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Unraveling the Nature of Excellent Potassium Storage in Small-Molecule Se@Peapod-Like N-Doped Carbon Nanofibers

The potassium-selenium (K-Se) battery is considered as an alternative solution for stationary energy storage because of abundant resource of K. However, the detailed mechanism of the energy storage process is yet to be unraveled. In this work, the findings in probing the working mechanism of the K-ion storage in Se cathode are reported using both experimental and computational approaches. A flexible K-Se battery is prepared by employing the small-molecule Se embedded in freestanding N -doped porous carbon nanofibers thin film (Se@NPCFs) as cathode. The reaction mechanisms are elucidated by identifying the existence of short-chain molecular Se encapsulated inside the microporous host, which transforms to K 2 Se by a two-step conversion reaction via an "all-solid-state" electrochemical process in the carbonate electrolyte system. Through the whole reaction, the generation of polyselenides (K 2 Se n , 3 ≤ n ≤ 8) is effectively suppressed by electrochemical reaction dominated by Se-2 molecules, thus significantly enhancing the utilization of Se and effecting the voltage platform of the K-Se battery. This work offers a practical pathway to optimize the K-Se battery performance through structure engineering and manipulation of selenium chemistry for the formation of selective species and reveal its internal reaction mechanism in the carbonate electrolyte.

25 ENERGY STORAGE↗
DOE OSTI2023

Effect of water droplet growth dynamics on electrode current in fuel-cell catalyst layers

Fuel cells are a promising next-generation energy-conversion technology designed to replace internal combustion engines in transportation applications. However, much work remains to optimize them. Operation at high humidities causes liquid water droplet formation on Pt catalyst particles during oxygen reduction, potentially impeding reactant arrival to the reactive electrode. In this work, four different cases of water droplet growth in fuel-cell catalyst layers are considered: pinned or advancing droplets on a bare Pt surface, advancing droplets on a Nafion film, and water-layer growth in carbon nanopores. Transient drop growth is captured with a combination of mass, species mass, and momentum balances, and the subsequent limiting current is determined via oxygen diffusion and Tafel kinetics. Further, water droplets are found not to be mass-transfer limiting due to the relatively large liquid-gas area compared to the Pt nanoparticle. Mass-transfer-limited behavior is calculated in carbon nanopores.

25 ENERGY STORAGE↗
DOE OSTI2025

Mixed-Integer Linear Programming Formulation with Embedded Machine Learning Surrogates for the Design of Chemical Process Families

In previous work, we introduced process family design. The main idea is to design a platform of common elements, and, allowing us to capture additional cost savings, simultaneously design a family of processes, and reducing both engineering and deployment timelines. We formulate this as an optimization problem, specifically a nonlinear generalized disjunctive program (GDP). We have proposed two approaches for reformulating and solving this problem: one based on full-discretization of the design space and one that uses Machine Learning (ML) surrogates to replace the nonlinear process models. Using ML surrogates to predict required system costs and performance indicators allows us to reformulate the nonlinearities in the GDP generate an efficient MILP formulation. In this work, we apply the ML surrogate approach to two case studies. One case study involves designing a family of carbon capture systems to cover a set of different flue gas flow rates and inlet CO 2 concentrations, where we consider the absorber and stripper as common unit module types. The second case study focuses on a water-desalination process, where we design a family of these processes for a variety of salt concentrations and flow rates. In both of these case studies, we demonstrate a scalable optimization approach that enables the design of multiple processes simultaneously, reducing the time-to-market and overall costs by maximizing the cost savings due to both economies of scale and economies of numbers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Laser-Induced Enhancement of Acoustic Mode Quality Factor Revealed by Correlated Single-Particle Optical and Electron Microscopy

Acoustic modes in plasmonic nanostructures provide fundamental insights into their optomechanical behavior at the nanoscale, enabling emerging applications in plasmon-enhanced optomechanics, ultrasensitive sensing, and nanoscale energy transduction. Here we explore the modulation of acoustic phonon dynamics in lithographically fabricated gold nanodisks via laser-induced photothermal annealing. Using a correlated approach that utilizes both single-particle transient extinction spectroscopy and advanced electron microscopy, we directly link nanoscale structural transformations to changes in mechanical properties as probed through the coherence of the excited acoustic modes. Specifically, ultrafast pump–probe microscopy reveals an enhancement in the acoustic mode quality factor of annealed gold nanodisks, indicative of reduced damping and improved vibrational coherence. Structural characterization via scanning electron microscopy and electron backscatter diffraction confirms that photoinduced annealing results in smoother surface morphology and overall enhanced crystallinity. The improved crystalline order reduces defect and crystal boundary scattering, which we suggest as the reason underlying the lower quality factor before annealing. Furthermore, these findings demonstrate that targeted structural engineering at the nanoscale offers a powerful strategy for optimizing the optomechanical performance of plasmonic nanostructures, with broad implications for the design of next-generation nanophotonic and optomechanical systems.

Annealing (metallurgy)↗
DOE OSTI2022

Surfactant Engineering and Its Role in Determining the Performance of Nanoparticulate Organic Photovoltaic Devices

The fabrication of organic photovoltaics (OPVs) from non-hazardous nanoparticulate (NP) inks offers considerable promise for the development of ecofriendly large-scale printed solar modules. However, the typical NP core-shell morphology (driven by the different donor/acceptor affinities for the surfactant used in NP synthesis) currently hinders the photovoltaic performance. As such, surfactant engineering offers an elegant approach to synthesizing a more optimal intermixed NP morphology and hence an improved photovoltaic performance. In this work, the morphology of conventional sodium dodecyl sulfate (SDS) and 2-(3-thienyl) ethyloxybutylsulfonate (TEBS)-stabilized poly(3-hexylthiophene) (P3HT) donor:phenyl-C 61 -butyric acid methyl ester (PC 61 BM) acceptor NPs is probed using scanning transmission X-ray microscopy, UV-vis spectroscopy, grazing-incidence X-ray diffraction, and scanning electron microscopy. While the SDS-stabilized NPs exhibit a size-independent core-shell morphology, this work reveals that TEBS-stabilized NPs deliver an intermixed morphology, the extent of which depends on the particle size. Consequently, by optimizing the TEBS-stabilized NP size and distribution, NP-OPV devices with a power conversion efficiency that is ~50% higher on average than that of the corresponding SDS-based NP-OPV devices are produced.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Learning perturbation-inducible cell states from observability analysis of transcriptome dynamics

Abstract A major challenge in biotechnology and biomanufacturing is the identification of a set of biomarkers for perturbations and metabolites of interest. Here, we develop a data-driven, transcriptome-wide approach to rank perturbation-inducible genes from time-series RNA sequencing data for the discovery of analyte-responsive promoters. This provides a set of biomarkers that act as a proxy for the transcriptional state referred to as cell state. We construct low-dimensional models of gene expression dynamics and rank genes by their ability to capture the perturbation-specific cell state using a novel observability analysis. Using this ranking, we extract 15 analyte-responsive promoters for the organophosphate malathion in the underutilized host organism Pseudomonas fluorescens SBW25. We develop synthetic genetic reporters from each analyte-responsive promoter and characterize their response to malathion. Furthermore, we enhance malathion reporting through the aggregation of the response of individual reporters with a synthetic consortium approach, and we exemplify the library’s ability to be useful outside the lab by detecting malathion in the environment. The engineered host cell, a living malathion sensor, can be optimized for use in environmental diagnostics while the developed machine learning tool can be applied to discover perturbation-inducible gene expression systems in the compendium of host organisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Probing lithium mobility at a solid electrolyte surface

Abstract Solid-state electrolytes overcome many challenges of present-day lithium ion batteries, such as safety hazards and dendrite formation 1,2 . However, detailed understanding of the involved lithium dynamics is missing due to a lack of in operando measurements with chemical and interfacial specificity. Here we investigate a prototypical solid-state electrolyte using linear and nonlinear extreme-ultraviolet spectroscopies. Leveraging the surface sensitivity of extreme-ultraviolet-second-harmonic-generation spectroscopy, we obtained a direct spectral signature of surface lithium ions, showing a distinct blueshift relative to bulk absorption spectra. First-principles simulations attributed the shift to transitions from the lithium 1 s state to hybridized Li- s /Ti- d orbitals at the surface. Our calculations further suggest a reduction in lithium interfacial mobility due to suppressed low-frequency rattling modes, which is the fundamental origin of the large interfacial resistance in this material. Our findings pave the way for new optimization strategies to develop these electrochemical devices via interfacial engineering of lithium ions.

25 ENERGY STORAGE↗
DOE OSTI2021

Identification of a pathway for electron uptake in Shewanella oneidensis

Extracellular electron transfer (EET) could enable electron uptake into microbial metabolism for the synthesis of complex, energy dense organic molecules from CO 2 and renewable electricity. Theoretically EET could do this with an efficiency comparable to H 2 -oxidation but without the need for a volatile intermediate and the problems it causes for scale up. However, significant gaps remain in understanding the mechanism and genetics of electron uptake. For example, studies of electron uptake in electroactive microbes have shown a role for the Mtr EET complex in the electroactive microbe Shewanella oneidensis MR-1, though there is substantial variation in the magnitude of effect deletion of these genes has depending on the terminal electron acceptor used. This speaks to the potential for previously uncharacterized and/or differentially utilized genes involved in electron uptake. To address this, we screened gene disruption mutants for 3667 genes, representing ≈99% of all nonessential genes, from the S. oneidensis whole genome knockout collection using a redox dye oxidation assay. Confirmation of electron uptake using electrochemical testing allowed us to identify five genes from S. oneidensis that are indispensable for electron uptake from a cathode. Knockout of each gene eliminates extracellular electron uptake, yet in four of the five cases produces no significant defect in electron donation to an anode. This result highlights both distinct electron uptake components and an electronic connection between aerobic and anaerobic electron transport chains that allow electrons from the reversible EET machinery to be coupled to different respiratory processes in S. oneidensis. Homologs to these genes across many different genera suggesting that electron uptake by EET coupled to respiration could be widespread. These gene discoveries provide a foundation for: studying this phenotype in exotic metal-oxidizing microbes, genetic optimization of electron uptake in S. oneidensis; and genetically engineering electron uptake into a highly tractable host like E. coli to complement recent advances in synthetic CO2 fixation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Grand canonical inverse design of multicomponent colloidal crystals

Inverse design methods are powerful computational approaches for creating colloidal systems which self-assemble into a target morphology by reverse engineering the Hamiltonian of the system. Despite this, these optimization procedures tend to yield Hamiltonians which are too complex to be experimentally realized. An alternative route to complex structures involves the use of several different components, however, conventional inverse design methods do not explicitly account for the possibility of phase separation into compositionally distinct structures. We present an inverse design scheme for multicomponent colloidal systems by combining active learning with a method to directly compute their ground state phase diagrams. This explicitly accounts for phase separation and can locate stable regions of Hamiltonian parameter space which grid-based surveys are prone to miss. Using this we design low-density, binary structures with Lennard-Jones-like pairwise interactions that are simpler than in the single component case and potentially realizable in an experimental setting. This reinforces the concept that ground states of simple, multicomponent systems might be rich with previously unappreciated diversity, enabling the assembly of non-trivial structures with only few simple components instead of a single complex one.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Structural Design Approach Tailored for the Rapid Preliminary Design of Microreactor Components

High-temperature microreactors can play a role in developing reliable, portable energy sources for off-grid remote locations, microgrid concepts, and industrial process heat. Portability and passive safety criteria tend to skew microreactor structural component designs toward complex geometries, high thermal stresses, and design bases with large numbers of startup/shutdown cycles. Current design rules, as typified by Section III of the American Society of Mechanical Engineers (ASME) Boiler & Pressure Vessel Code, are less than optimal for these conditions, particularly for preliminary component designs where developers need to rapidly consider a large number of potential component configurations. This paper presents a design method targeted toward rapid, efficient evaluation of preliminary component designs using modern finite element analysis. The new method retains key connections with the ASME Code rules and design data while streamlining the design approach. This paper presents the design method, several verification examples illustrating the similarities and differences between the new method and the current ASME rules, and the application of the new approach to the evaluation of a test article mimicking key features of a heat pipe–cooled microreactor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Ptychographic phase retrieval by proximal algorithms

We derive a set of ptychography phase-retrieval iterative engines based on proximal algorithms originally developed in convex optimization theory, and discuss their connections with existing ones. The use of proximal operator creates a simple frame work that allows us to incorporate the effect of noise from a maximum-likelihood (ML) principle. We focus on three particular algorithms, namely proximal minimization, alternating direction method of multiplier and accelerated proximal gradient (APG). We benchmark their performance with numerical simulations, and discuss their optimal conditions for convergence and accuracy. An experimental dataset is used to demonstrate their effectiveness as well, in which case an array of cubic Au nanoparticles with a size of 50 nm is imaged. We show that with the presence of Poisson noise, a dataset with photon counts up to 10 4 at one detector pixel already requires ML-based methods to achieve a stable convergence. Among the three algorithms derived in this work, APG method is reported first time for its application in ptychographic reconstruction and shows superior performance in terms of both accuracy and convergence rate with a noisy dataset.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Extensive Attention Mechanisms in Graph Neural Networks for Materials Discovery

We present our research where attention mechanism is extensively applied to various aspects of graph neural net- works for predicting materials properties. As a result, surrogate models can not only replace costly simulations for materials screening but also formulate hypotheses and insights to guide further design exploration. We predict formation energy of the Materials Project and gas adsorption of crystalline adsorbents, and demonstrate the superior performance of our graph neural networks. Moreover, attention reveals important substructures that the machine learning models deem important for a material to achieve desired target properties. Our model is based solely on standard structural input files containing atomistic descriptions of the adsorbent material candidates. We construct novel methodological extensions to match the prediction accuracy of state-of-the-art models some of which were built with hundreds of features at much higher computational cost. We show that sophisticated neural networks can obviate the need for elaborate feature engineering. Our approach can be more broadly applied to optimize gas capture processes at industrial scale.

Cong, Guojing↗
DOE OSTI2022

The potential of bacterial microcompartment architectures for phytonanotechnology

The application of nanotechnology to plants, termed phytonanotechnology, has the potential to revolutionize plant research and agricultural production. Advancements in phytonanotechnology will allow for the time-controlled and target-specific release of bioactive compounds and agrochemicals to alter and optimize conventional plant production systems. A diverse range of engineered nanoparticles with unique physiochemical properties is currently being investigated to determine their suitability for plants. Improvements in crop yield, disease resistance and nutrient and pesticide management are all possible using designed nanocarriers. However, despite these prospective benefits, research to thoroughly understand the precise activity, localization and potential phytotoxicity of these nanoparticles within plant systems is required. Protein-based bacterial microcompartment shell proteins that self-assemble into spherical shells, nanotubes and sheets could be of immense value for phytonanotechnology due to their ease of manipulation, multifunctionality, rapid and efficient producibility and biodegradability. Here in this review, we explore bacterial microcompartment-based architectures within the scope of phytonanotechnology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Disruption of starch biosynthesis and triacylglycerol degradation impairs growth but improves photosynthesis in Arabidopsis

Enhancing lipid accumulation by redirecting carbon from starch to triacylglycerol (TAG) in vegetative tissues is a promising strategy for developing high-energy-density crops for bioenergy production. However, our understanding of how starch and TAG metabolism interact and how this interaction affects growth and photosynthesis is incomplete. Here, we investigated the metabolic and physiological consequences of disrupting starch biosynthesis and TAG turnover in Arabidopsis thaliana by generating single, double, and triple mutants involving ADG1 (starch biosynthesis), TGD1 (lipid trafficking), and SDP1\\\\\\\\r\\\\\\\\n(TAG lipase). Unexpectedly, elimination of starch biosynthesis lowered TAG levels in the high-TAG-accumulating tgd1 mutant, primarily through enhanced TAG breakdown. This decline was completely reversed by sucrose supplementation, suggesting that TAG degradation was induced by carbon limitation.\\\\\\\\r\\\\\\\\nGenetic suppression of TAG turnover via SDP1 disruption in the starchless tgd1 adg1-1 background led to a nine-fold rise in leaf TAG accumulation in the tgd1 sdp1 adg1-1 triple mutant, together with enhanced photosynthetic performance. However, this metabolic reprogramming incurred growth penalties.\\\\\\\\r\\\\\\\\nOur results highlight the role of dynamic TAG turnover in maintaining metabolic balance and photosynthesis in starch-deficient backgrounds. These findings underscore the need for refined metabolic engineering strategies that coordinate TAG biosynthesis and degradation to optimize lipid accumulation in bioenergy crops.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Cyanobacterial circadian regulation enhances bioproduction under subjective nighttime through rewiring of carbon partitioning dynamics, redox balance orchestration, and cell cycle modulation

Abstract Background The industrial feasibility of photosynthetic bioproduction using cyanobacterial platforms remains challenging due to insufficient yields, particularly due to competition between product formation and cellular carbon demands across different temporal phases of growth. This study investigates how circadian clock regulation impacts carbon partitioning between storage, growth, and product synthesis in Synechococcus elongatus PCC 7942, and provides insights that suggest potential strategies for enhanced bioproduction. Results After entrainment to light-dark cycles, PCC 7942 cultures transitioned to constant light revealed distinct temporal patterns in sucrose production, exhibiting three-fold higher productivity during subjective night compared to subjective day despite moderate down-regulation of genes from the photosynthetic apparatus. This enhanced productivity coincided with reduced glycogen accumulation and halted cell division at subjective night time, suggesting temporal separation of competing processes. Transcriptome analysis revealed coordinated circadian clock-driven adjustment of the cell cycle and rewiring of energy and carbon metabolism, with over 300 genes showing differential expression across four time points. The subjective night was characterized by altered expression of cell division-related genes and reduced expression of genes involved in glycogen synthesis, while showing upregulation of glycogen degradation pathways, alternative electron flow components, the pentose phosphate pathway, and oxidative decarboxylation of pyruvate. These molecular changes created favorable conditions for product formation through enhanced availability of major sucrose precursors (glucose-1-phosphate and fructose-6-phosphate) and maintained redox balance through multiple mechanisms. Conclusions Our analysis of circadian regulatory rewiring of carbon metabolism and redox balancing suggests two potential approaches that could be developed for improving cyanobacterial bioproduction: leveraging natural circadian rhythms for optimizing cultivation conditions and timing of pathway induction, and engineering strains that mimic circadian-driven metabolic shifts through controlled carbon flux redistribution and redox rebalancing. While these strategies remain to be tested, they could theoretically improve the efficiency of photosynthetic bioproduction by enabling better temporal separation between cell growth, carbon storage accumulation, and product synthesis phases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Resilient Operations of Networked Microgrids (RONM)

Objective: Improve the resiliency of power systems with optimization-based methods that leverage advanced microgrid technologies to reduce system recovery times after extreme event induced outages. Outcome: First-of-kind, high-fidelity physics-based optimization method for modeling networked microgrids which includes key engineering constraints associated with system recovery after extreme events.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Direct conversion of Light Hydrocarbons to Olefins (Final report)

Reaction35 is developing a new industrial process that is substantially different from the traditional standalone dehydrogenation process practiced in industry such as Oleflex® and Catofin®. Those processes have substantial energy consumption and loss of feed constraints. The Reaction35 process is based on using molecular bromine to activate the alkane (e.g., nbutane) by forming highly reactive butyl bromides. The butyl bromides are easily converted to nbutylenes (final product) and hydrogen bromide. The hydrogen bromide generated in bromination and dehydrobromination is oxidized with air, recovering the molecular bromine which is reused. The overall result is a process with a favorably low energy consumption and less than 1 % overall loss of feed compared to more than 5 % for the direct dehydrogenation processes. During the grant period, several important aspects of the technology have been developed further. The major effort was the hydrogenation catalyst step development. The hydrogenation catalyst is used for recovery of the polybromobutanes to the bromobutanes intermediates. The scientific field regarding dibromo- and polybromoalkanes has not been extensively studied, which necessitated that Reaction35 performs a full study of a number of catalysts and the various experimental conditions that influence the hydrogenation reaction. Currently, Reaction35 has completed its catalyst selection and preliminary experimental parameters optimization. This will allow for the construction of an engineering model for a pilot unit testing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Building a quantum computing architecture using 3D superconducting cavities

Quantum computers promise advantages over classical machines for solving certain complex problems, but building processors that truly deliver this advantage remains a central challenge, particularly due to limited coherence times. Three-dimensional superconducting radio-frequency (SRF) cavities offer an attractive platform due to their exceptionally long lifetimes. However, since these harmonic systems require nonlinear elements, such as transmons, for control, additional losses are often introduced. In this talk, I will present a multimode quantum system based on an elliptical SRF cavity hosting two cavity modes weakly coupled to an ancillary transmon circuit. This architecture is carefully engineered to preserve coherence while enabling efficient control. By optimizing the design to mitigate transmon-induced decoherence, we realize single-photon lifetimes of 20.6 ms and 15.6 ms in the two modes, with pure dephasing times exceeding 40 ms. Using sideband interactions and error-resilient protocols, such as measurement-based correction and post-selection, we demonstrate high-fidelity state control, including preparation of Fock states up to N=20 with fidelities above 95% (to our knowledge, the highest reported to date), as well as high-fidelity two-mode entanglement. These results highlight 3D SRF cavities as a robust foundation for qudit-based quantum information processing, harnessing the large Hilbert space of cavity modes. I will conclude by outlining strategies to further enhance coherence in both cavities and ancilla qubits, and discuss pathways toward scaling this architecture into a larger quantum computing platform.

Roy, Tanay [Fermilab]↗