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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Fragment optimization and elaboration strategies – the discovery of two lead series of PRMT5/MTA inhibitors from five fragment hits

Here we describe the early stages of a fragment-based lead discovery (FBLD) project for a recently elucidated synthetic lethal target, the PRMT5/MTA complex, for the treatment of MTAP-deleted cancers. Starting with five fragment/PRMT5/MTA X-ray co-crystal structures, we employed a two-phase fragment elaboration process encompassing optimization of fragment hits and subsequent fragment growth to increase potency, assess synthetic tractability, and enable structure-based drug design. Two lead series were identified, one of which led to the discovery of the clinical candidate MRTX1719.

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

A Game-Theoretic Quantum Algorithm for Solving Magic Squares

Variational quantum algorithms (VQAs) offer a promising near-term approach to finding optimal quantum strategies for playing non-local games. These games test quantum correlations beyond classical limits and enable entanglement verification. In this work, we present a variational framework for the Magic Square Game (MSG), a two-player non-local game with perfect quantum advantage. We construct a value Hamiltonian that encodes the game’s parity and consistency constraints, then optimize parameterize quantum circuits to minimize this cost. Our approach build on the stabilizer formalism, leverages commutation structure for circuit design, and is hardware-efficient. Compared to existing work, our contribution emphasizes algebraic structure an interpretability. We validate our method through numerical experiments and outline generalizations to larger games.

Chehade, Sarah [ORNL]↗
DOE OSTI2025

Resilient Operation of Networked Community Microgrids with High Solar Penetration

This project, funded by the US Department of Energy’s Solar Energy Technologies Office (SETO), focused on the operation of microgrids as a coordinated network. The primary objective, which was successfully achieved, was to develop both control strategies and hardware solutions to support the resilient and efficient operation of networked microgrids with high solar penetration. The work was structured around the following four main tasks: • Development of distributed and scalable optimization algorithms for AC-coupled networked microgrids. • Design and implementation of a novel DC interconnection hardware to enable precise power exchange between microgrids. • Laboratory operational validation of the developed technologies using 480 V testbeds and commercially available hardware. • Field operational validation of the complete solution in Adjuntas, Puerto Rico, interconnecting two kW-scale, split-phase microgrids of Casa Pueblo’s microgrids. This project addressed multiple technical challenges across the domains of optimization, control, hardware interconnection, and protection. One of its key contributions was delivering tangible, real-world solutions for networking microgrids. In contrast to purely theoretical or simulation-based work, this project included full-scale hardware operational validation both in the lab and in the field. The work conducted as part of this project—in collaboration with the University of Puerto Rico; the University of Tennessee, Knoxville; the University of Central Florida; and Casa Pueblo—has advanced the state of the art in networked microgrids. Key contributions include the development of distributed control strategies, practical solutions for real-world implementation challenges, and the introduction of a novel DC interlink approach for microgrid interconnection. The project featured both laboratory and field validation using commercial off-the-shelf components. The field deployment successfully validated that a group of microgrids can operate in a coordinated manner, enabling precise power flow between systems and mutual support during extreme events. This project resulted in 15 journal publications and 15 conference papers; 5 graduate students and 15 undergraduate students were supported. The codes of distributed optimization and forecasting were made open-source through OSTI.gov for distributed optimization and forecasting. All the publications are available in the ORNL-hosted project landing page. The DC interlink with state-of-charge balancing control was operationally validated in Adjuntas by interconnecting two real-world, 240 V split-phase microgrids. To the best knowledge of the team, this represents the first operational validation of AC microgrids interconnected via DC-interlinks. As a culmination of this project, a follow-on grant was awarded to support the technology transfer of the distributed optimization framework to a commercial microgrid controller, Stellar Edge, developed by the California-based company New Sun Road.

14 SOLAR ENERGY↗
DOE OSTI2021

Identification and structural analysis of a thermophilic β-1,3-glucanase from compost

β-1,3-glucanase can specifically hydrolyze glucans to oligosaccharides and has potential applications in biotechnology. We used the metatranscriptomic technology to discover a thermophilic β-1,3-glucanase from compost. The phylogenetic study shows that it belongs to the family 16 glycoside hydrolase (GH16) and is most homologous with an enzyme from Streptomyces sioyaensis, an actinobacterium. It has the activity of 146.9 U/mg in the optimal reaction condition (75 °C and pH 5.5). Its catalytic domain was crystallized and diffracted to 1.14 Å resolution. The crystal structure shows a sandwich-like β-jelly-roll fold with two disulfide bonds. After analyzing the occurring frequencies of these cysteine residues, we designed two mutants (C160G and C180I) to study the role of these disulfide bonds. Both mutants have decreased their optimal temperature from 75 to 70 °C, which indicate that the disulfide bonds are important to maintain thermostability. Interestingly, the activity of C160G has increased ~ 17% to reach 171.4 U/mg. We speculate that the increased activity of C160G mutant is due to increased dynamics near the active site. Our studies give a good example of balancing the rigidity and flexibility for enzyme activity, which is helpful for protein engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Optimal design of chemoepitaxial guideposts for the directed self-assembly of block copolymer systems using an inexact Newton algorithm

Directed self-assembly (DSA) of block copolymers (BCPs) is one of the most promising developments in the cost-effective production of nanoscale devices. The process makes use of the natural tendency for BCP melts to form nanoscale structures upon phase separation. The phase separation can be directed through the use of chemically patterned substrates to promote the formation of morphologies that are essential to the production of semiconductor devices. Moreover, the design of substrate pattern can be formulated as an optimization problem for which we seek optimal substrate designs that effectively produce given target morphologies. In this paper, we adopt a phase field model given by a nonlocal Cahn–Hilliard partial differential equation (PDE) based on the minimization of the Ohta–Kawasaki free energy, and present an efficient PDE-constrained optimization framework for the optimal design problem. The design variables are the locations of circular- or strip-shaped guiding posts that are used to model the substrate chemical pattern. To solve the ensuing optimization problem, we propose a variant of an inexact Newton conjugate gradient algorithm tailored to this problem. Additionally, we demonstrate the effectiveness of our computational strategy on numerical examples that span a range of target morphologies. Owing to our second-order optimizer and fast state solver, the numerical results demonstrate five orders of magnitude reduction in computational cost over previous work. The efficiency of our framework and the fast convergence of our optimization algorithm enable us to rapidly solve the optimal design problem in not only two, but also three spatial dimensions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Design Overview of a High-Pressure Helium Flow Visualization Apparatus for Blanket Cooling Studies

Cooling of the fusion blanket first wall remains a significant challenge given the adverse conditions of heat and particle flux encountered near the plasma. Helium emerges as an attractive cooling candidate because of its chemical and neutronic inertness and separability from hydrogenic species (e.g. tritium). Because of the low thermal mass of helium, optimization of these coolant channels is warranted to provide high heat transfer performance at low pumping costs. Increasingly, computational fluid dynamics (CFD) simulations are employed to model and optimize these flow channels, and accompanying experimental data are needed to validate the predictions of these models. To provide the aforementioned experimental data, a high-pressure helium flow visualization upgrade has been designed for the Helium Flow Loop Experiment facility. This apparatus was built to American Society of Mechanical Engineers boiler and pressure vessel standards to withstand operating pressure of 4 MPa and mated to high-pressure glass windows. Seedless flow visualization is performed via high-speed background oriented schlieren (BOS), with image correlation used for time-resolved two-dimensional velocimetry at frequencies in excess of 60 kHz. Rectangular flow channel test articles are additively manufactured via laser powder bed fusion and installed into this visualization apparatus, with one-sided heating supplied by resistive heaters. In conclusion, the chosen test geometries were informed by prior CFD simulations, and the helium flow structures observed via BOS (detachment, recirculation, etc.) will be used for the validation of these accompanying models, in support of the design and optimization of blanket cooling channel configurations.

Helium flow↗
DOE OSTI2021

Design and Optimization of the Direct Recycling of Spent Li-Ion Battery Cathode Materials

Direct regeneration of spent Li-ion batteries based on the hydrothermal relithiation of cathode materials is a promising next-generation recycling technology. In order to demonstrate the feasibility of this approach at a large scale, we systematically design and optimize the process parameters to minimize both energy and raw material costs. Specifically, the effects of regenerative processing parameters on the composition, structure, and electrochemical performance of the regenerated cathode materials are investigated via systematic characterization and testing. From this analysis, it was found that the raw material costs can be substantially reduced by either replacing the typically employed 4 M LiOH solution by a cost-effective mixture of 0.1 M LiOH and 3.9 M KOH or recycling of the concentrated 4 M LiOH for continuous relithiation processes. Finally, life cycle analysis suggests that this strategy results in reduced energy consumption and greenhouse gas emissions, leading to an increased potential revenue, particularly when compared with hydro- and pyrometallurgical recycling methods.

25 ENERGY STORAGE↗
DOE OSTI2020

Optimizing the Design of Diatom Biosilica-Targeted Fusion Proteins in Biosensor Construction for Bacillus anthracis Detection

In vivo functionalization of diatom biosilica frustules by genetic manipulation requires careful consideration of the overall structure and function of complex fusion proteins. Although we previously had transformed Thalassiosira pseudonana with constructs containing a single domain antibody (sdAb) raised against the Bacillus anthracis Sterne strain, which detected an epitope of the surface layer protein EA1 accessible in lysed spores, we initially were unsuccessful with constructs encoding a similar sdAb that detected an epitope of EA1 accessible in intact spores and vegetative cells. This discrepancy limited the usefulness of the system as an environmental biosensor for B. anthracis. We surmised that to create functional biosilica-localized biosensors with certain constructs, the biosilica targeting and protein trafficking functions of the biosilica-targeting peptide Sil3T8 had to be uncoupled. We found that retaining the ER trafficking sequence at the N-terminus and relocating the Sil3T8 targeting peptide to the C-terminus of the fusion protein resulted in successful detection of EA1 with both sdAbs. Homology modeling of antigen binding by the two sdAbs supported the hypothesis that the rescue of antigen binding in the previously dysfunctional sdAb was due to removal of steric hindrances between the antigen binding loops and the diatom biosilica for that particular sdAb.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Optimizing Information Automation Using a New Method Based on System-Theoretic Process Analysis: Tool Development and Method Evaluation

This report is an update to a prior report that describes progress and findings for a program of research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and throughout the plant, along with a greater interest in the use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human performance-related organizational and technical design issues are identified and addressed early in the design process. This report describes modeling tools and techniques, based on sociotechnical systems theory, to support these design goals and their application in the current research effort. The report is primarily intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control, feedback, and communication relationships amongst the system’s technical and organizational components. We have employed two STAMP-based tools in this effort. The first is Causal Analysis based on STAMP (CAST), an accident and incident analysis technique that was used to examine a performance- and safety-related incident at an industry partner’s plant involving the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. The second tool is Systems Theoretic Process Analysis (STPA) which is a proactive risk analysis tool used to examine existing and potential, planned sociotechnical systems. STPA was used to identify risk factors in the current design of a generic nuclear power plant (NPP) preventive maintenance system. Our analyses focused on identifying near-term system improvements and longer-term design requirements for an optimized IAE system. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived time and schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the eventual event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. STPA findings exposed several areas of concern in the design of current preventive maintenance systems. We also present two preliminary information automation models. The proactive issue resolution (PIR) model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system and represents an end-state vision for our work. From our results, we have generated an initial set of preliminary system-level requirements and safety constraints for these models. We have also focused on early development of easy to learn, easy to use “transportable” tools for sociotechnical systems analysis. We intend these to be used by NPP personnel as a means of gaining reliable and relatively quick insight into (1) sociotechnical systems factors impacting incidents and accidents, (2) potential sociotechnical risk factors in existing or planned system designs, and (3) potential weaknesses in a system’s safety and/or information control structure. We conclude the report with a set of summary recommendations, a discussion of planned and potential follow-on research and development, and a draft list of system-level requirements and safety constraints for optimized information automation systems.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Molecular dynamics study on the interfacial properties of mixtures of monomers of polyvinylpyrrolidone (PVP)-based battery binders on graphene and graphite surfaces

This study investigates the behavior of two different mixtures of monomers of polyvinylpyrrolidone (PVP)-based battery binders, polyvinylpyrrolidone:polyvinylidene difluoride (PVP:PVDF) and polyvinylpyrrolidone:polyacrylic acid (PVP:PAA), at graphene and graphite interfaces using classical molecular dynamics simulations. The aim is to identify the best performing monomer binder blend and carbon-based material for the design of battery-optimized energy devices. The PVP:PAA monomer binder blend and graphite are found to have the best interaction energies, densification upon adsorption, and more ordered structure. The adsorption of both monomer binder blends is strongly guided by the higher affinity of PVP and PAA monomeric molecules for the surfaces compared to PVDF. The structure of adsorbed layers of PVP:PVDF monomer binder blend on graphene and graphite develops more quickly than PVP:PAA, indicating faster kinetics. This study complements a previous density functional theory study recently reported by our group and contributes to a better understanding of the nanoscopic features of relevant interfacial regions involving mixtures of monomers of PVP-based battery binders and different carbon-based materials. In conclusion, the effect of a blend of commonly used monomer binders on carbon-based materials is essential for obtaining tightly bound anode and cathode active materials in lithium-ion batteries, which is crucial for designing battery-optimized energy devices.

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

The shear Alfvén continuum of quasisymmetric stellarators

The shear Alfvén wave (SAW) continuum plays a critical role in the stability of energetic particle-driven Alfvén eigenmodes. We develop a theoretical framework to analyze the SAW continuum in three-dimensional (3-D) quasisymmetric magnetic fields, focusing on its implications for stellarator design. By employing a near-axis model and degenerate perturbation theory, the continuum equation is solved, highlighting unique features in 3-D configurations, such as the interactions between spectral gaps. Numerical examples validate the theory, demonstrating the impact of flux-surface shaping and quasisymmetric field properties on continuum structure. The results provide insights into optimizing stellarator configurations to minimize resonance-driven losses of energetic particles. This work establishes a basis for incorporating Alfvénic stability considerations into the stellarator design process, demonstrated through optimization of a quasihelical configuration to avoid high-frequency spectral gaps.

fusion plasma↗
DOE OSTI2020

Multiple-objective Reinforcement Learning for Inverse Design and Identification

The aim of inverse chemical design is to develop new molecules with given optimized molecular properties or objectives. Recently, generative deep learning (DL) networks are considered as the state-of-the-art in inverse chemical design and have achieved early success in generating molecular structures with desired properties in the pharmaceutical and material chemistry fields. However, satisfying a large number (> 10 objectives) of molecular objectives is a limitation of current generative models. To improve the model’s ability to handle a large number of molecule design objectives, we developed a Reinforcement Learning (RL) based generative framework to optimize chemical molecule generation. Our use of Curriculum Learning (CL) to fine-tune the pre-trained generative network allowed the model to satisfy up to 21 objectives and increase the generative network’s robustness. The experiments show that the proposed multiple-objective RL-based generative model can correctly identify unknown molecules with an 83% to 100% success rate, compared to the baseline approach of 0%. Additionally, this proposed generative model is not limited to just chemistry research challenges; we anticipate that problems that utilize RL with multiple objectives will benefit from this framework.

reinforcement learning, generative model, inverse ↗
DOE OSTI2024

Modeling-Based Design and Optimization of a Gradient Composite Transition Joint

An innovative additively manufactured gradient composite transition joint (AM-GCTJ) has been designed to join dissimilar metals, to address the pressing issue of premature failure observed in conventional dissimilar metal welds (DMWs) when subjected to increased cyclic operating conditions of fossil fuel power plants. The transition design, guided by computational modeling, developed a gradient composite material distribution, facilitating a smooth transition in material volume fraction and physical properties between different alloys. This innovative design seeks to alleviate structural challenges arising from distinct material properties, including high thermal stress and potential cracking issues resulting from the thermal expansion mismatch typically observed in conventional DMWs. In this study, we investigated the creep properties of transition joints comprising Grade 91 steel and 304 stainless steel through a combination of simulations and creep testing experiments. The implementation of a gradient composite design in the plate transition joint resulted in a significant enhancement of creep resistance when compared to the baseline conventional DMW. For instance, the creep rupture life of the transition joint was improved by > 400% in a wide range of temperature and stress testing conditions. Meanwhile, the failure location shifted to the base material of Grade 91 steel. Such enhancement can be primarily attributed to the strong mechanical constraint facilitated by the gradient composite design, which effectively reduced the stresses on the less creep-resistant alloy in the transition zone. Beyond examining plate joints, it is crucial to assess the deformation response of tubular transition joints under pressure loading and transient temperature conditions to substantiate and demonstrate the effectiveness of the design. The simulation results affirm that the tubular transition joint demonstrates superior resistance compared to its counterpart DMW when subjected to multiaxial stresses in tubular structures. In addition, optimization of the transition joint’s geometry dimensions has been conducted to diminish the accumulated deformation and enhance the service life. Lastly, the scalability and potential of the innovative transition joints for large-diameter pipe applications are addressed.

Zhang, Wei↗
DOE OSTI2024

Control-inspired design and power optimization of an active mechanical motion rectifier based power takeoff for wave energy converters

Ocean waves have high energy density and are persistent and predictable. Yet, converting wave energy to a useable form remains challenging. A significant hurdle is the oscillatory nature of waves resulting in the alternating loads, which necessitate the use of rectification at some stage of the energy conversion. This research effort presents a novel design of active mechanical motion rectifier (AMMR) for the power takeoff (PTO), which provides enhanced controllability and better power performance when compared to passive mechanical motion rectifiers (MMR). Inspired by transistors used in synchronous electrical rectifiers, the proposed design uses controllable electromagnetic clutches in the mechanical transmission to allow active engagement-disengagement control; thus, rectifying the oscillatory motion into a unidirectional rotation for high energy conversion efficiency and allowing the generator in unidirectional rotation to control the bidirectional wave capture structure for maximizing the power output. A semi-analytical computational approach is developed to efficiently evaluate the optimal power achieved using the proposed AMMR-based PTO and active control. It is found that the AMMR-based PTO design yields a higher optimal power than the previous passive MMR design across the wave spectrum. The influences of generator inertia and reactive power are discussed. Furthermore, the effects of control parameters on the power output and the optimal trajectories are analyzed. Wave tank tests with the AMMR prototype demonstrated the effectiveness of AMMR based PTO design and validated the numerical analysis.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Multi-scale and multi-physics analysis, design optimization, and experimental validation of heat exchangers utilizing high performance, non-round tubes

Air-to-refrigerant heat exchangers (HXs) are fundamental components in HVAC&R systems, and considerable research has been dedicated designing continually smaller, lighter, and more efficient HX designs. In recent years, researchers have leveraged advancements in Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA), and optimization algorithms to consider primary tube shape and topology optimization to design highly compact, high performance HXs for a multitude of applications. In this research, we present a computationally efficient, comprehensive, multi-scale, and multi-physics analysis and optimization method for air-to-refrigerant HXs featuring automated CFD and FEA simulations and approximation-assisted optimization. This methodology was utilized to design HXs with shape-optimized, non-round tubes which outperform current state-of-the-art tube-fin HXs without compromising structural integrity. The optimal HXs were shown to deliver similar thermal performance to the baseline HXs while also achieving more than 20% reductions in airside pressure drop and core envelope volume and more than 30% reduction in internal volume. Comprehensive experimental validation of the optimization methodology was conducted through the testing of two prototypes in a standardized wind tunnel facility under multiple operating conditions. For prototype #1 under dry evaporator conditions, the predicted heat load agreed within ± 10% of measured values and the predicted airside pressure drop agreed within ± 30%, while for dehumidifying conditions, the predicted sensible and latent heat loads agreed within ± 10% and ± 20% of the measured values, respectively. For prototype #2, the predicted condenser heat load agreed within ± 3.0% of measured values, and the predicted airside pressure drop agreed within ± 27%. The acceptable agreement between simulation and experimental results for the present application highlights the flexibility of the novel optimization methodology to design next generation HXs with improved performance and reduced volume, weight, and environmental impact.

42 ENGINEERING↗
DOE OSTI2025

Organic Electrochemical Transistor Channel Materials: Copolymerization Versus Physical Mixing of Glycolated and Alkoxylated Polymers

Organic electrochemical transistors (OECTs) feature a polymer channel capable of conducting both ions and electronic charges. The choice of the channel material is critical for OECT performance. Many efforts have focused on improving performance via the chemical tunability of conjugated polymers – through backbone, side chain, and molar mass engineering – leading to useful design principles for accumulation-mode OECT materials. However, tuning the chemical structure of conjugated polymers often requires time-consuming optimization of the synthesis route. Meanwhile, variations in molar mass, dispersity, structural defects, and metal content present challenges when attempting to analyze the detailed effects of structural modifications, as multiple performance-determining factors are often (unintentionally) changed at the same time. Therefore, this study explores blended channel materials obtained by physically mixing glycolated and alkoxylated polymers in different ratios, and compares their OECT performance with the corresponding statistical copolymers. It is shown that mixing two well-performing materials creates blends that enable rational tuning of the transistor properties without compromising on performance. Thus, channels based on blends of alkoxylated and glycolated polymers hold promise for OECT technology with tailored response, as only two materials are needed to achieve any desired side chain ratio, simplifying the optimization of OECT characteristics.

copolymerization↗
DOE OSTI2021

Dual-Solvent Li-Ion Solvation Enables High-Performance Li-Metal Batteries

Novel electrolyte designs to further enhance the lithium (Li) metal battery cyclability are highly desirable. Here, fluorinated 1,6-dimethoxyhexane (FDMH) is designed and synthesized as the solvent molecule to promote electrolyte stability with its prolonged –CF 2 – backbone. Meanwhile, 1,2-dimethoxyethane is used as a co-solvent to enable higher ionic conductivity and much reduced interfacial resistance. Combining the dual-solvent system with 1 m lithium bis(fluorosulfonyl)imide (LiFSI), high Li-metal Coulombic efficiency (99.5%) and oxidative stability (6 V) are achieved. Using this electrolyte, 20 µm Li||NMC batteries are able to retain ≈80% capacity after 250 cycles and Cu||NMC anode-free pouch cells last 120 cycles with 75% capacity retention under ≈2.1 µL mAh -1 lean electrolyte conditions. Such high performances are attributed to the anion-derived solid-electrolyte interphase, originating from the coordination of Li-ions to the highly stable FDMH and multiple anions in their solvation environments. This work demonstrates a new electrolyte design strategy that enables high-performance Li-metal batteries with multisolvent Li-ion solvation with rationally optimized molecular structure and ratio.

25 ENERGY STORAGE↗