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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Behind the Meter Storage for Electric Vehicle Charging, Electrochemical and Thermal Energy Storage, and Solar Photovoltaic

In response to the potentially large and irregular demand from EVs, along with changing load profiles from buildings with on-site generation, utilities are evaluating multiple options for managing dynamic loads, including time-of-use pricing, demand charges, battery storage, and curtailment of variable generation. Buildings, as well as commercial, public, and workplace EV charging operations, can use a combination of electrochemical battery storage and thermal energy storage coupled with on-site generation to manage energy costs as well as provide resiliency and reliability for EV charging and building energy loads. We are completing a behind the meter storage analysis that focuses on determining the optimal system designs and energy flows for thermal and electrochemical behind the meter storage with on-site solar photovoltaic (PV) generation enabling electric vehicle charging in various climates, building types, and utility rate structures. In completing this analysis, we have developed a tool that combines existing battery models via the System Advisor Model (SAM) and building modeling software via EnergyPlus into a single interface. This tool allows us to simulate a building with a detailed battery model to properly size the battery, thermal energy storage, and solar PV systems to maximize profit for the system owner. This also allows us to assess how the battery degrades under various supervisory control dispatch algorithms to control charging/discharging; we can also see how thermal energy storage is created and used to complement the battery to reduce thermal loads in the building. With this project, we can analyze new batteries that are designed specifically for energy storage, rather than designed to be extremely energy dense for electric vehicle applications, using battery lifetime models from other national labs and the existing SAM battery model, which has detailed lifetime and degradation parameters. We can also assess novel thermal storage technologies by integrating them into the whole building energy simulation program EnergyPlus. Because the model calls both SAM and EnergyPlus, required inputs need to be compatible for both models. These inputs include, on a high-level, the following: weather files, building and electric vehicle load profiles, electricity rate tariff information, and system cost information for the stationary battery, solar PV, and thermal storage system. The various buildings we are studying for this analysis are retail big-box grocery store, commercial office building, fleet vehicle depot and operations facility, multi-family residential, and electric vehicle charging station. For these different applications, the battery and thermal storage will be dispatched differently, and the various technologies are sized differently to optimize cost.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Aluminum/SmCo 5 composites for structural and magnetic applications

Metal-bonded magnetic composites (MBMCs) present a promising alternative to dense sintered magnets, particularly for intricate components. Compared to polymer-based bonded magnets, MBMCs have wider applicability in harsh environments. In this paper, we demonstrate a solid-state shear-based manufacturing technique to introduce localized magnetization into a paramagnetic aluminum matrix by embedding SmCo5 permanent magnet particles. Our magnetic composites display hard magnetic behavior with a coercivity of 13 kOe and a remanent magnetization of 4.32 emu/g. In addition to magnetization, we also report a 9% improvement in Young’s modulus. Despite the local temperature rise during processing, the magnetic phases didn’t decompose into unwanted phases, preserving the composite's hard magnetic properties. Creation of an interfacial metallurgical bond with the matrix ensured the suitability of the composites for structural applications. Our study investigates the mechanical, and functional properties of composites, paving the way for lightweight structural magnetic composites with a transformative potential in the aerospace, nuclear, and automotive applications. This work underscores the potential for further optimization and development to drive innovations in magnet and equipment design.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Coarse-Grained Simulations for the Characterization and Optimization of Hybrid Protein–DNA Nanostructures

We present here the combination of experimental and computational modeling tools for the design and characterization of protein–DNA hybrid nanostructures. Our work incorporates several features in the design of these nanostructures: (1) modeling of the protein–DNA linker identity and length; (2) optimizing the design of protein–DNA cages to account for mechanical stresses; (3) probing the incorporation efficiency of protein–DNA conjugates into DNA nanostructures. The modeling tools were experimentally validated using structural characterization methods like cryo-TEM and AFM. Our method can be used for fitting low-resolution electron density maps when structural insights cannot be deciphered from experiments, as well as enable in-silico validation of nanostructured systems before their experimental realization. Finally, these tools will facilitate the design of complex hybrid protein–DNA nanostructures that seamlessly integrate the two different biomolecules.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Origin of core-to-core x-ray emission spectroscopy sensitivity to structural dynamics

Recently, coherent structural dynamics in the excited state of an iron photosensitizer was observed through oscillations in the intensity of Kα x-ray emission spectroscopy (XES). Understanding the origin of the unexpected sensitivity of core-to-core transitions to structural dynamics is important for further development of femtosecond time-resolved XES methods and, we believe, generally necessary for interpretation of XES signals from highly non-equilibrium structures that are ubiquitous in photophysics and photochemistry. Here, we use multiconfigurational wavefunction calculations combined with atomic theory to analyze the emission process in detail. The sensitivity of core-to-core transitions to structural dynamics is due to a shift of the minimum energy metal–ligand bond distance between 1s and 2p core-hole states. A key effect is the additional contraction of the non-bonding 3s and 3p orbitals in 1s core-hole states, which decreases electron– electron repulsion and increases overlap in the metal–ligand bonds. The effect is believed to be general and especially pronounced for systems with strong bonds. The important role of 3s and 3p orbitals is consistent with the analysis of radial charge and spin densities and can be connected to the negative chemical shift observed for many transition metal complexes. The XES sensitivity to structural dynamics can be optimized by tuning the emission energy spectrometer, with oscillations up to ±4% of the maximum intensity for the current system. The theoretical predictions can be used to design experiments that separate electronic and nuclear degrees of freedom in ultrafast excited state dynamics.

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

Photon-magnon coupling using gain-assisted spoof-localized surface plasmons

Improving the photon-magnon coupling strength can be done by tuning the structure of microwave resonators to better interact with the magnon counterpart. Planar resonators accommodating unconventional photon modes beyond the half- and quarter-wavelength designs have been explored due to their optimized mode profiles and potentials for on-chip integration. Here, we designed and fabricated an actively controlled ring resonator supporting the spoof localized surface plasmons (LSPs), and implemented it in the investigation of photon-magnon coupling for hybrid magnonic applications. We demonstrated gain-assisted photon-magnon coupling with the YIG magnon mode under several different sample geometries. The achieved coupling amplification largely benefits from the high quality factor (Q-factor) due to the additional gain provided by a semiconductor amplifier, which effectively increases the Q-factor from a nearly null state (passive resonance) to more than 1000 for a quadrupole LSP mode. Our results suggest an additional control knob for manipulating photon-magnon coupled systems exploiting external controls of gain and loss.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Evaluation of Additively Manufactured Monolithic SiC and SiC Ceramic Matrix Composites for CSP- Fabrication and Testing of Receiver Design Feature Specimens in a Simulating Lab Test via Laser Heating

Critical to the creation of a multi-component SiC receiver design concept capable of meeting the SETO CST cost goal objectives of <$150/kWth is the optimal utilization of material for solar absorption and heat transfer to transport fluid. This is to maximize the solar-thermal efficiency in the techno-economic analysis of derived use case. As a first step in preparation of sub-component design for on-sun test evaluations we use different proposed SiC absorber element in a customized laser heat flux test to assess an effective heat transfer coefficient characteristic of the design. The test results are analyzed to extract the effective heat transfer coefficient, thus enable optimization of the geometry of receiver components for heat transfer, efficiency attributes and the thermo-structural management of the components. High intensity CO2 laser is used in combination with air flow through the test specimen to assess the effective heat transfer coefficient under heat flux conditions corresponding to high solar concentrations in the range of 1000-2000 suns.

14 SOLAR ENERGY↗
DOE OSTI2024

Transformer Neural Networks with Spatiotemporal Attention for Predictive Control and Optimization of Industrial Processes

In the context of real-time optimization and model predictive control of industrial systems, machine learning, and neural networks represent cutting-edge tools that hold promise for enhancing dynamic modeling. This work presents a novel transformer neural network architecture for real-time optimization and model predictive control. This network design includes a modified attention mechanism inspired by positional embedding attention from vision transformers and task-specific modifications to the input-output structure of the transformer’s decoder stack. Experiments were conducted using data from a 450 MW coal-fired power plant to evaluate this approach's effectiveness. The transformer neural network was compared with conventional recurrent models, including GRU and LSTM. The transformer exhibited a 6% increase in the R-squared (R2) value of predictions and an 83% reduction in mean squared error (MSE). Computation time was also reduced by 84% compared to conventional recurrent models.

Gallup, Ethan R.↗
DOE OSTI2025

Feedforward equilibrium trajectory optimization with GSPulse

One of the common tasks required for designing new plasma scenarios or evaluating capabilities of a tokamak is to design the desired equilibria using a Grad-Shafranov (GS) equilibrium solver. However, most standard equilibrium solvers are time-independent and do not include dynamic effects such as plasma current flux consumption, induced vessel currents, or voltage constraints. Another class of tools, plasma equilibrium evolution simulators, do include time-dependent effects. These are generally structured to solve the forward problem of evolving the plasma equilibrium given feedback-controlled voltages. In this work, we introduce GSPulse, a novel algorithm for equilibrium trajectory optimization, that is more akin to a pulse planner than a pulse simulator. GSPulse includes time-dependent effects and solves the inverse problem: given a user-specified set of target equilibrium shapes, as well as limits on the coil currents and voltages, the optimizer returns trajectories of the voltages, currents, and achievable equilibria. This task is useful for scoping performance of a tokamak and exploring the space of achievable pulses. The computed equilibria satisfy both Grad-Shafranov force balance and axisymmetric circuit dynamics. The optimization is performed by restructuring the free-boundary equilibrium evolution equations into a form where it is computationally efficient to optimize the entire dynamic sequence. GSPulse can solve for hundreds of equilibria simultaneously within a few minutes. GSPulse has been validated against NSTX-U and MAST-U experiments and against SPARC feedback control simulations, and is being used to perform scenario design for SPARC. The computed trajectories can be used as feedforward inputs that are connected to the feedback controller to inform and improve feedback performance. The code for GSPulse is available open-source at github.com/jwai-cfs/GSPulse_public.

equilibrium↗
DOE OSTI2025

Design and Study of Inductively Coupled Plasma Chamber Components Using the SupRISE Test Device at DIII-D

The DIII-D National Fusion Facility aims to increase the auxiliary heating power for the tokamak by upgrading the Neutral Beam Injection (NBI) system. In collaboration with North Carolina State University, the conventional ‘arc and filament’ NBI ion sources will be converted to inductively coupled plasma (ICP) sources which utilize radio frequency (RF) coupling to maximize reliability for high power operation. In support of this initiative, a full scale test device (SupRISE, Superior Radiofrequency Ion Source Experiment) is currently under construction at the DIII-D Facility. In preparation for the construction of a full scale prototype that can be installed on the DIII-D NBI system, experiments on SupRISE will be conducted to determine the optimal RF frequency for high power coupling, Faraday shield slit configuration, and ICP chamber length. SupRISE is comprised of an approximately 30 x 70 cm quartz dielectric vessel with an internal Faraday shield enclosed in a secondary vacuum chamber to ensure structural stability of the dielectric. Actively cooled front and back plates are designed to reduce the thermal stresses on the plasma facing components and mate with the existing accelerator used by the NBI system at DIII-D. 50 kW of RF power will be coupled to the plasma through the quartz over a variable frequency range of 4-8 MHz to sustain a plasma density of ∼ 10 18 m −3 for a 10 s ON, 210 s OFF duty cycle. Various modelling efforts have been employed to simulate the thermal and stress profiles over the primary components of the SupRISE device as well as the inductance behavior of the RF antenna. These simulation results and the final design for SupRISE will be presented. An additional reduced-scale predecessor ICP source (called RISE) has been used to develop a predictive match model that will be applied to frequency optimization studies on SupRISE. Furthermore, the outcomes of this research and complementary efforts at North Carolina State University are essential for the incorporation of ICP NBI positive ion sources at the DIII-D facility.

DIII-D↗
DOE OSTI2021

Tailored Fiber Placement for Complex Preforms

Tailored Fiber Placement (TFP) offers a novel approach to optimize fiber architecture for the fabrication of complex, structural parts not traditionally suitable for advanced composites. This technology not only offers new routes for weight reduction via metal substitution, it also offers cost reduction through minimization of material scrap and reduced labor. This reduction in component weight leads to increased fuel efficiency, and reduced production energy consumption, thereby, helping to achieve the stated IACMI technical goals. This technology leverages centuries of manufacturing development in support of the textile and embroidery industry. One major drawback to this technology is the lack of commercial or non- proprietary structural performance data and robust analytical tools used to optimize fiber architecture and predict performance. This project was structured to utilize common sub-element features to validate analytical performance tools, generate performance data, and gather cost and performance data on components of interest. This project was designed to give industry sponsors the confidence and ability to take full advantage of TFP to fabricate primary, highly loaded structure and integrate features such as metallic fasteners. The project focused principally on the use of high strength carbon fiber, such as T700, and the use of aerospace epoxy resin matrix to primarily support development of new composite applications in vehicle, aerospace, and industrial markets. This project applied previously developed analytical tools to predict the performance of TFP produced parts. This work focused on developing the pipeline to characterize material in order to accurately predict component performance when modifying the TFP print paths and stitch density. This focused on experimental characterization via standardized ASTM testing, alongside experimental testing of more representative service components by testing curved beam strength, beam shear performance, a large scale TFP lug, and ultimately designing a fully TFP clip bracket that reduced weight and cost compared to a traditional metallic component. The new knowledge gained from this program included: 1) development and demonstration of novel analytical tools applied to analysis of TFP preforms; 2) development and demonstration of a building block approach using coupons and sub-elements to optimize the design of a more complex component; 3) demonstration that optimized fiber orientation using TFP can exceed performance of conventional textile composite materials and can open new applications currently limited to metallic components; 4) Demonstration of performance and cost benefits of the TFP process as compared to metallic and conventional textile composites. Recommendations for follow-on work include development of design allowables to assess the impact of high temperature/moisture exposure or saturation during loading, tracking the impact of stitching needle wear on the performance of parts and ability to stitch thicker preforms, using TFP preforms as local reinforcement at areas of bearing or complex loading, and topology optimization of components by tow steering. The expertise developed during the course of this project can be leveraged to provide commercial engineering design and fabrication services using TFP. UDRI is in the process of formalizing their partnership with Spintech, who will serve as the commercialization partner for this technology and provide molding services and deliver finished components to the end user. UDRI will continue to produce the preforms until the economics allow Spintech to procure its own TFP equipment or lease UDRI equipment, at which point UDRI will step away from manufacture and serve as the engineering and design lead on product development.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Optimizing the self-assembly of conjugated polymers and small molecules through structurally programmed non-covalent control

Organic conjugated polymers and oligomers are key electronic materials for applications such as transistors, photovoltaics, and light emitting devices due to their potential for solution processability, mechanical flexibility, and precise structure-based tuning compared to inorganic materials. In dilute environments, the optoelectronic properties of conjugated polymers are largely governed by their constitutional structure and, to a lesser degree, their solution-state intramolecular configuration. In the solid state, intramolecular conformation and intermolecular electronic coupling impact these properties substantially, especially in relation to device performance. Therefore, an increasingly important area of research concerning conjugated materials is developing design strategies aimed at optimizing the solid-state packing for electronic applications. Programming solid-state packing arrangements through discrete non-covalent interactions is an emerging strategy within the context of conjugated polymers. This review focuses on the use of the two most prevalent discrete and directional interactions used to dictate the self-assembly of conjugated polymers and oligomers—hydrogen bonds and chalcogen bonds. Further, we also discuss how these design motifs can imbue conjugated materials with appealing physical properties while simultaneously retaining or improving electronic capabilities.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Glass formulation and composition optimization with property models: A review

Abstract Glass is a versatile material with a remarkable history and many practical applications. It plays a critical role in our everyday lives, the advancement of science, and the development of many technologies. The Edisonian type trial‐and‐error method was commonly used for conventional design of glass compositions, which was time‐consuming and costly. With the urgent need to develop new glass compositions for technology applications rapidly, it has become necessary to develop precise property models with predictive powers using large databases and efficient formulation approaches. This paper reviews the design of glass compositions using these analytical and numerical models of composition–structure–property relations of glasses, some based on large databases and machine learning approaches. Aspects of data collection, model fitting, feature extraction, model evaluation, and uncertainty quantification will be covered. Furthermore, advances in the glass optimization framework and available tools are summarized with examples. The outlook and perspective for further glass property model development and formulation approaches are discussed.

Lu, Xiaonan↗
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 OSTI2024

Designing workflows for materials characterization

Experimental science is enabled by the combination of synthesis, imaging, and functional characterization organized into evolving discovery loop. Synthesis of new material is typically followed by a set of characterization steps aiming to provide feedback for optimization or discover fundamental mechanisms. However, the sequence of synthesis and characterization methods and their interpretation, or research workflow, has traditionally been driven by human intuition and is highly domain specific. Here, we explore concepts of scientific workflows that emerge at the interface between theory, characterization, and imaging. In this study, we discuss the criteria by which these workflows can be constructed for special cases of multiresolution structural imaging and functional characterization, as a part of more general material synthesis workflows. Some considerations for theory–experiment workflows are provided. We further pose that the emergence of user facilities and cloud labs disrupts the classical progression from ideation, orchestration, and execution stages of workflow development. To accelerate this transition, we propose the framework for workflow design, including universal hyperlanguages describing laboratory operation, ontological domain matching, reward functions and their integration between domains, and policy development for workflow optimization. These tools will enable knowledge-based workflow optimization; enable lateral instrumental networks, sequential and parallel orchestration of characterization between dissimilar facilities; and empower distributed research.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Molecular concentration field design using closed-form steady-state solutions

Control over spatial concentration fields represents a fundamental challenge in designing synthetic biological systems and programmable soft materials. While nature creates morphogen gradients that orchestrate complex developmental processes, synthetic approaches have largely relied on empirical optimization and computationally intensive simulations. Here, we present an analytical framework for steady-state concentration fields generated by finite-sized localized sources in diffusion–degradation systems and derive closed-form solutions for one-, two-, and three-dimensional geometries. By expressing these solutions in dimensionless form, we show that gradient steepness and spatial structure are organized by the Thiele modulus, which captures the competition between diffusion and degradation length scales. The analysis reveals distinct design regimes: in degradation-dominated systems, gradient shape is governed by exponential decay and becomes dimension-independent, whereas in diffusion-dominated systems, gradient magnitude and extent follow dimension-dependent power-law scaling. Building on these results, we introduce a quantitative design strategy that uses threshold-based criteria to program concentration ranges by tuning physically accessible parameters, most directly the production rate, while holding transport and degradation properties fixed. Comparisons with numerical solutions and reported experimental systems demonstrate consistency with the predicted scaling behavior. Together, this work provides a generalizable and physically transparent framework for designing steady-state concentration fields in synthetic biological and soft matter systems, enabling predictive control of gradient-mediated organization without reliance on extensive numerical optimization.

Kim, Dong Woo [Johns Hopkins University, Baltimore↗
DOE OSTI2026

Non‐Equilibrium Synthesis Methods to Create Metastable and High‐Entropy Nanomaterials

Stabilizing multiple elements within a single phase enables the creation of advanced materials with exceptional properties arising from their complex composition. However, under equilibrium conditions, the Hume–Rothery rules impose strict limitations on solid-state miscibility, restricting combinations of elements with mismatched crystal structures, atomic radii, valence states, or electronegativities. This severely narrows the accessible compositional space for creating new inorganic materials. In this review, we highlight how non-equilibrium synthesis methods, featuring ultrafast heating and quenching, can overcome these thermodynamic barriers, enabling integration of immiscible elements into metastable and high-entropy nanostructures. The resulting materials benefit from both kinetic trapping and stabilization by high configurational entropy, leading to enhanced phase stability. These materials can exhibit unique structural and functional properties that are needed for advancing catalysis, energy storage, thermoelectrics, and sensing. Furthermore, the ability of non-equilibrium methods to generate unconventional compositions and structures expands the material design space dramatically, offering rich datasets for AI-guided materials discovery. When combined with their inherent high-throughput and scalable characteristics, these approaches enable rapid, iterative optimization and accelerate the development and industrial production of next-generation inorganic materials.

high-entropy materials↗
DOE OSTI2021

TEQUILA: a platform for rapid development of quantum algorithms

Variational quantum algorithms are currently the most promising class of algorithms for deployment on near-term quantum computers. In contrast to classical algorithms, there are almost no standardized methods in quantum algorithmic development yet, and the field continues to evolve rapidly. As in classical computing, heuristics play a crucial role in the development of new quantum algorithms, resulting in a high demand for flexible and reliable ways to implement, test, and share new ideas. In this paper, inspired by this demand, we introduce TEQUILA, a development package for quantum algorithms in PYTHON, designed for fast and flexible implementation, prototyping and deployment of novel quantum algorithms in electronic structure and other fields. TEQUILA operates with abstract expectation values which can be combined, transformed, differentiated, and optimized. On evaluation, the abstract data structures are compiled to run on state of the art quantum simulators or interfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Nanoporous Materials Genome Center Final Technical Report

Nanoporous materials (NPMs), including zeolites/zeotypes, metal-organic frameworks (MOFs), covalent organic frameworks, polymers with intrinsic microporosity, and molecular cages, possess enormous potential in diverse areas relevant to the DOE Office of Science Basic Energy Sciences (BES) mission and objectives. The Nanoporous Materials Genome Center (NMGC) has developed exascale-ready software, computational/theoretical chemistry methods, and data-driven science approaches that enable (i) the de-novo design of functional NPMs for chemical separation and catalysis tasks of increasing complexity, (ii) the discovery of the most promising functional NPMs from databases of synthesized and hypothetical adsorbent structures and the optimization of process conditions for specific applications, and (iii) the microscopic-level understanding of the fundamental interactions underlying the function of NPMs including hierarchical architectures, composite materials, responsive frameworks that may undergo phase transitions or post-synthetic modifications, and materials containing defects, partial disorder, or interfaces. A pivotal part of the NMGC project has been a tight collaboration between leading experimental groups for synthesis and characterization of NPMs and of computational groups that allowed for iterative feedback. The NMGC project has resulted in the publication of more than 290 research and review articles including more than 60 publications in high-impact journals and more than 15 journal covers. NMGC publications have already received more than 20,000 citations (with more than 3,000 citations per year in 2021, 2022, and 2023) and contribute to an h-index of more than 72. The NMGC award has supported collaborative research involving 28 research groups and contributed to the training of more than 40 postdocs, more than 60 graduate students, and more than 20 undergraduate students with broad expertise in data-driven science approaches, computational chemistry methods, and high-performance computing, in addition to the skills to thrive in an integrated experimental and computational research environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗