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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Africa Battery Energy Storage Systems (BESS) Capacity Building Li-Ion Battery Degradation and Performance [Slides]

This presentation is intended for power system engineers, operators, and planners who work on isolated power systems that have (or may soon have) high levels of power generation coming from wind turbines, solar farms, and battery energy storage, which are collectively referred to as inverter-based resources. It describes the basics of lithium-ion battery energy storage systems and lithium-ion battery degradation. Battery degradation at the cell-level is explained, and then the structure and degradation of battery energy storage systems is also explained. This is intended to help power system engineers, operators, and planners to understand and effectively utilize battery energy storage systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Machine learning-led semi-automated medium optimization reveals salt as key for flaviolin production in Pseudomonas putida

Although synthetic biology can produce valuable chemicals in a renewable manner, its progress is still hindered by a lack of predictive capabilities. Media optimization is a critical, and often overlooked, process which is essential to obtain the titers, rates and yields needed for commercial viability. Here, we present a molecule- and host-agnostic active learning process for media optimization that is enabled by a fast and highly repeatable semi-automated pipeline. Its application yielded 60% and 70% increases in titer, and 350% increase in process yield in three different campaigns for flaviolin production in Pseudomonas putida KT2440. Explainable Artificial Intelligence techniques pinpointed that, surprisingly, common salt (NaCl) is the most important component influencing production. The optimal salt concentration is very high, comparable to seawater and close to the limits that P. putida can tolerate. The availability of fast Design-Build-Test-Learn (DBTL) cycles allowed us to show that performance improvements for active learning are rarely monotonous. This work illustrates how machine learning and automation can change the paradigm of current synthetic biology research to make it more effective and informative, and suggests a cost-effective and underexploited strategy to facilitate the high titers, rates and yields essential for commercial viability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Review of in situ process monitoring for metal hybrid directed energy deposition

Hybrid manufacturing, or the combination of additive and subtractive manufacturing within a single build volume is transforming the way products are being fabricated. Additive manufacturing confers unprecedented freedom of design and reduced material usage while enabling serial customization. Subtractive manufacturing provides superior surface finish and improved dimensional accuracies. Interwoven, these two digital manufacturing paradigms are enabling the rapid manufacturing of complex, highly accurate, and customized geometries in a diversity of high-performance alloys. In situ monitoring, heavily relied upon in either additive or subtractive, becomes even more crucial with the interplay of the two processes in a single combined build sequence. Moreover, challenges that do not exist in either process alone can now have a dramatic impact on final part quality: (1) a large amount of heat is generated during additive manufacturing deposition, which is primarily dissipated into the machine tooling and impacts accuracy by deforming the material and causing misaligned machining; (2) microstructure, mechanical properties, and residual stresses are the result of the complex thermal histories generated by additive manufacturing and can impact subsequent cutting performance. This comprehensive review considers previous research in monitoring and providing closed-loop control in both additive and subtractive manufacturing separately and then considers the implications of the effectiveness of these monitoring techniques when additive and subtractive processes are integrated together.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Dynamic Modelling and Performance Evaluation of a Chemisorption Heat Pump for Cold Climate

Space heating is a significant contributor to the energy consumption in residential buildings, especially in cold climates where electric-driven heat pumps lose the advantage of high efficiency and conventional gas-combustion furnaces have limited efficiency. Chemical adsorption (chemisorption) heat pumps (CSHP) have the potential for producing heating with high energy efficiency under cold operating conditions. A CSHP operates intermittently between desorption and adsorption modes, and their performance is affected by system design and transient system control. This study developed a dynamic model and used it to evaluate the daily system performance under different designs and controls, particularly the buffer tank size and the controlled minimum heating power. The simulation results revealed the effects of these parameters on the system performance and helped identify the optimal design and control for the highest coefficient of performance and heating capacity.

Yang, Zhiyao↗
DOE OSTI2020

Reconstruction of Charged Particle Tracks in Realistic Detector Geometry Using a Vectorized and Parallelized Kalman Filter Algorithm

One of the most computationally challenging problems expected for the High-Luminosity Large Hadron Collider (HL-LHC) is finding and fitting particle tracks during event reconstruction. Algorithms used at the LHC today rely on Kalman filtering, which builds physical trajectories incrementally while incorporating material e ects and error estimation. Recognizing the need for faster computational throughput, we have adapted Kalman-filterbased methods for highly parallel, many-core SIMD and SIMT architectures that are now prevalent in high-performance hardware. Previously we observed significant parallel speedups, with physics performance comparable to CMS standard tracking, on Intel Xeon, Intel Xeon Phi, and (to a limited extent) NVIDIA GPUs. While early tests were based on artificial events occurring inside an idealized barrel detector, we showed subsequently that our mkFit software builds tracks successfully from complex simulated events (including detector pileup) occurring inside a geometrically accurate representation of the CMS-2017 tracker. Here, we report on advances in both the computational and physics performance of mkFit, as well as progress toward integration with CMS production software. Recently we have improved the overall eciency of the algorithm by preserving short track candidates at a relatively early stage rather than attempting to extend them over many layers. Moreover, mkFit formerly produced an excess of duplicate tracks; these are now explicitly removed in an additional processing step. We demonstrate that with these enhancements, mkFit becomes a suitable choice for the first iteration of CMS tracking, and eventually for later iterations as well. We plan to test this capability in the CMS High Level Trigger during Run 3 of the LHC, with an ultimate goal of using it in both the CMS HLT and oine reconstruction for the HL-LHC CMS tracker.

Cerati, Giuseppe↗
DOE OSTI2026

Data mining the missing ordered phases of Li/Na metal oxides

Data-driven discovery of Li-ion and Na-ion battery materials has been pioneered by generic materials data platforms such as the Materials Project. After decades of progress, it is timely to ask whether there remain underexplored compositional spaces. Here, in this work, we present a systematic data-mining effort to uncover missing ordered binary, ternary and quaternary Li/Na-containing metal oxides using high-throughput density functional theory (DFT). Building on 19,120 stable and metastable oxides entries from the Materials Project, we performed 13,245 additional calculations through isovalent substitutions of known ground states, experimentally reported compounds, and specific prototype structures. Our study identifies 36 new ground states within the GGA/GGA + U convex hull and 45 within the r 2 SCAN convex hull. Additionally, we identified 840 metastable compounds from GGA/GGA + U and 979 from r 2 SCAN that are absent in the present Materials Project databases. Moreover, we have tripled the metastable materials in compositional spaces with a molar ratio of cation/anion >1, highlighting the overlooked opportunities in this compositional space.

25 ENERGY STORAGE↗
DOE OSTI2025

Promotional Effect of ZnO and ZrO 2 in K-Doped Fe Catalysts for CO 2 Hydrogenation to Light Olefins

Promoters play a critical role in tuning the activity and selectivity of Fe catalysts in CO 2 hydrogenation to produce light olefins, which are key building blocks in the petrochemical industry. Herein, by a combined experimental and theoretical approach, we show that high and stable performance of Fe catalysts could be achieved by taking advantage of the promotional effect of both Zn and Zr. Structural characterization indicates that ZnO could improve the dispersion and reducibility of Fe oxides and facilitate the formation of active Fe carbide species, whereas ZrO 2 could stabilize the structure and catalytic performance, especially the selectivity of hydrocarbon products. In situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) experiments suggest that carbonate, bicarbonate, formate, and methoxy are essential intermediates in the CO 2 hydrogenation to hydrocarbon products, including paraffins and olefins. The conversion kinetics of each intermediate species are dependent on the type of promoters as well as the phase structure of the active Fe species. DFT calculations revealed a strong correlation between the formation energy of surface oxygen vacancies and that of Fe carbide species in promoted Fe oxides, in accordance with experimental results. Moreover, the calculated energy profiles of CO 2 hydrogenation over different catalysts indicate that Zn could promote the activation of CO 2 and its transformation to the oxygenate intermediates, while Zr could facilitate the conversion of oxygenates to hydrocarbon precursors. Finally, the discrepancies in the evolution trend of various intermediate species on promoted Fe catalysts in the transient DRIFTS experiments can be rationalized by the differences in energy barriers of elementary or rate limiting steps.

CO2 conversion↗
DOE OSTI2026

Ecosystems for Scientific Computing in the Age of AI

Scientific computing is at an inflection point. Artificial intelligence (AI) is reshaping how scientific software is developed, how teams collaborate, how projects are governed, and how the next generation is trained. Drawing on insights from a 2025 workshop report, this article argues that the future of discovery will depend on agile, robust ecosystems built through socio-technical co-design—the intentional integration of technical and human systems. This perspective is essential for ensuring that future scientific computing remains trustworthy, sustainable, and scalable. It combines advances in AI, high-performance computing, and software with new models for cross-disciplinary collaboration, education, and workforce development. Key recommendations include building modular, trustworthy AI-enabled software ecosystems; enabling teams to integrate AI into scientific workflows while preserving human creativity, integrity, and rigor; and developing adaptive training pathways that keep pace with rapid technological change. By sharing these perspectives, we hope to stimulate broader community dialogue and encourage coordinated action.

AI↗
DOE OSTI2026

Making Small-Volume Heat Pump Water Heaters Larger: A Design Framework for Integrated Phase Change Material Heat Exchangers

Those that use electricity for water heating, the majority use resistive elements rather than heat pump water heaters (HPWHs), the latter of which use 60-70% less energy than the former. One major barrier to wider HPWH adoption is the added equipment required, which prevents current 50-80-gallon tanks on the market from fitting into smaller utility closets sized for 30-40 gallons, such as those found in manufactured housing. Additionally, these smaller HPWHs tend to underperform relative to their larger counterparts. One solution that addresses both space and performance concerns is thermal energy storage, and in particular, phase change materials (PCMs). PCMs have been studied extensively in building envelope and HVAC systems, but remain a nascent technology in residential water heating. While water itself has a uniquely high energy storage capacity, PCMs have an even higher energy storage density, thus providing the potential to elevate the performance of 40-gallon HPWHs to that of 50-gallon or larger tanks. This research is part of a larger project that seeks to utilize thermal energy storage to enable decarbonized water heating in low-income communities. In this study, we outline the design process used to produce novel PCM heat exchangers for use in small-volume HPWH tanks, including the identification of design constraints and performance targets relevant to real-world applications. In order to ensure optimal PCM utilization and tank storage capacity, we focus here on co-maximizing surface area and PCM volume in the heat exchangers; therefore, this research targets triply periodic minimal surface (TPMS) lattices. TPMS lattices boast enhanced heat transfer capabilities compared to traditional heat exchanger geometries and offer highly tailorable designs; thus, they pair well with the growing field of additive manufacturing, or 3D printing. Starting with a suite of TPMS lattices, we demonstrate a systematic approach for narrowing down feasible designs that comply with identified constraints while meeting PCM performance objectives.

25 ENERGY STORAGE↗
DOE OSTI2022

COMET: A Domain-Specific Compilation of High-Performance Computational Chemistry

The computational power increases over the past decades have greatly enhanced the ability to simulate chemical reactions and understand ever more complex transformations. Tensor contractions are the fundamental computational building block of these simulations. These simulations have often been tied to one platform and restricted in generality by the interface provided to the user. The expanding prevalence of accelerators and researcher demands necessitate a more general approach which is not tied to specific hardware or requires contortion of algorithms to specific hardware platforms. In this paper we present COMET, a domain-specific programming language and compiler infrastructure for tensor contractions targeting heterogeneous accelerators. We present a system of progressive lowering through multiple layers of abstraction and optimization that achieves up to 1.98×speedup for 30 tensor contractions commonly used in computational chemistry and beyond.

Mutlu, Erdal↗
DOE OSTI2021

SYMBIOSYS: A Methodology for Performance Analysis of Composable HPC Data Services

Microservices are a powerful new way of building, customizing, and deploying distributed services owing to their flexibility and maintainability. Several large-scale distributed platforms have emerged to serve the growing needs of data-centric workloads and services in commercial computing. Concurrently, high-performance computing (HPC) systems and software are rapidly evolving to meet the demands of diversified applications and heterogeneity. The interplay of hardware factors, software configuration parameters, and the flexibility offered with a microservice architecture makes it nontrivial to estimate the optimal service instantiation for a given application workload. Further, this problem is exacerbated when considering that these services operate in a dynamic and heterogeneous HPC environment. An optimally integrated service can be vastly more performant than a haphazardly integrated one. Existing performance tools for HPC either fail to understand the request-response model of communication inherent to microservices or they operate within a narrow scope, limiting the insight that can be gleaned from employing them in isolation. We propose a methodology for integrated performance analysis of HPC microservices frameworks and applications called SYMBIOSYS. We describe its design and implementation within the context of the Mochi framework. This integration is achieved by combining distributed callpath profiling and tracing with a performance data exchange strategy that collects fine-grained, low-level metrics from the RPC communication library and network layers. The result is a portable, low-overhead performance analysis setup that provides a holistic profile of the dependencies among microservices and how they interact with the Mochi RPC software stack. Using HEPnOS, a production-quality Mochi data service, we demonstrate the low-overhead operation of SYMBIOSYS at scale and use it to identify the root causes of poorly performing service configurations.

microservices↗
DOE OSTI2025

Does class matter? Understanding differential pandemic recovery via a building typology

This study investigates the recovery of building-level footfall from the COVID-19 pandemic using privacy-preserving mobile devices-based footfall data within 60 downtown areas in the USA and Canada. Using clustering, we identify five distinct building typologies based on their characteristics, including rent, quality and recovery rates. The results reveal significant variation of recovery rates by building features. We find negative relationships with footfall recovery for both the percentage of office and remote work tenants and building quality. In contrast, buildings with traditional work tenants and retail functions achieve higher recovery rates. We also test the ‘flight to quality’ hypothesis via on our typology results. High-quality office buildings (Class A+) continue to have high rents but experience low physical footfall recovery, which suggests that this class is not as resilient as portrayed. The findings thus suggest the importance of considering both economic and footfall resilience in evaluating the performance of office buildings.

Covid-19↗
DOE OSTI2022

Electron Cloud Measurements in Fermilab Booster

Fermilab Booster synchrotron requires an intensity upgrade from 4.5x1012 to 6.5x1012 protons per pulse as a part of Fermilabs Proton Improvement Plan-II (PIP-II). One of the factors which may limit the high-intensity performance is the fast transverse instabilities caused by electron cloud effects. According to the experience in the Recycler, the electron cloud gradually builds up over multiple turns in the combined function magnets and can reach final intensities orders of magnitude greater than in a pure dipole. Since the Booster synchrotron also incorporates combined function magnets, it is essential to discover any existence of an electron cloud. And if it does, its effects on the PIP-II era Booster and its mitigating techniques. As the first step, the presence or absence of the electron cloud was investigated using the clearing bunch technique. This paper presents experimental details and observations of the bunch-by-bunch tune shifts of beams with various bunch train structures at low and high intensities and simulation results conducted using PyECLOUD.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Unlocking the Value of Deep Energy Retrofits

This publication is based on an extensive study conducted on behalf of the New York State Energy Research and Development Authority (NYSERDA) and the U S Department of Energy (DOE) to explore financial and risk products to accelerate the implementation of deep energy retrofit (DER) solutions to reduce costs These financial products are intended to speed market development via three fundamental themes: reallocating risk from building owners and lenders to insurers, quantifying and monetizing previously unrecognized value associated with DERs, and providing building owners and lenders with confidence in the performance of building systems Findings are based on a comprehensive analysis and characterization of 100+ existing DER case studies, and more than 40 qualitative interviews with industry experts, including insurers, researchers, building owners, and policymakers In addition, a quantitative model of overall project economics with baseline, high, and low cases was developed This data informed the analysis that resulted in three recommended financial product solutions, which were evaluated for their potential to raise projected cash flows and finance DERs: 1) Building System Performance and Energy Savings Guarantee; 2) Trade Credit Insurance; 3) Ancillary Revenue Contracts. This report identifies many value streams associated with DERs and introduces these three potential financial products, which aim to reallocate risks and reduce barriers to the adoption of advanced envelope DERs.

ancillary renenue contracts↗
DOE OSTI2020

The Role of Competitions in Speeding Energy-Efficient Technology Development and Adoption

This conference paper, which will be submitted for publication in the 2020 ACEEE Summer Study on Energy Efficiency in Buildings, describes competition approaches used by the U.S. Department of Energy (DOE) Building Technologies Office (BTO) and other government agencies to encourage the development and adoption of innovative new energy-efficient, high-performing products while spurring external competition to maximize limited resources. The competition model helps to disrupt traditional thinking and introduce, expand, and evolve what’s possible within limited resource conditions. DOE BTO has sponsored technology competitions, including campaigns, challenges, prizes, and technology procurements to speed the uptake of more efficient refrigerators, clothes washers, air conditioners, and many types of highly efficient lighting technologies, including compact fluorescent lamps (CFLs) and light-emitting diode LED-based home and office luminaires, replacement lamps, and street lighting. In this paper, we will draw upon the technology competition frameworks employed by DOE BTO to support ongoing research and development efforts to illustrate the differences between the approaches and to identify which type is likely to be the most effective in a given technology status and market context. We’ll also share examples of the various technology competition types and results. A question-and-answer table helps readers compare and contrast the four competition types. The paper concludes with a summary of lessons learned from past DOE BTO competitions. The paper will be available in the ACEEE 2020 Summer Study proceedings and a related presentation will be given at the conference.

U.S. Department of Energy Building Technologies Of↗
DOE OSTI2024

The Grain Boundary Relaxation (GBR) Approach for Manufacturing High Strength Nanocrystalline Lightweight Metals

The overarching goal of the project was to conduct research and development work as proposed in the Statement of Project Objective (SOPO) of the award document DE-FE-0009116. The project had 4 tasks and 12 milestones. All the milestone deliverables were completed. The accomplishments of the project objectives and technical discussions are described in Sections 3 and 4, respectively. The modeling and simulation work indicated that to increase the strength and stability of nanocrystalline aluminum (Al), selection of dopants, such as Mg, is necessary. It was predicted that the crystallite size should be less than 50 nm to give high strength. On the basis of modeling, cryo-milling of Al was conducted with the addition of Mg as a function of different times. The crystallite size of the cryo-milled powders was determined by XRD and TEM. Both measurements showed that the actual crystallite size of the grain was <40 nm. The thermal stability of the grain size was established as a function of temperature. It was established that the grain size was < 50 nm up to 500C. The crystallite size of the bulk sample prepared by spark plasma sintering (SPS) and cold spray (CS) additive manufacturing was less than <40 nm. The mechanical properties of the bulk samples prepared by SPS and CS, showed excellent microhardness, good tensile properties (>200 MPa) with moderate ductility and improved fatigue performance. Adding yttria stabilized zirconia (YSZ) improved the build thick of the CS sample, however the YSZ was getting embedded into the sample. A highly dense SPS samples sent for 3rd party testing to the Innovation Testing Services showed a minimum hardness of 180 HV with an average tensile strength of 512.5 MPa. The high cycle fatigue tests also showed an endurance limit of 179.5 MPa. The Energy cost evaluations showed an overall energy cost of around $\$$17.05 for the cryomilling and SPS processes and the total manufacturing cost calculations of $\$$78.14 for 1 kg of sample. The energy cost to prepare a Kg of CS sample is $\$$17.60 and the overall manufacturing cost is $\$$86.85.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Automatic and rapid calibration of urban building energy models by learning from energy performance database

Urban building energy modeling (UBEM) is attracting increasing attention in the energy modeling filed. Unlike modeling a single building using detailed building systems information, UBEM generally uses limited high-level building stock data to infer default assumptions about building characteristics and operations. Additionally, this practice inherently brings uncertainty to UBEM. This study introduced a novel method of automatic and rapid calibration of UBEM based on the annual electricity and natural gas energy use data by learning the correlations between crucial model input parameters and the building energy use from the reference building models. A case study was presented to calibrate 72 large office buildings built before 1978 in San Francisco. Seventeen model parameters were selected and Monte Carlo sampling was used to create 1000 samples that reasonably represent the parameter space. Then 1000 simulations were performed for the reference building model to create an energy performance database. The results showed that by learning from the energy performance database, it took less than four simulation runs on average to calibrate a building model. After the calibration, the distributions of each parameter were obtained to replace their single predefined default values. For example, the default lighting power density of 21.39 W/m 2 was calibrated to be 7.50 W/m 2 on average. The case study successfully demonstrated the effectiveness of the novel calibration method for UBEM in the mild climate. The method will be further tested in future for other climate zones and other building types.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Energy savings and life cycle cost analysis of advanced double skin facade system applied to old apartments in South Korea

South Korea is one of the most densely populated countries in the world, and the population density in urban areas is much higher among others. Apartments are the most common form of residential buildings due to their high population density. More than 60% of domestic residential buildings are apartments, with more than 10 million households. The high population density is a problem that has long plagued South Korea because more than 45% of apartments are old apartments that are more than 20 years old. Old apartment buildings have low thermal performance that results in lots of energy consumption. Balconies, which worked as a thermal buffer, are also being removed by residents to expand indoor space. According to the green remodeling project supported by the Korean government, the typical retrofitting method is replacing external windows with the high-efficiency window in old apartments in South Korea. Here, this paper proposes a retrofitting method using an extended double-skin façade (DSF) system that replaces exterior windows and acts as a thermal buffer. The simulation model is developed with the EnergyPlus simulation program to conduct energy performance analyses. The simulation model has been calibrated using actual experimental data collected between October 1, 2019, and January 15, 2020. Results show that the cooling, heating, and lighting energy can be reduced up to 44.1% by fully utilizing electric energy generated by solar PV panels integrated with the DSF system. The payback period is about 15 years based on the energy price provided by the utility company. Although the payback period is long, it has great potential of energy savings and CO 2 emission reductions. The DSF system should be considered as a way of renovation, considering other factors such as increased real estate values and energy cost increases in the future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗