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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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24 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A high-throughput experimentation platform for data-driven discovery in electrochemistry

Automating electrochemical analyses combined with artificial intelligence is poised to accelerate discoveries in renewable energy sciences and technologies. This study presents an automated high-throughput electrochemical characterization (AHTech) platform as a cost-effective and versatile tool for rapidly assessing liquid analytes. The Python-controlled platform combines a liquid handling robot, potentiostat, and customizable microelectrode bundles for diverse, reproducible electrochemical measurements in microtiter plates, minimizing chemical consumption and manual effort. To showcase the capability of AHTech, we screened a library of 180 small molecules as electrolyte additives for aqueous zinc metal batteries, generating data for training machine learning models to predict Coulombic efficiencies. Key molecular features governing additive performance were elucidated using Shapley Additive exPlanations and Spearman’s correlation, pinpointing high-performance candidates like cis-4-hydroxy-d-proline, which achieved an average Coulombic efficiency of 99.52% over 200 cycles. The workflow established herein is highly adaptable, offering a powerful framework for accelerating the exploration and optimization of extensive chemical spaces across diverse energy storage and conversion fields.

Lin, Dian-Zhao [Johns Hopkins University, Baltimor↗
DOE OSTI2025

Self-Driving Microscopy for AI/ML-Enabled Physics Discovery and Materials Optimization

Materials are the bedrock of economy and foundation for all real-world technologies. The viability of space travel, grid energy storage, solar to fuels conversion, methane removal, and photovoltaic energy solutions hinge on the discovery and optimization of novel materials and rapid scaling toward manufacturing. The last 20 years have seen an exponential growth in the theoretical predictive capability for crystalline materials and small molecules. However, it is only in the last five years that we have seen the rapid expansion of high-throughput synthesis enabled by laboratory robotics and microfluidics, as well as a resurgence of combinatorial synthesis (Abolhasani and Kumacheva 2023; Epps and Abolhasani 2021; Jiang et al. 2022; Rajan 2008; Soldatov et al. 2021; Szymanski et al. 2023). Combinatorial synthesis, microfluidics, and ultimately dip-pen megalibraries have demonstrated the ability to “write” multicomponent nanomaterials at high throughput scale, generating millions of material examples in the 3D, 4D, and 5D composition spaces (Chen et al. 2016, 2019; Jibril et al. 2022).

36 MATERIALS SCIENCE↗
DOE OSTI2020

Chemical Robotics Enabled Exploration of Stability in Multicomponent Lead Halide Perovskites via Machine Learning

Metal halide perovskites have attracted immense interest as a promising material for a variety of optoelectronic and sensing applications. However, issues regarding long-term stability have emerged as the key bottleneck for commercialization. Here, we develop an automated experimental workflow based on combinatorial synthesis and rapid throughput characterization to explore long-term stability of these materials in ambient conditions. We apply it to four model perovskite systems: MA x FA y Cs 1–x–y PbBr 3 , MA x FA y Cs 1–x–y PbI 3 , Cs x FA y MA 1–x–y Pb(Br x+y I 1–x–y ) 3 , and Cs x MA y FA 1–x–y Pb(I x+y Br 1–x–y ) 3 . Non-negative matrix factorization and Gaussian process regression are used to interpolate the photoluminescent behavior of the phase diagram. This interpolative regression analysis helps to distinguish mixtures that form solid solutions from those that segregate into multiple materials, pointing out the most stable regions of the phase diagram. Here, we find stability dependence on composition to be nonuniform within the composition space, suggesting the presence of potential preferential compositional regions. This proposed workflow is universal and can be applied to other solution-processable materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

U.S. Industrial and Commercial Motor System Market Assessment Report Volume 1: Characteristics of the Installed Base

Motor systems are an integral part of our industrial and commercial facilities. They provide the motive force behind the fans, pumps, compressors, chillers, and conveyors in these facilities. Given their centrality to any facility’s operations, they are a critical energy end use to understand, particularly when developing technologies and policies to meet sustainability goals, improve productivity, and enhance resilience. In the late 1990s, the U.S. Department of Energy (DOE) conducted two seminal studies to better understand the installed stock and energy savings opportunities of industrial and commercial motor systems. In the industrial sector, The United States Industrial Electric Motor Systems Market Opportunities Assessment used primary data collected through onsite assessments and led to a greater understanding of the installed base of motor systems, their characteristics, and the opportunities for energy savings (U.S. Department of Energy, 2002). Notable findings included the following: Industrial motor systems consumed 679 billion kilowatt-hours (kWh) in 1994, representing 23 percent of U.S. electricity consumption. Cost-effective energy efficiency measures could result in 62-104 billion kWh of energy savings annually. Sixty-two percent of the energy savings potential was from fan, pump, and compressor end use equipment. Nearly half of motor system electricity consumption was attributable to approximately 3,500 facilities, or 1.5 percent of U.S. manufacturing facilities. Opportunities for Energy Savings in the Residential and Commercial Sectors with High Efficiency Electric Motors provided an evaluation of the installed stock of motor driven equipment in U.S. commercial and residential buildings and opportunities for utilization of high efficiency motors and variable speed technologies (Arthur D. Little, 1999). Notable findings included the following: Commercial motor systems consumed 343 billion kWh in 1995, with refrigeration and space conditioning constituting 93 percent of the total. Cost-effective energy efficiency measures could result in 51 billion kWh of energy savings annually. Due in no small part to these seminal studies, motor system technologies and usage characteristics have changed drastically since the late 1990s. Greater awareness of cost-effective strategies for reducing motor system electricity consumption have been developed and deployed. This includes several software tools, literature, and utility and government programs promoting energy efficiency improvements in motor driven systems. Additionally, several rounds of energy efficiency standards have been enacted, resulting in improved installed motor efficiency. The cost of variable speed drives has dropped substantially, and combined with utility rebate programs, has led to their greater adoption. Further, since these results were published, the U.S. manufacturing sector has undergone a massive transformation. Due to global competition, some sectors have relocated operations overseas. Others have brought operations onshore to avail low cost and abundant natural gas. Additionally, automation and robotics have pervaded the entire sector. Consequently, these two reports likely do not represent the current state of motor driven systems in U.S. industrial and commercial facilities. As cited in recent studies, the lack of current information on motor system electricity consumption and use characteristics limits the ability to conduct analysis on energy savings potential, develop technologies to address energy and productivity gaps, and develop programs to promote energy efficiency practices and technologies for motor systems (International Energy Agency, 2007; UNIDO, 2010; McKane and Hasanbeigi, 2011; Waide and Brunner, 2011). Specifically, the lack of information affects a range of stakeholders: Governments must rely on outdated information when setting research agendas, developing policies, and designing energy efficiency programs and offerings. Utilities and energy efficiency programs cannot identify the current market needs or potential impact when designing rebate and energy efficiency programs. Electric grid planners cannot identify motor system usage characteristics when developing plans to support the resilience of the electric grid. Manufacturers of motors, motor driven equipment, and drives are hampered when developing technologies to meet the needs of their market. Motor system end users are limited in their ability to identify energy saving opportunities within their own facilities because they do not have reliable benchmark information. In response to the lack of current information and analysis on industrial and commercial motor systems, the DOE initiated an update to these two studies. Launched in 2016 and led by Lawrence Berkeley National Laboratory (LBNL), the Motor System Market Assessment (MSMA) provides an updated, more comprehensive assessment of the installed stock of motor systems in both the industrial and commercial sectors, a review of the supply chains supporting motor and drives in the U.S., and the performance improvement opportunity available from using best available technologies and maintenance and operation practices. The outcomes of the MSMA are documented in three U.S. Industrial and Commercial Motor System Market Assessment reports, with this report being the first listed: 1. Volume 1: Characteristics of the Installed Base (this report) documents the findings on the installed base of motor systems in the U.S. industrial and commercial sectors. Quantification of energy savings potential is not documented in this report but in Volume 3. 2. Volume 2: Motors and Drives Supply Chain Review reviews the state of supply chains for motors and drives installed in U.S. industrial and commercial facilities, focusing on advanced motor and drive technologies and their constituent materials. 3. Volume 3: Energy Savings Opportunity analyzes the energy performance improvement opportunity for the installed base of U.S. industrial and commercial motor systems. This report has been prepared as a reference for motor system stakeholders. It provides factual information as could be best determined by the assessment results and avoids speculating on any findings.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Modular Autonomous Experimentation for Biological Applications (Full Report)

The Modular Autonomous Research System (MARS) was developed to address the pressing need for faster, more reliable, and more adaptable scientific discovery. Traditional experimentation is limited by manual labor, long cycle times, and fragmented data streams, which constrain the ability to explore complex chemical and materials design spaces. To overcome these limitations, we created an integrated, modular platform that combines laboratory robotics, diverse measurement instruments, and a central data infrastructure with artificial intelligence–driven decision-making. The system links liquid handling robots, robotic arms, and optical plate readers into a closed loop where experiments are executed automatically, data is analyzed in real time, and subsequent experimental conditions are adaptively chosen to maximize information gain. Over the course of the project, MARS was validated on two primary test cases—spectroscopic metal–ligand binding assays and peptide-directed mineralization—which highlighted the system’s ability to handle uncertainty and variability in experimental measurements. To further demonstrate modularity and extensibility, we also established additional testbeds in electrochemistry for catalyst discovery and electrolyte formulation for advanced batteries. The results show that MARS can reliably conduct autonomous campaigns with minimal human intervention, adapt to distinct scientific domains, and provide a scalable model for future self-driving laboratories. This work establishes new capabilities for modular, uncertainty-aware automation and directly supports the need for advanced, data-driven research platforms capable of accelerating discovery across a wide range of scientific and national security missions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Development of an Energy Efficient and Cost Effective Autonomous Vehicle Research Platform

Commercialization of autonomous vehicle technology is a major goal of the automotive industry, thus research in this space is rapidly expanding across the world. However, despite this high level of research activity, literature detailing a straightforward and cost-effective approach to the development of an AV research platform is sparse. To address this need, we present the methodology and results regarding the AV instrumentation and controls of a 2019 Kia Niro which was developed for a local AV pilot program. This platform includes a drive-by-wire actuation kit, Aptiv electronically scanning radar, stereo camera, MobilEye computer vision system, LiDAR, inertial measurement unit, two global positioning system receivers to provide heading information, and an in-vehicle computer for driving environment perception and path planning. Robotic Operating System software is used as the system middleware between the instruments and the autonomous application algorithms. After selection, installation, and integration of these components, our results show successful utilization of all sensors, drive-by-wire functionality, a total additional power* consumption of 242.8 Watts (*Typical), and an overall cost of $118,189 USD, which is a significant saving compared to other commercially available systems with similar functionality. This vehicle continues to serve as our primary AV research and development platform.

33 ADVANCED PROPULSION SYSTEMS↗