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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Process intensification education contributes to sustainable development goals. Part 1

In 2015 all the United Nations (UN) member states adopted 17 sustainable development goals (UN-SDG) as part of the 2030 Agenda, which is a 15-year plan to meet ambitious targets to eradicate poverty, protect the environment, and improve the quality of life around the world. Although the global community has progressed, the pace of implementation must accelerate to reach the UN-SDG time-line. For this to happen, professionals, institutions, companies, governments and the general public must become cognizant of the challenges that our world faces and the potential technological solutions at hand, including those provided by chemical engineering. Process intensification (PI) is a recent engineering approach with demonstrated potential to significantly improve process efficiency and safety while reducing cost. It offers opportunities for attaining the UN-SDG goals in a cost-effective and timely manner. However, the pedagogical tools to educate undergraduate, graduate students, and professionals active in the field of PI lack clarity and focus. This paper sets out the state-of-the-art, main discussion points and guidelines for enhanced PI teaching, deliberated by experts in PI with either an academic or industrial background, as well as representatives from government and specialists in pedagogy gathered at the Lorentz Center (Leiden, The Netherlands) in June 2019 with the aim of uniting the efforts on education in PI and produce guidelines. In this Part 1, we discuss the societal and industrial needs for an educational strategy in the framework of PI. The terminology and background information on PI, as it relates to educational implementation in industry and academia, are provided as a preamble to Part 2, which presents practical examples that will help educating on Process Intensification.

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

Metastable‐State Photoacids with Fast Reverse Reactions

Metastable-state photoacid (mPAH) has become a common tool for controlling and driving chemical processes with light. mPAHs with fast reverse reactions are desirable for precise temporal control or generating quick pulses of proton concentration. Here, in this work, different approaches towards fast reversing mPAHs are studied. Experimental and computational results showed that stabilizing the charge–transfer intermediate is an effective way to increase the rate. A novel mPAH with a reverse reaction ≈500 times faster than the most used mPAH in methanol is developed. Another water-soluble mPAH showed a reverse reaction with a rate constant of 7.8 s −1 , which is the fastest ever reported. The half-life of the acidic state is calculated to be 89 ms, which allowed to demonstrate sub-second switching using this mPAH.

Abbood, Rana [Florida Institute of Technology, Mel↗
DOE OSTI2023

What is microbial dormancy?

Life can be stressful. One way to deal with stress is to simply wait it out. Microbes do this by entering a state of reduced activity and increased resistance commonly called ‘dormancy’. But what is dormancy? Different scientific disciplines emphasize distinct traits and phenotypic ranges in defining dormancy for their microbial species and system-specific questions of interest. Here, we propose a unified definition of microbial dormancy, using a broad framework to place earlier discipline-specific definitions in a new context. We then discuss how this new definition and framework may improve our ability to investigate dormancy using multi-omics tools. Finally, we leverage our framework to discuss the diversity of genomic mechanisms for dormancy in an extreme environment that challenges easy definitions – the permafrost.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Informing selection of drugs for COVID-19 treatment through adverse events analysis

Coronavirus disease 2019 (COVID-19) is an ongoing pandemic and there is an urgent need for safe and effective drugs for COVID-19 treatment. Since developing a new drug is time consuming, many approved or investigational drugs have been repurposed for COVID-19 treatment in clinical trials. Therefore, selection of safe drugs for COVID-19 patients is vital for combating this pandemic. Our goal was to evaluate the safety concerns of drugs by analyzing adverse events reported in post-market surveillance. We collected 296 drugs that have been evaluated in clinical trials for COVID-19 and identified 28,597,464 associated adverse events at the system organ classes (SOCs) level in the FDA adverse events report systems (FAERS). We calculated Z-scores of SOCs that statistically quantify the relative frequency of adverse events of drugs in FAERS to quantitatively measure safety concerns for the drugs. Analyzing the Z-scores revealed that these drugs are associated with different significantly frequent adverse events. Our results suggest that this safety concern metric may serve as a tool to inform selection of drugs with favorable safety profiles for COVID-19 patients in clinical practices. Caution is advised when administering drugs with high Z-scores to patients who are vulnerable to associated adverse events.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Unraveling the Threads of Environmental Justice in Critical Mineral Extraction: A Framework for Regionalized Life Cycle Data

As we transition to a more sustainable energy system, the extraction and processing of critical minerals becomes increasingly important. However, these industries often raise concerns about environmental and social impacts, particularly in disadvantaged communities. To address these concerns, our research focuses on regionalizing environmental life cycle data to connect it with communities affected by mineral extraction. A framework was developed for collecting life cycle background data that supports the Justice40 Toolset, a market-based approach to evaluating net benefits and costs of critical mineral material recovery pathways. A goal was to alleviate public skepticism around mineral extraction processes, including secondary and unconventional feedstocks, by highlighting both environmental and social impacts. To achieve this, computational analysis and geospatial data science techniques were employed, such as within-scale and across-scale methods and proxy dataset usage. By doing so, we were able to develop a framework for identifying and disaggregating data down to regions small enough to support Justice40 goals. Our approach not only provides valuable tools fo insight into the environmental implications of mineral extraction but also helps policymakers evaluate the social impacts on local communities. This research contributes to a more just and equitable transition to a sustainable energy system, ensuring that marginalized voices are heard in decision-making process.

Davis, Tyler [NETL Site Support Contractor, Nation↗
DOE OSTI2025

Comparing four heat-inducible promoters in stably transformed sugarcane regarding spatial and temporal control of transgene expression reveals candidates to drive stem-preferred transgene expression

Small heat shock protein (sHSP) promoters contain cis-regulatory elements that facilitate transcription in response to heat stress, making them valuable tools for functional studies through controlled gene expression and the precise regulation of gene-editing tools or morphogenic regulators. To evaluate their utility, GUS reporter gene expression driven by four plant-sourced HSP promoters (p GmHSP17.5 , p HvHSP17 , p ZmHSP17.7 , and p ZmHSP26 ) was compared across various tissues of stably transformed sugarcane before and after heat treatment. At 22°C, all promoters showed minimal activity in leaves and roots, although p ZmHSP17.7 and p HvHSP17 displayed moderate expression in stems. Following heat treatment, all promoters exhibited their highest activity in stems, followed by leaves and roots. In stem tissues, p GmHSP17.5 displayed heat-induced uidA expression comparable to the constitutive p ZmUbi promoter. Notably, heat-induced reporter gene activity in stem middle sections of single-copy transgenic lines containing p ZmHSP17.7 , p HvHSP17 , or p ZmHSP26 exceeded p ZmUbi -derived uidA activity by 9.7-fold, 3.8-fold, and 3.0-fold, respectively, with 346- to 3,672-fold induction compared to control conditions. Most promoters showed peak expression in the middle sections of the stem, while p HvHSP17 was the most active in the stem apices. Histochemical analysis revealed that p ZmHSP17.7 and p HvHSP17 were active in both parenchyma cells and vascular bundles within sugarcane stems. Among leaf tissues, mature leaves exhibited greater expression than senescing or immature leaves, while root activity remained consistently minimal across all promoters. Temperature-course experiments identified distinct activation thresholds: 34°C–36°C for p ZmHSP17.7 , 36°C for p ZmHSP26 , 36°C–38°C for p HvHSP17 , and 40°C–42°C for p GmHSP17.5 . Drought stress also induced reporter gene transcription in stems under HSP promoters, although with lower fold induction than heat treatment. These findings provide valuable tools for gene function studies and biotechnology applications, including heat stress tolerance research, controlled transgene expression in metabolic engineering, precision gene editing, and developmental biology studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

CPGminer: An Interactive Dashboard to Explore the Genomic Features and Taxonomy of Complete Prokaryotic Genomes

Prokaryotes, the earliest forms of life on Earth, play crucial roles in global biogeochemical processes in virtually all ecosystems. The ever-increasing amount of prokaryotic genome sequencing data provides a wealth of information to examine fundamental and applied questions through systematic genome comparison. Genomic features, such as genome size and GC content, and taxonomy-centric genomic features of complete prokaryotic genomes (CPGs) are crucial for various fields of microbial research and education, yet they are often overlooked. Additionally, creating systematically curated datasets that align with research concerns is an essential yet challenging task for wet-lab researchers. In this study, we introduce CPGminer, a user-friendly tool that allows researchers to quickly and easily examine the genomic features and taxonomy of CPGs and curate genome datasets. We also provide several examples to demonstrate its practical utility in addressing descriptive questions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Improved detection of low-frequency within-host variants from deep sequencing: A case study with human papillomavirus

Abstract High-coverage sequencing allows the study of variants occurring at low frequencies within samples, but is susceptible to false-positives caused by sequencing error. Ion Torrent has a very low single nucleotide variant (SNV) error rate and has been employed for the majority of human papillomavirus (HPV) whole genome sequences. However, benchmarking of intrahost SNVs (iSNVs) has been challenging, partly due to limitations imposed by the HPV life cycle. We address this problem by deep sequencing three replicates for each of 31 samples of HPV type 18 (HPV18). Errors, defined as iSNVs observed in only one of three replicates, are dominated by C→T (G→A) changes, independently of trinucleotide context. True iSNVs, defined as those observed in all three replicates, instead show a more diverse SNV type distribution, with particularly elevated C→T rates in CCG context (CCG→CTG; CGG→CAG) and C→A rates in ACG context (ACG→AAG; CGT→CTT). Characterization of true iSNVs allowed us to develop two methods for detecting true variants: (1) VCFgenie, a dynamic binomial filtering tool which uses each variant’s allele count and coverage instead of fixed frequency cut-offs; and (2) a machine learning binary classifier which trains eXtreme Gradient Boosting models on variant features such as quality and trinucleotide context. Each approach outperforms fixed-cut-off filtering of iSNVs, and performance is enhanced when both are used together. Our results provide improved methods for identifying true iSNVs in within-host applications across sequencing platforms, specifically using HPV18 as a case study.

Virology↗
DOE OSTI2020

MEP: Mobility Energy Productivity Metric

In response to the need to assess fundamental improvements in mobility as technology provides new modes, methods, and opportunities in urban areas to connect people with goods, services, and employment, a mobility-energy productivity score (MEPS) has been developed. The MEPS fundamentally measures the potential of a multi-modal system to connect a person to a variety of services and activities that define a high-quality of life. The MEPS is measured relative to the convenience and energy needed to provide connectivity. Fundamentally derived from accessibility theory, the MEPS advances practice by using readily available travel time data (either from web-based APIs or outputs from an urban transportation model) combined with established parameters that reflect the energy intensity of various travel modes, and relative frequency of activity engagement. The construction of the MEPS allows for aggregation and disaggregation to the appropriate spatial, modal, and trip purpose resolution, as analysis needs dictate. The MEPS could be used to compare alternative futures related to technology, infrastructure investment, or policy, providing a much needed tool for planners, researchers, and analysts. In other words, the metric measures how efficiently connected a place is.

Hou, Yi↗
DOE OSTI2022

Atomic Force Microscope Active Optical Probe for Single-Molecule Imaging and Time-Resolved Optical Spectroscopy (DOE SBIR Phase II/IIA Final Report)

Actoprobe LLC reports on the results of its DOE SBIR Phase II/IIA project on the development of Atomic Force Microscope Active Optical Probe for Single-Molecule Imaging and Time-Resolved Optical Spectroscopy. While chemistry science and technology greatly benefit from Atomic Force Microscopy in surface characterization, time-resolved chemical imaging on the single-molecule level lags far behind. Current scanning probe microscopy only obtains information about mechanical but not optical/chemical properties. To address this problem, the Actoprobe LLC research team has proposed a novel class of Atomic Force Microscopy probes, Ultra-Fast Pulsed Active Atomic Force Microscopy Optical Probes (UFP AAOPs), that will allow ultrafast time-resolved optical and chemical imaging at the nanoscale. As envisioned, these unique optical probes will perform the functions of conventional Atomic Force Microscopy probes and, in addition, will simultaneously provide chemical information about molecular scale interactions. This innovation is accomplished by integrating an ultrafast pulsed Quantum Dot laser source into an Atomic Force Microscopy probe. This report describes our progress with the fabrication of an ultrafast micrometer-size semiconductor laser, based on “artificial atoms” - Quantum Dots, integrated with an Atomic Force Microscopy probe. In this Phase II/IIA project, we have demonstrated the feasibility of the UFP AAOP concept by fabricating a first prototype of the UFP AAOP. The excellent performance of the probe has been proven in terms of AFM and optical spatial resolution through rigorous tests. The UFP AAOP provides pulses with less than 4 ps duration and higher than 11 GHz repetition rate, and spatial resolution better than 300 nm at 1240 nm wavelength. Technically, it is possible to reduce the pulse width to less than 1 ps and to improve lateral resolution to ~ 0.5 nm, which implies the potential capability for the probe to characterize chemical compounds with single-molecule resolution. The UFP AAOP fabrication procedure has been developed for wafer-scale production of multiple devices, with the yield of the process estimated to be lower than 1% with the limited fabrication capabilities and equipment available for use in the research project. However, using high-volume production tools and special GaAs processing equipment, the yield can be significantly improved, theoretically to ~ 50%. Finally, economic feasibility and scale-up manufacturing potential were analyzed for UFP AAOP and found to be very promising. In summary, the Actoprobe team has successfully demonstrated the feasibility of the UFP AAOP concept.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Advanced Algal Biofoundries for the Production of Polyurethane Precursors

The primary goal of the BEEPs project was to develop a process that could accelerate the development of algae as bioproduction platforms, from initial chemical product concept to an economically viable market supply. Under this program we elected to develop strains of algae that could generate polyurethane precursors, while simultaneously developing basic genetic tools to enable improved algal production systems. This program was specifically designed to incorporate National Laboratories as a means to utilize the expertise and facilities for new bio-production platforms. To that end, we designed a program to collaborate with the Agile BioFoundry at Lawrence Berkeley National Laboratory (LBNL) and computational platforms at Pacific Northwest National Laboratory (PNNL). In addition to these National Laboratory partners, we also had academic partners from UC Davis and Georgia Tech, as well as commercial partners Algenesis Materials and BASF. To achieve these goals, we initially focused on developing the genetic tools and high throughput screening technologies necessary to generate and assess production of polymer precursors (succinic acid) in algae and cyanobacteria, including advanced promoters and biosensors. In parallel, we computationally identified potential production bottlenecks and then used the developed genetic tools to increase production rates and yields. Constant feedback of data was used in conjunction with machine learning, high-throughput cell sorting, and synthetic biology, for additional targeted metabolic engineering. Multiple rounds of tool design, building, testing, and learning were supplied to partners at PNNL and LBNL to develop new models and tools that could expedite bioproduction platform development and increase yield performance. We targeted, and achieved, the FOA requirement yield metric of 20 g/L, as a milestone and deliverable from at least one of our engineered strains for the production of succinic acid.

09 BIOMASS FUELS↗
DOE OSTI2025

Recent Progress in Solid‐State Lithium Batteries through Cathode Microstructure Engineering

A high‐performance cathode is necessary to realize the great potentials of solid‐state batteries such as high energy density and long cycle life. It is also needed to validate electrolyte performance, which is lacking. Currently, cathodes for solid‐state batteries are thinner and have lower cathode active material content than their lithium‐ion battery counterpart, resulting from insufficient conductivity and limiting the battery energy density. This review article provides an overview of recent development in cathode microstructures and their impact on battery properties, including compatibility between cathode and electrolyte, cathode architecture design, interface engineering, correlation between material properties, cathode processing approaches, and performance, as well as the advanced characterization methods used to understand the above correlations . Some perspectives on future development are shared including utilizing in situ and operando characterization tools to better understand dynamic evolution of the cathode/electrolyte interface, adapting artificial intelligence and machine learning to design and optimize cathode structures. The article is aimed to promote research interest on cathode development and advance solid‐state battery technologies.

cathode engineering↗
DOE OSTI2024

OPEN-Augmented Reality GUI for Bioenergy Crop Phenotyping and Precision Agriculture (Donald Danforth Plant Science Center Final Scientific Technical Report)

The project led by the Donald Danforth Plant Science Center, in collaboration with Arizona State University, George Washington University, and Saint Louis University, has made significant strides in advancing the phenotypic analysis of bioenergy crops through the development of an innovative AI processing pipeline. This initiative was primarily funded by ARPA-E, with additional cost-sharing provided by the participating institutions. The project successfully utilized a variety of sensors—3D scanners, thermal, RGB, and hyperspectral—to refine algorithms for data-driven trait signature identification and improve the classification and visualization of plant traits. The developed AI processing pipeline is capable of handling the complex, multidimensional data characteristic of dynamic agricultural environments. 1) Contributions to understanding: The research has advanced the field of plant phenomics by showcasing the synergistic use of various sensor data to enhance the precision of trait analysis in bioenergy crops. Through the integration of 3D scanners, thermal, RGB, and hyperspectral sensors, the project has developed robust data-driven trait signature algorithms and visualization techniques. These innovations have facilitated detailed monitoring and management of plant traits, providing vital insights into plant growth dynamics and stress responses. Further, the project has broadened our understanding of how machine learning can be effectively applied in multi-sensor environments to refine trait analysis. By leveraging diverse datasets, the research has not only improved the accuracy of phenotypic assessments but also established a versatile methodological framework that can be extended beyond agriculture to other fields requiring detailed phenotypic analysis. 2) Technical effectiveness and economic feasibility: The AI processing pipeline developed in this project demonstrated significant technical effectiveness, achieving high throughput analysis of extensive phenotypic data and meeting targeted accuracies. This system exemplified the capability of advanced machine learning technologies to efficiently manage and analyze large, complex datasets. Economically, the implementation of the project-developed pipelines may offer substantial cost savings across multiple sectors. It enhances data analysis processes and significantly reduces the need for manual data interpretation, thereby decreasing both the time and resources required. 3) Public benefit: The project has significantly broadened the scope of agricultural methodologies to enhance phenotypic analysis, with potential applications in various sectors beyond agriculture. Additionally, the initiative fostered an enriching educational and collaborative environment, significantly enhancing the technical skills of participants. It also made substantial contributions to the scientific community by providing open-access data sets and tools, encouraging ongoing research and development across various disciplines. Overall, the project not only met its scientific goals but also showcased the extensive utility of integrating advanced machine learning and sensor data analysis technologies. These advancements have proven instrumental in driving forward both theoretical research and practical applications, setting a strong foundation for future explorations and innovations in data-driven science.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Grid Resilience Analysis on Geothermal District Heating and Cooling Implementation Alongside Four Existing Oil and Gas Wells in Tuttle, Oklahoma: Preprint

This study builds on the existing techno-economic and environmental life cycle assessments performed for a geothermal district heating and cooling system implementation in Tuttle Oklahoma with four existing oil and gas wells. Its resilience in meeting the peak annual heating and cooling loads of the district assuming a temporary disconnection from the electrical grid is assessed both qualitatively and quantitatively. Attributes of resilience and qualitative criteria established by Kolker et al. (2022) for geothermal district heating systems are applied to the proposed case to highlight its vulnerabilities. Results indicate that increasing the redundancy and diversity in the physical configuration of the distributional piping can considerably increase the system’s resilience. A quantitative assessment executed via the REopt tool predicts that the ancillary electricity required to power the geothermal system’s heating and cooling can be met by an onsite emergency diesel generator during times of grid outages for over 28 days.

district heating and cooling↗
DOE OSTI2025

Grid Resilience Analysis on Geothermal District Heating and Cooling Implementation Alongside Four Existing Oil and Gas Wells in Tuttle, Oklahoma

This study builds on the existing techno economic and environmental life cycle assessments performed for a geothermal district heating and cooling system implementation in Tuttle Oklahoma with four existing oil and gas wells. Its resilience in meeting the peak annual heating and cooling loads of the district assuming a temporary disconnection from the electrical grid is assessed both qualitatively and quantitatively. Attributes of resilience and qualitative criteria established by Kolker et al. (2022) for geothermal district heating systems are applied to the proposed case to highlight its vulnerabilities. Results indicate that increasing the redundancy and diversity in the physical configuration of the distributional piping can considerably increase the system's resilience. A quantitative assessment executed via the REopt tool predicts that the ancillary electricity required to power the geothermal system's heating and cooling can be met by an onsite emergency diesel generator during times of grid outages for over 28 days.

district heating and cooling↗
DOE OSTI2024

Dual Enhancement of Thermostability and Activity of Xylanase through Computer-Aided Rational Design

In the realm of enzyme engineering, the dual enhancement of thermostability and activity remains a challenge. Herein, we employed a computer-aided approach integrating folding free energy calculations and evolutionary analysis to engineer Paecilomyces thermophila xylanase into a hyperthermophilic enzyme for application in the paper and pulp industry. Through the computational rational design, XynM9 with superior thermostability and enhanced activity was designed. Its optimal reaction temperature increases by 10 °C to 85 °C, its T m increases by 10 °C to 93 °C, and its half-life increases 11-fold to 5.8 h. Additionally, its catalytic efficiency improves by 57% to 3926 s –1 mM –1 . Molecular dynamics simulations revealed that XynM9 is stabilized by more hydrogen bonds and salt bridges than wild-type xylanase. The mutant’s narrower catalytic cleft enhances the substrate-binding affinity, thus improving the catalytic efficiency. In harsh conditions at 80 °C and pH 10, using XynM9 significantly reduced both hemicellulose and lignin, which makes it a good candidate for use in the paper and pulp process. Finally, our study presents an accurate and efficient strategy for the dual enhancement of enzyme properties, guiding further improvement of computational tools for protein stabilization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Direct Recycling of Lithium-Ion Battery Cathodes: A Multi-Stage Annealing Process to Recover the Pristine Structure and Performance

Direct recycling is an alternative low-cost process that retains the structure of the lithium-ion battery cathode rather than going through materials dissolution and repurification. While the process shows promise, various steps need to be better understood and studied to identify possible roadblocks, cost intensive steps, and needed variations in protocol that may be necessary based on the feedstock of recycled cathodes available. In this study, we have evaluated the process of thermal relithiation as it applies to end-of-life cathode materials. For recovered end-of-life cathodes, approximately 20% of the useable lithium has been lost due to solid electrolyte interface formation, parasitic reactions, and particle isolation; this lost lithium contributes to higher cell impedance and a gradual shift in electrode potentials. As a first step in the direct recycling process, this lithium needs to be restored not only to recover capacity but also to eliminate surface vacancies and hinder surface reconstruction that may increase impedance and impact performance. Here, we have optimized a coating method followed by a two-stage annealing process that restores a model delithiated NMC333 material to pristine performance. Comparisons to single-stage processes are made, and new characterization tools have been used to better understand the processes.

25 ENERGY STORAGE↗
DOE OSTI2020

A Novel and Practical Method to Quantify the Quality of Mobility: The Mobility Energy Productivity Metric: Preprint

Recent technology innovations are enabling fundamental improvements in mobility systems, including options for new travel modes, methods, and opportunities to connect people with goods, services, and employment. A desire to quantify and compare both existing and emerging transportation options motivated development of the mobility energy productivity (MEP) metric described herein. The MEP metric fundamentally measures the potential of a city's transportation system to connect a person to a variety of services and activities that define a high-quality of life, relative to the convenience, cost and energy needed to provide these connections. Fundamentally derived from accessibility theory, the MEP advances practice by using readily available travel time data (either from web-based application programming interfaces (APIs) or outputs from an urban transportation model) combined with established parameters that reflect the energy intensity and cost of various travel modes, and relative frequency of activity engagement. The construction of the MEP metric allows for aggregation and disaggregation to the appropriate spatial, modal, and trip purpose resolution, as analysis needs dictate. The MEP could be used to compare alternative futures related to technology, infrastructure investment, or policy, providing a much-needed tool for planners, researchers, and analysts.

33 ADVANCED PROPULSION SYSTEMS↗