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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 OSTI2022

Delineating the Roles of Mn, Al, and Co by Comparing Three Layered Oxide Cathodes with the Same Nickel Content of 70% for Lithium-Ion Batteries

High-nickel layered oxides continue to prevail in the energy storage market as the frontmost cathode candidates for next-generation lithium-ion batteries. Demand and development of LiNi 1–x–y Mn x Co y O 2 (NMC) and LiNi 1–x–y Co x Al y O 2 (NCA) cathodes are rampantly increasing, particularly for the electric vehicle (EV) industry. However, the continued presence of cobalt in NMC and NCA cathodes raises global concerns due to geopolitical and ethical issues attributed to Co sourcing. We herein introduce a novel cobalt-free, high-nickel cathode LiNi 0.7 Mn 0.25 Al 0.05 O 2 (NMA70) and benchmark it against Co-containing LiNi 0.7 Mn 0.15 Co 0.15 O 2 (NMC70) as well as Co- and Al-free LiNi 0.7 Mn 0.3 O 2 (NM70) cathodes with equivalent 70% Ni contents that are all synthesized in-house. NMA70 displays a high initial C/10 capacity of 210 mA h g –1 , matching that of NMC70 in half cells with a cutoff voltage of 4.5 V. NMA70 also exhibits an impressive high-voltage full cell cycling performance with a cutoff voltage of 4.4 V with a nearly identical capacity retention of 83% compared to that of 82% for NMC70 after 300 cycles. Postmortem X-ray photoelectron spectroscopy (XPS), high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), and electron energy loss spectroscopy (EELS) analyses indicate a thinner cathode–electrolyte interface (CEI) developed in NMA70 compared to that in NM70 and unveil a more robust solid-electrolyte interface (SEI) passivation on the graphite anode among all samples. The benefits of Al doping are additionally highlighted with enhanced high-voltage CEI and thermal stabilities in NMA70. Furthermore, this work assesses the roles of Mn, Al, and Co to demonstrate both the practicality and feasibility of synthesizing cobalt-free, high-nickel cathodes that are promising alternatives to current NMC- and NCA-based cathodes.

25 ENERGY STORAGE↗
DOE OSTI2022

A GeoHealth Call to Action: Moving Beyond Identifying Environmental Injustices to Co-Creating Solutions

As marginalized communities continue to bear disproportionate impacts from environmental hazards, we urgently call for researchers and institutions to elevate the principles of Environmental Justice. The American Geophysical Union (AGU) GeoHealth section supports members' engagement in health-related community-engaged and community-led transdisciplinary research. We highlight intersectional research that provides examples and actions for both individuals and organizations on community science and trust building, removing barriers created by scientific agency priorities and career expectations, and opportunities in education and policy. Justice does not start or end at one meeting; this is ongoing work that is active, evolving, and an ethical responsibility of AGU's membership.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Update on Our Action Plan for Equity, Inclusion, and Diversity in Publishing at JGR: Biogeosciences

We made a commitment to better include underrepresented members of our community in the publication pipeline of JGR: Biogeosciences. This commitment consists of regular updates on our policies and practices, and concrete actions we intend to implement over the next year. So far, our progress to tackle biases and ensure equitable research in the biogeosciences has focused on improving diversity of our associate editor and reviewer pools, increasing awareness of unconscious bias in peer-review, and promoting inclusion in global collaborations. In this update, we explore manuscript submissions and manuscript decisions by gender, and we present a pilot that aims to promote ethical and equitable global collaborations in resource-poor settings. Here, we end our editorial by presenting our next set of actions that we plan on completing over the next year, which include a more thorough analysis of reviewer demographics.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

AGU Publications Updates Authorship Policy to Foster Greater Equity and Transparency in Global Research Collaborations

AGU Publications encourages research collaborations between regions, countries, and communities. When well-resourced researchers complete research or field work in low-resourced settings while excluding local communities or researchers from the process, this can be referred to as parachute science or helicopter research. To help address concerns of parachute science and to promote greater equity and transparency in global research collaborations, AGU Publications has updated its authorship policy across its scholarly journals. The implementation of this policy follows a successful 18-month pilot at JGR: Biogeosciences. For research completed in low-resourced regions, authors are encouraged to include a disclosure statement pertaining to the ethical and scientific considerations of their research collaborations.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Comparative Analysis of Report-Back of Research Results Strategies for Personal Chemical Exposure Data

Background. Report-back of research results (RBRR) is ethically supported and highly requested by participants yet lacks broadly transferable guidelines for RBRR. Effective RBRR must be responsive to target audience needs and may not be addressed by a ‘one-size-fits-all’ approach. Objective. Within a subset of our 19 studies on RBRR, we had the unique opportunity to carry out a comparative analysis of RBRR strategies across cohorts with similar development and evaluation methods, yet distinct in life stage, geography, number and type of chemicals assessed, and community contexts. Methods. We highlight key outcomes from three environmental health studies: an ongoing New York, NY cohort (Fair Start; n=486) and a Detroit, MI cohort (CLEAR; n=34) assessing exposure to ambient urban pollution during pregnancy, and a longitudinal cohort in Houston, TX (Houston-3H) following Hurricane Harvey (n=312). Focus group and survey data were analyzed to identify lessons learned and explore how RBRR supports understanding of environmental health. Results. Commonalities emerged in RBRR development, design, organization, and data visualization, as well as in how RBRR can contribute to an understanding of health-environment connections. Differences included preferences for individual versus community level findings, as well as distinguishable contextual considerations. For pregnancy cohorts, messaging was framed with cultural sensitivity, and to avoid unintended consequences of parental guilt due to prenatal exposures. In the post-disaster Houston-3H study, participants requested additional transparency regarding sampling design and study rationale. Significance. All RBRR case studies reported chemicals without known regulatory or health guidelines, so results were contextualized within the study population. Participants across cohorts requested multi-study comparisons to better understand their results beyond their communities. While foundational RBRR elements (e.g. plain language, graphic organizers) may supersede cohort-specific differences, RBRR should be personalized to encompass perceptions of health across different life-stage, cultural, and environmental contexts.

Vogel, Taylor J.↗
DOE OSTI2024

Review of low-cost self-driving laboratories in chemistry and materials science: the “frugal twin” concept

This review proposes the concept of a “frugal twin,” similar to a digital twin, but for physical experiments. Frugal twins range from simple toy examples to low-cost surrogates of high-cost research systems. For example, a color-mixing self-driving laboratory (SDL) can serve as a low-cost version of a costly multi-step chemical discovery SDL. Frugal twins already provide hands-on experience for SDLs with low costs and low risks. They can also offer as test beds for software prototyping (e.g., optimization, data infrastructure), and a low barrier to entry for democratizing SDLs. However, there is room for improvement. The true value of frugal twins can be realized in three core areas. Firstly, hardware and software modularity; secondly, purpose-built design (human-inspired vs. hardware-centric vs. human-in-the-loop); and thirdly state-of-the-art (SOTA) software (e.g., multi-fidelity optimization). We also describe the ethical benefits and risks that come with the democratization of science through frugal twins. For future work, we suggest ideas for new frugal twins, SDL educational course outcomes, and a classification scheme for autonomy levels.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Are humans still necessary? Expanding the discussion

The rise of automation, artificial intelligence (AI), and autonomous systems raises important questions about the future role of humans and the field of human factors/ergonomics in workplaces. This paper builds on Dr. Peter Hancock’s 2023 ‘Are Humans Still Necessary?’ article published in the Ergonomics journal. Using a multi-method approach that included a debate, opinion polling, roundtable discussions, and AI queries, the current effort examined the necessity of human involvement in future work environments. Debate team members presented arguments for and against the need for human workers, considering human factors, technology, and socioeconomic factors. Observations indicate that while AI may handle routine tasks, humans will likely remain essential for complex decision making, creativity, and ethical considerations. The paper advocates for viewing workplace dynamics as collaborative human-AI partnerships rather than competition, highlighting the need for a transdisciplinary approach in which human factors/ergonomics professionals play a vital role in enhancing these relationships.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Evaluating the carbon capture potential of industrial waste as a feedstock for enhanced weathering

Abstract Limiting anthropogenic global climate warming since the start of the industrial period to less than 2 °C will very likely require both deep and rapid reductions in anthropogenic greenhouse gas emissions and a range of approaches toward carbon dioxide removal (CDR). One prominent CDR approach is enhanced weathering (EW), in which crushed silicate rock is applied on land or in the open ocean to accelerate natural weathering processes that absorb carbon dioxide from Earth’s ocean–atmosphere system. However, in addition to a range of potential environmental, socioeconomic, and ethical issues associated with this pathway, bottlenecks in feedstock sourcing represent a key barrier for deployment of EW at scale. Here, we evaluate the potential of silicate wastes produced from industrial processes—such as steel slag and cement waste—as feedstocks for the EW process. An empirical model that links industrial alkaline waste production to gross domestic product at purchase power parity is developed to forecast waste production in the alternative futures described by the shared socioeconomic pathway (SSP) framework. By incorporating these results into an intermediate-complexity Earth system model, we also explore the impacts of EW using industrial waste on changes to global temperature, ocean pH, and ocean aragonite saturation state, while also quantifying overall CDR efficiency through the end of the century. We estimate a maximum cumulative end-of-century capture potential of ∼400 GtCO 2 for industrial waste, which could represent a significant fraction of the projected CDR requirement of many mitigation scenarios in the SSP framework. However, feedstock-dependent environmental impacts and the technoeconomics of feedstock redistribution may ultimately limit deployment scope.

Xu, Pengxiao (ORCID:0009000633724293)↗
DOE OSTI2023

2023 roadmap for potassium-ion batteries

Abstract The heavy reliance of lithium-ion batteries (LIBs) has caused rising concerns on the sustainability of lithium and transition metal and the ethic issue around mining practice. Developing alternative energy storage technologies beyond lithium has become a prominent slice of global energy research portfolio. The alternative technologies play a vital role in shaping the future landscape of energy storage, from electrified mobility to the efficient utilization of renewable energies and further to large-scale stationary energy storage. Potassium-ion batteries (PIBs) are a promising alternative given its chemical and economic benefits, making a strong competitor to LIBs and sodium-ion batteries for different applications. However, many are unknown regarding potassium storage processes in materials and how it differs from lithium and sodium and understanding of solid–liquid interfacial chemistry is massively insufficient in PIBs. Therefore, there remain outstanding issues to advance the commercial prospects of the PIB technology. This Roadmap highlights the up-to-date scientific and technological advances and the insights into solving challenging issues to accelerate the development of PIBs. We hope this Roadmap aids the wider PIB research community and provides a cross-referencing to other beyond lithium energy storage technologies in the fast-pacing research landscape.

Xu, Yang (ORCID:0000000301776348)↗
DOE OSTI2022

The Promise of Emergent Nanobiotechnologies for In Vivo Applications and Implications for Safety and Security

Nanotechnology, the multi-disciplinary field based on the exploitation of the unique physicochemical properties of nanoparticles (NPs) and nanoscale materials, has opened a new realm of possibilities for biological research and biomedical applications. The development and deployment of mRNA-NP vaccines for COVID-19, for example, may revolutionize vaccines and therapeutics. However, regulatory and ethical frameworks that protect the health and safety of the global community and environment are lagging, particularly for nanotechnology geared towards biological applications (i.e., bio-nanotechnology). Considering this, the following review, while not comprehensive, attempts to illustrate the breadth and promise of bionanotechnology developments, and how they may present future safety and security challenges. Specifically, we address current advancements to streamline the development of engineered NPs for in vivo applications and provide discussion on nano-bio interactions, NP in vivo delivery, nano-enhancement of human performance, nanomedicine, and the impacts of NPs on human health and the environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Optimization of Application-Driven Development of In Vitro Neuromuscular Junction Models

Neuromuscular junctions (NMJs) are specialized synapses responsible for signal transduction between motor neurons (MNs) and skeletal muscle tissue. Malfunction at this site can result from developmental disorders, toxic environmental exposures, and neurodegenerative diseases leading to severe neurological dysfunction. Exploring these conditions in human or animal subjects is restricted by ethical concerns and confounding environmental factors. Therefore, in vitro NMJ models provide exciting opportunities for advancements in tissue engineering. In the last two decades, multiple NMJ prototypes and platforms have been reported, and each model system design is strongly tied to a specific application: exploring developmental physiology, disease modeling, or high-throughput screening. Directing the differentiation of stem cells into mature MNs and/or skeletal muscle for NMJ modeling has provided critical cues to recapitulate early-stage development. Patient-derived inducible pluripotent stem cells provide a personalized approach to investigating NMJ disease, especially when disease etiology cannot be resolved down to a specific gene mutation. Having reproducible NMJ culture replicates is useful for high-throughput screening to evaluate drug toxicity and determine the impact of environmental threat exposures. Cutting-edge bioengineering techniques have propelled this field forward with innovative microfabrication and design approaches allowing both two-dimensional and three-dimensional NMJ culture models. Many of these NMJ systems require further validation for broader application by regulatory agencies, pharmaceutical companies, and the general research community. In this summary, we present a comprehensive review on the current state-of-art research in NMJ models and discuss their ability to provide valuable insight into cell and tissue interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Evaluation of data collection bias of third molar stages of mineralisation for age estimation in the living

Abstract Age assessment of the living is a fundamental procedure in the process of human identification, in order to guarantee fair treatment of individuals, which has ethical, civil, legal, and medical repercussions. The careful selection of the appropriate methods requires evaluation of several parameters: accuracy, precision of the method, as well as its reproducibility. The approach proposed by Mincer et al. adapted from Demirjian et al. exploring third molar mineralisation, is one of the most frequently considered for age estimation of the living. Thus, this work aims to assess potential bias in the data collection when applying the classification stages for dental mineralisation adapted by Mincer et al. A total of 102 orthopantomographs, of clinical origin, belonging to individuals aged between 12 and 25 years ($ \bar{\textit x} $ = 20.12 years, SD = 3.49 years; 65 females, 37 males, all of Portuguese nationality) were included and a retrospective analysis performed by five observers with different levels of experience (high, average, and basic). The performance and agreement between five observers were evaluated using Weighted Cohen’s Kappa and the Intraclass Correlation Coefficient. To access the influence of impaction on third molar classification, variables were tested using ordinal logistic regression Generalised Linear Model. It was observed that there were variations in the number of teeth identified among the observers, but the agreement levels ranged from moderate to substantial (0.4–0.8). Upon closer examination of the results, it was observed that although there were discernible differences between highly experienced observers and those with less experience, the gap was not as significant as initially hypothesised, and a greater disparity between the classifications of the upper (0.24–0.49) and lower third molars (>0.55) was observed. When bone superimposition is present, the classification process is not significantly influenced; however, variation in teeth angulation affects the assessment. The results suggest that with an efficient preparation, the level of experience as a factor can be overcome. Mincer and colleague's classification system can be replicated with ease and consistency, even though the classification of upper and lower third molars presents distinct challenges.

de Oliveira Santos, Inês (ORCID:0000000267324347)↗
DOE OSTI2022

Research Software Engineering at Oak Ridge National Laboratory

Research software engineers (RSE) play a vital role in scientific discoveries worldwide. They lead the core development of the applications, libraries, and tools that enable today’s supercomputers to process the vast volumes of data generated from the world’s most extensive and complicated scientific instruments and facilities. This article describes the mission, culture, and practices of RSE teams at Oak Ridge National Laboratory (ORNL), including their team dynamics and composition, work ethics, standard practices, and ever-evolving skill sets vital to pursuing scientific innovations and implementing novel ideas. We describe the lessons learned from specific activities that contribute to shaping the identity and growth of RSE roles at ORNL. Lastly, we provide our view for the near future on effective strategies for establishing, leading, and nurturing RSE teams and building a thriving community in collaboration with science stakeholders.

42 ENGINEERING↗
DOE OSTI2025

Sparse measurement medical CT reconstruction using multi-fused block matching denoising priors

A major challenge for medical X-ray CT imaging is reducing the number of X-ray projections to lower radiation dosage and reduce scan times without compromising image quality. However these under-determined inverse imaging problems rely on the formulation of an expressive prior model to constrain the solution space while remaining computationally tractable. Traditional analytical reconstruction methods like Filtered Back Projection (FBP) often fail with sparse measurements, producing artifacts due to their reliance on the Shannon-Nyquist Sampling Theorem. Consensus Equilibrium, which is a generalization of Plug and Play, is a recent advancement in Model-Based Iterative Reconstruction (MBIR), has facilitated the use of multiple denoisers are prior models in an optimization free framework to capture complex, non-linear prior information. However, 3D prior modelling in a Plug and Play approach for volumetric image reconstruction requires long processing time due to high computing requirement. Instead of directly using a 3D prior, this work proposes a BM3D Multi Slice Fusion (BM3D-MSF) prior that uses multiple 2D image denoisers fused to act as a fully 3D prior model in Plug and Play reconstruction approach. Our approach does not require training and are thus able to circumvent ethical issues related with patient training data and are readily deployable in varying noise and measurement sparsity levels. In addition, reconstruction with the BM3D-MSF prior achieves similar reconstruction image quality as fully 3D image priors, but with significantly reduced computational complexity. We test our method on clinical CT data and demonstrate that our approach improves reconstructed image quality.

Hossain, Maliha [ORNL]↗
DOE OSTI2023

Review of machine learning and deep learning models for toxicity prediction

The ever-increasing number of chemicals has raised public concerns due to their adverse effects on human health and the environment. To protect public health and the environment, it is critical to assess the toxicity of these chemicals. Traditional in vitro and in vivo toxicity assays are complicated, costly, and time-consuming and may face ethical issues. These constraints raise the need for alternative methods for assessing the toxicity of chemicals. Recently, due to the advancement of machine learning algorithms and the increase in computational power, many toxicity prediction models have been developed using various machine learning and deep learning algorithms such as support vector machine, random forest, k-nearest neighbors, ensemble learning, and deep neural network. This review summarizes the machine learning- and deep learning-based toxicity prediction models developed in recent years. Support vector machine and random forest are the most popular machine learning algorithms, and hepatotoxicity, cardiotoxicity, and carcinogenicity are the frequently modeled toxicity endpoints in predictive toxicology. It is known that datasets impact model performance. The quality of datasets used in the development of toxicity prediction models using machine learning and deep learning is vital to the performance of the developed models. The different toxicity assignments for the same chemicals among different datasets of the same type of toxicity have been observed, indicating benchmarking datasets is needed for developing reliable toxicity prediction models using machine learning and deep learning algorithms. This review provides insights into current machine learning models in predictive toxicology, which are expected to promote the development and application of toxicity prediction models in the future.

Research & Experimental Medicine↗
DOE OSTI2024

Comminty Geothermal: Planning and Design of a Heating and Cooling System in Framingham, Massachusetts

These reports, plans, and drawings review the achievements of Home Energy Efficiency Team (HEET) and its partners to plan and design a network of interconnected ground-source heat pump systems, or geothermal network, in an area encompassing multiple environmental justice (EJ) neighborhoods in the City of Framingham, MA. The materials provided in this dataset include, a) stakeholder and design best practices, b) study on optimal method to interconnect geothermal loops, c) guidelines for monitoring and metering, d) operations and maintenance plans, e) permitting guidelines and f) 10-day driller tutorial curriculum. These materials can guide the efficient and ethical design of future geothermal networks nationwide. The capacity of the system is estimated at 217 tons and is designed to provide 100% of heating and cooling needs for the buildings connected to the loop. In this project, 80 boreholes are used as the main thermal resources, the distribution system (or loop) consists of 0.61 miles of an 8-inch single-pipe at ambient temperature, with the capacity to connect 44 buildings, including 13 apartment buildings from the Framingham Housing Authority, one transitional home, one school building and 29 single family homes. While Framingham already has a geothermal network loop that is currently in the commissioning stage, our proposed project is unique because it is the first utility-led expansion loop (2nd loop) project that will connect to an adjacent existing geothermal loop (1st loop) in a pre-existing neighborhood. Both the 1st and 2nd loops are being installed, owned and operated by Eversource Energy, the utility Deployment Partner.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Personal Interventions for Reducing Exposure and Risk for Outdoor Air Pollution: An Official American Thoracic Society Workshop Report

Poor air quality affects the health and wellbeing of large populations around the globe. Although source controls are the most effective approaches for improving air quality and reducing health risks, individuals can also take actions to reduce their personal exposure by staying indoors, reducing physical activity, altering modes of transportation, filtering indoor air, and using respirators and other types of face masks. A synthesis of available evidence on the efficacy, effectiveness, and potential adverse effects or unintended consequences of personal interventions for air pollution is needed by clinicians to assist patients and the public in making informed decisions about use of these interventions. To address this need, the American Thoracic Society convened a workshop in May of 2018 to bring together a multidisciplinary group of international experts to review the current state of knowledge about personal interventions for air pollution and important considerations when helping patients and the general public to make decisions about how best to protect themselves. From these discussions, recommendations were made regarding when, where, how, and for whom to consider personal interventions. In addition to the efficacy and safety of the various interventions, the committee considered evidence regarding the identification of patients at greatest risk, the reliability of air quality indices, the communication challenges, and the ethical and equity considerations that arise when discussing personal interventions to reduce exposure and risk from outdoor air pollution.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2021

A Mixed-Method Design Approach for Empirically Based Selection of Unbiased Data Annotators

Implicit bias embedded in the annotated data is by far the greatest impediment in the effectual use of supervised machine learning models in tasks involving race, ethics, and geopolitical polarization. For societal good and demonstrable positive impact on wider society, it is paramount to carefully select data annotators and rigorously validate the annotation process. Current approaches to selecting annotators are not sufficiently grounded in scientific principles and are limited at the policy-guidance level, thereby rendering them unusable for machine learning practitioners. This work proposes a new approach based on the mixed-methods design that is functional, adaptable, and simpler to implement in selecting unbiased annotators for any machine learning problem. By demonstrating it on a real-world geopolitical problem, we also identified and ranked key inane profile characteristics towards an empirically-based selection of unbiased data annotators.

Thakur, Gautam Malviya↗