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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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DOE OSTI2022

Evaluating the performance of random forest and iterative random forest based methods when applied to gene expression data

Gene-to-gene networks, such as Gene Regulatory Networks (GRN) and Predictive Expression Networks (PEN) capture relationships between genes and are beneficial for use in downstream biological analyses. There exists multiple network inference tools to produce these gene-to-gene networks from matrices of gene expression data. Random Forest-Leave One Out Prediction (RF-LOOP) is a method that has been shown to be efficient at producing these gene-to-gene networks, frequently known as GEne Network Inference with Ensemble of trees (GENIE3). Random Forest can be replaced in this process by iterative Random Forest (iRF), which performs variable selection and boosting. Here we validate that iterative Random Forest-Leave One Out Prediction (iRF-LOOP) produces higher quality networks than GENIE3 (RF-LOOP). We use both synthetic and empirical networks from the Dialogue for Reverse Engineering Assessment and Methods (DREAM) Challenges by Sage Bionetworks, as well as two additional empirical networks created from Arabidopsis thaliana and Populus trichocarpa expression data.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Confronting barriers and recognizing opportunities: Developing effective community-based environmental monitoring programs to meet the needs of Aboriginal communities

Aboriginal communities can be negatively affected by resource development, but often they do not have a full opportunity to participate in project review and the resulting monitoring and mitigation activities. Cumulative impacts of resource development are also typically neglected in monitoring protocols that focus on a limited number of environmental values, rather than adopting a long-term, holistic view of development over time and space. Community-based environmental monitoring (CBEM) is emerging as a way to meaningfully include local Aboriginal citizens in the decision-making process as well as the assessment of the long-term impacts of the development of natural resources. We explored opportunities and barriers for developing CBEM programs that meet the needs of small and rural Aboriginal communities that are faced with the rapid and wide-spread development of natural resources. We conducted interviews with a local Aboriginal community, and natural resource management practitioners who could provide perspectives on the application of CBEM to resource management in north-central British Columbia, Canada. Results demonstrate that CBEM offers a locally adapted and culturally appropriate approach to facilitate the participation of Aboriginal communities in natural resource decision making and management. The interpretation of the specific role and purpose of CBEM differed among participants, depending on their objectives for and concerns about natural resource development. However, all parties were consistent in viewing CBEM as an effective method for engaging in dialogue, cooperation, and tracking environmental change. The development or improvement of CBEM programs should consider the efficacy of monitoring protocols, social cohesion and relationships, ability to inform decision-making, and effectiveness of CBEM for the members of the community. - Highlights: • We explored how to develop effective CBEM with a focus on Aboriginal communities. • We identified opportunities and barriers for developing CBEM programs. • CBEM can facilitate Aboriginal community participation in natural resource management.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Modular evaluation method for subsurface activities (MEMSA). A novel approach for integrating social acceptance in a permit decision-making process for subsurface activities

We investigate how the decision support system ‘Modular Evaluation Method Subsurface Activities’ (MEMSA) can help facilitate an informed decision-making process for permit applications of subsurface activities. To this end, we analyze the extent the MEMSA approach allows for a dialogue between stakeholders in a transparent manner. We use the exploration permit for the underground gas storage facility at the Pieterburen salt dome (Netherlands) as a case study. The results suggest that the MEMSA approach is flexible enough to adjust to changing conditions. Furthermore, MEMSA provides a novel way for identifying structural problems and possible solutions in permit decision-making processes for subsurface activities, on the basis of the sensitivity analysis of intermediate rankings. We suggest that the planned size of an activity should already be specified in the exploration phase, because this would allow for a more efficient use of the subsurface as a whole. We conclude that the host community should be involved to a greater extent and in an early phase of the permit decision-making process, for example, already during the initial analysis of the project area of a subsurface activity. We suggest that strategic national policy goals are to be re-evaluated on a regular basis, in the form of a strategic vision for the subsurface, to account for timing discrepancies between the realization of activities and policy deadlines, because this discrepancy can have a large impact on the necessity and therefore acceptance of a subsurface activity.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2017

Social sensitivity analysis in conflictive environmental governance: A case of forest planning

In environmental governance, there is a need to include tools that analyze the robustness of the assessment processes, as well as the validity of policies and measures. This requires a methodological framework that integrates formal techniques such as sensitivity analysis with what the authors have called social sensitivity analysis. The latter consists of participatory processes in which stakeholders analyze the robustness of the assessment process used as well as the validity of the results of such assessments. This methodology was applied to a procedure for assessing planning alternatives for forest tracks. Sensitivity analysis studies the technical robustness of the results of the assessment, as well as exploring the social validity of these results, thus facilitating processes of dialogue and consensus needed in decision-making in conflictive situations. These results are considered interesting, not only from the perspective of implanting polices, but also as a reference for other places with similar situations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Governance in Strategic Environmental Assessment: Lessons from the Portuguese practice

The analysis of governance in Strategic Environmental Assessment (SEA) can help understand why, whether and how strategic decision-making happens. Understanding the governance context is strategic to improve the role and capacity of SEA to stimulate, and legitimate decisions that integrate environmental issues and are sustainability driven. The objective of this paper is to discuss why governance is important in SEA. In the SEA literature governance is mostly addressed in silos (i.e. public participation or decisions transparency or accountability) rather than in an integrated way. In addition few authors adopt a strategic view to address the governance context within which SEA is used. In this paper we address the heuristics of governance in SEA based on theoretical and empirical evidence, suggesting how SEA may incorporate the governance dimension. First a review of the SEA literature in relation to governance sets the context to the analysis on how governance is approached in practice, based on 60 Portuguese SEA cases. This is followed by the presentation of an empirical SEA case conducted in Portugal to illustrate what, in our understanding, can be an example of good practice in considering governance in SEA. Final discussion reflects on the role of governance in SEA in promoting engagement, enabling collaborative action, learning processes and dialogues, concluding on the relevance of governance in creating development contexts that can deal with change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

A modeling comparison of deep greenhouse gas emissions reduction scenarios by 2030 in California

California aims to reduce greenhouse gas (GHG) emissions to 40% below 1990 levels by 2030. We compare six energy models that have played various roles in informing the state policymakers in setting climate policy goals and targets. These models adopt a range of modeling structures, including stock-turnover back-casting models, a least-cost optimization model, macroeconomic/macro-econometric models, and an electricity dispatch model. Results from these models provide useful insights in terms of the transformations in the energy system required, including efficiency improvements in cars, trucks, and buildings, electrification of end-uses, low- or zero-carbon electricity and fuels, aggressive adoptions of zero-emission vehicles (ZEVs), demand reduction, and large reductions of non-energy GHG emissions. Some of these studies also suggest that the direct economic costs can be fairly modest or even generate net savings, while the indirect macroeconomic benefits are large, as shifts in employment and capital investments could have higher economic returns than conventional energy expenditures. These models, however, often assume perfect markets, perfect competition, and zero transaction costs. They also do not provide specific policy guidance on how these transformative changes can be achieved. Greater emphasis on modeling uncertainty, consumer behaviors, heterogeneity of impacts, and spatial modeling would further enhance policymakers' ability to design more effective and targeted policies. Here, this paper presents an example of how policymakers, energy system modelers and stakeholders interact and work together to develop and evaluate long-term state climate policy targets. Lastly, even though this paper focuses on California, the process of dialogue and interactions, modeling results, and lessons learned can be generally adopted across different regions and scales.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2026

Shadow of the Future: Developing Trust and Software within the Exascale Computing Project

Collaboration and team science are emerging areas of interest in software production. Historically, multi-institutional research collaborations are difficult to initiate and maintain, negatively impacting communication, negotiation, and dialogue between industry, government, and academic researchers. The Exascale Computing Project (ECP), a massive, multi-team, high-stakes initiative, facilitated broader research collaboration under a shared funding structure and extended timeline to support scientific discovery. Here, we conducted interviews with ECP teams, representing a variety of domain specialties, research institutions, and programming backgrounds. Using thematic analysis, we assessed how ECP’s structure created an environment of increased trust among projects and how software shared between teams facilitated sustained collaboration. We found that the expectation of future collaboration, i.e., the shadow of the future, greatly enhanced trust among teams and the quality of scientific software produced. Based on our findings within ECP projects, we connect to the existing literature on trust in software engineering and share recommendations for sustainable multi-institutional collaboration and shared best software practices.

Exascale computing project↗

DOE OSTI2014

Current Status and Recommendations for the Future of Research, Teaching, and Testing in the Biological Sciences of Radiation Oncology: Report of the American Society for Radiation Oncology Cancer Biology/Radiation Biology Task Force, Executive Summary

In early 2011, a dialogue was initiated within the Board of Directors (BOD) of the American Society for Radiation Oncology (ASTRO) regarding the future of the basic sciences of the specialty, primarily focused on the current state and potential future direction of basic research within radiation oncology. After consideration of the complexity of the issues involved and the precise nature of the undertaking, in August 2011, the BOD empanelled a Cancer Biology/Radiation Biology Task Force (TF). The TF was charged with developing an accurate snapshot of the current state of basic (preclinical) research in radiation oncology from the perspective of relevance to the modern clinical practice of radiation oncology as well as the education of our trainees and attending physicians in the biological sciences. The TF was further charged with making suggestions as to critical areas of biological basic research investigation that might be most likely to maintain and build further the scientific foundation and vitality of radiation oncology as an independent and vibrant medical specialty. It was not within the scope of service of the TF to consider the quality of ongoing research efforts within the broader radiation oncology space, to presume to consider their future potential, or to discourage in any way the investigators committed to areas of interest other than those targeted. The TF charge specifically precluded consideration of research issues related to technology, physics, or clinical investigations. This document represents an Executive Summary of the Task Force report.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2022

The lay of the land: What we know about non-operating agricultural and absentee forest landowners in the U.S. and Europe

While non-operating agricultural and absentee forest landowners across the U.S. and Europe are an important group of landowners, our understanding of them remains relatively limited. In this paper, we conduct a systematic literature review on these landowners to encapsulate a current lay of the land in terms of what we know about these landowners and move the dialogue on this topic forward. Eighty-one articles are identified in our search of empirical literature. For each of the landowner types, we discuss their demographics and the three primary themes that emerged related to land management: participation in land management decisions, attitudes regarding land use and ownership, and resource needs in working with these landowners. For agricultural non-operating landowners, we find limited participation in land management decisions, particularly among women, a variety of individual and social factors play a role in involvement, and while they have pro-conservation attitudes, implementation of conservation practices is more limited. Absentee forest landowners we find are more willing to use management plans, yet less willing to engage in active management and risk reduction. These landowners have a range of attitudes regarding land use, with studies highlighting recreation, conservation, and profit motivations. In conclusion, our review concludes with identifying specific needs for more research and outreach on these landowners.

absentee↗

DOE OSTI2024

Using stable isotopes to inform water resource management in forested and agricultural ecosystems

Present and future climatic trends are expected to markedly alter water fluxes and stores in the hydrologic cycle. In addition, water demand continues to grow due to increased human use and a growing population. Sustainably managing water resources requires a thorough understanding of water storage and flow in natural, agricultural, and urban ecosystems. Measurements of stable isotopes of water (hydrogen and oxygen) in the water cycle (atmosphere, soils, plants, surface water, and groundwater) can provide information on the transport pathways, sourcing, dynamics, ages, and storage pools of water that is difficult to obtain with other techniques. However, the potential of these techniques for practical questions has not been fully exploited yet. Here, we outline the benefits and limitations of potential applications of stable isotope methods useful to water managers, farmers, and other stakeholders. We also describe several case studies demonstrating how stable isotopes of water can support water management decision-making. Finally, we propose a workflow that guides users through a sequence of decisions required to apply stable isotope methods to examples of water management issues. We call for ongoing dialogue and a stronger connection between water management stakeholders and water stable isotope practitioners to identify the most pressing issues and develop best-practice guidelines to apply these techniques.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Parton distributions and lattice QCD calculations: A community white paper

In the framework of quantum chromodynamics (QCD), parton distribution functions (PDFs) quantify how the momentum and spin of a hadron are divided among its quark and gluon constituents. Two main approaches exist to determine PDFs. The first approach, based on QCD factorization theorems, realizes a QCD analysis of a suitable set of hard-scattering measurements, often using a variety of hadronic observables. The second approach, based on first-principle operator definitions of PDFs, uses lattice QCD to compute directly some PDF-related quantities, such as their moments. Motivated by recent progress in both approaches, in this paper we present an overview of lattice-QCD and global-analysis techniques used to determine unpolarized and polarized proton PDFs and their moments. We provide benchmark numbers to validate present and future lattice-QCD calculations and we illustrate how they could be used to reduce the PDF uncertainties in current unpolarized and polarized global analyses. Finally, this document represents a first step towards establishing a common language between the two communities, to foster dialogue and to further improve our knowledge of PDFs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Food–Energy–Water Crises in the United States and China: Commonalities and Asynchronous Experiences Support Integration of Global Efforts

Food, energy, and water (FEW) systems have been recognized as an issue of critical global importance. Understanding the mechanisms that govern the FEW nexus is essential to develop solutions and avoid humanitarian crises of displacement, famine, and disease. The U.S. and China are the world’s leading economies. Although the two nations are shaped by fundamentally different political and economic systems, they share FEW trajectories in several complementary ways. These realities place the U.S. and China in unique positions to engage in problem definition, dialogue, actions, and transdisciplinary convergence of research to achieve productive solutions addressing FEW challenges. By comparing the nexus and functions of the FEW systems in the two nations, this perspective aims to facilitate collaborative innovations that reduce disciplinary silos, mitigate FEW challenges, and enhance environmental sustainability. Finally, the review of experiences and challenges facing the U.S. and China also offers valuable insights for other nations seeking to achieve sustainable development goals.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Safety moments in chemical safety education.

Chemical safety education is a critical aspect of an integrated culture of safety in academic research settings. Showcasing best practices and sharing practical solutions for recognizing hazards and minimizing risks represent one way of reinforcing a research community's actions, attitudes, and behavior toward safety. For goals of improving chemical safety education with nonformal endeavors, safety moments are similar to 1-2 slides that focus on raising awareness and knowledge for routine safety issues in research laboratories. Intended to catalyze brief discussions at the beginning of meetings and presentations, these materials provide a proactive way for students and faculty to engage in open communication on diverse research safety topics across science and engineering. This commentary provides an overview of designing effective safety moments and tailoring them to highlight practical safety needs and considerations. Key components of model safety moment slides are presented, alongside centralized resources assembled by student-led laboratory safety teams, which can also be extended to posters, social media platforms, online videos, and other forms of scientific communication. Combined with both top-down backing from institution leaders and bottom-up support from student researchers, safety moments remain a low-barrier risk reduction strategy that is easy to implement, encourages local dialogue on safety, combats complacency, and holds potential for facilitating long-term improvements to academic lab safety culture.

Communication/Writing↗

DOE OSTI2024

Incorporating Coverage-Dependent Reaction Barriers into First-Principles-Based Microkinetic Models: Approaches and Challenges

Mean-field microkinetic models (MKMs) are appealing for their relatively facile construction, computational tractability, and high-throughput catalyst screening capabilities. As such, they will continue to be a valuable tool for materials design in heterogeneous catalysis even as the field aims to describe more complex systems. Numerous prior reports have provided the groundwork for constructing first-principles-based MKMs, including the analysis of strategies for incorporating lateral interactions into thermodynamic parameters (e.g., adsorption energies). Yet, there remains a need for concerted dialogue on methods for calculating and incorporating coverage-dependent kinetic parameters into MKMs. In this Perspective, we assess strategies for doing so, including the corresponding key physical implications and computational challenges. Here, we emphasize that decoupling thermodynamic and kinetic parameters within MKMs can violate thermodynamic consistency and risk unphysical solutions. For some reactions and catalyst materials, scaling relationships can predict coverage-dependent activation energies, but there are several exceptions evident in the literature, indicating that this approach is not universally applicable and that the field could benefit from research aimed at elucidating the limitations. Conducting high-coverage transition state searches is a rigorous but computationally costly strategy, and the effects of various methods for mitigating this cost on resulting energetics have yet to be broadly explored and validated. The goal of this Perspective is to generate discussion on and inspire focused research into the physical relevance of approaches for describing coverage-dependent reaction barriers in MKMs, including the development of computationally tractable methodologies, to advance the applicability of MKMs across diverse reaction chemistries and conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2026

AutoLabs: cognitive multi-agent systems with self-correction for autonomous chemical experimentation

The automation of chemical research through self-driving laboratories (SDLs) promises to accelerate scientific discovery, yet the reliability and granular performance of the underlying AI agents remain critical, under-examined challenges. In this work, we introduce AutoLabs, a self-correcting, multi-agent architecture designed to autonomously translate natural-language instructions into executable protocols for a high-throughput liquid handler. The system engages users in dialogue, decomposes experimental goals into discrete tasks for specialized agents, performs tool-assisted stoichiometric calculations, and iteratively self-corrects its output before generating a hardware-ready file. We present a comprehensive evaluation framework featuring five benchmark experiments of increasing complexity, from simple sample preparation to multi-plate timed syntheses. Through a systematic ablation study of 20 agent configurations, we assess the impact of reasoning capacity, architectural design (single- vs. multi-agent), tool use, and self-correction mechanisms. Our results demonstrate that agent reasoning capacity is the most critical factor for success, reducing quantitative errors in chemical amounts (nRMSE) by over 85% in complex tasks. When combined with a multi-agent architecture and iterative self-correction, AutoLabs approaches expert-authored reference procedures on the benchmark (F1-score > 0.89) on challenging multi-plate syntheses. These findings establish a clear blueprint for developing robust and trustworthy AI partners for autonomous laboratories, highlighting the synergistic effects of modular design, advanced reasoning, and self-correction to ensure both performance and reliability in high-stakes scientific applications. Code: https://github.com/pnnl/autolabs

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Solving tricky quantum optics problems with assistance from large language models

The capabilities of modern artificial intelligence (AI) as a “scientific collaborator” are explored by engaging it with three nuanced problems in quantum optics: state populations in optical pumping, resonant transitions between decaying states (the Burshtein effect), and degenerate mirrorless lasing. Through iterative dialogue, the authors observe that AI models–when prompted and corrected–can reason through complex scenarios, refine their answers, and provide expert-level guidance, closely resembling the interaction with an adept colleague. The findings highlight that AI can democratize access to sophisticated modeling and analysis, shifting the focus in scientific practice from technical mastery to the generation and testing of ideas, and reducing the time for completing research tasks from days to minutes.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2022

Disentangling direct from indirect relationships in association networks

Networks are vital tools for understanding and modeling interactions in complex systems in science and engineering, and direct and indirect interactions are pervasive in all types of networks. However, quantitatively disentangling direct and indirect relationships in networks remains a formidable task. Here, we present a framework, called iDIRECT (Inference of Direct and Indirect Relationships with Effective Copula-based Transitivity), for quantitatively inferring direct dependencies in association networks. Using copula-based transitivity, iDIRECT eliminates/ameliorates several challenging mathematical problems, including ill-conditioning, self-looping, and interaction strength overflow. With simulation data as benchmark examples, iDIRECT showed high prediction accuracies. Application of iDIRECT to reconstruct gene regulatory networks in Escherichia coli also revealed considerably higher prediction power than the best-performing approaches in the DREAM5 (Dialogue on Reverse Engineering Assessment and Methods project, #5) Network Inference Challenge. In addition, applying iDIRECT to highly diverse grassland soil microbial communities in response to climate warming showed that the iDIRECT-processed networks were significantly different from the original networks, with considerably fewer nodes, links, and connectivity, but higher relative modularity. Further analysis revealed that the iDIRECT-processed network was more complex under warming than the control and more robust to both random and target species removal ( P < 0.001). As a general approach, iDIRECT has great advantages for network inference, and it should be widely applicable to infer direct relationships in association networks across diverse disciplines in science and engineering.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

PIBHI 2025: status and perspectives of ECR ion sources

The article summarizes the discussions held during the PIBHI 2025 workshop (https://agenda.infn.it/e/pibhi2025) highlighting the most significant points to have emerged. The main goal of the workshop was to foster dialogue on topics relevant to the ECR ion sources (ECRIS) community through dedicated and thematic round tables. The outcomes of these discussions are outlined below, with particular focus on the remaining open questions in the field.

43 PARTICLE ACCELERATORS↗