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Recommendations for improving rigor and reproducibility in site specific characterization

Heterogeneous catalysis is driven by the interaction of reactant molecules and the catalyst surface. The locus of this interaction as well as the surrounding ensemble of atoms is referred to as the catalyst active site. Active site characterization attempts to distinguish active catalytic sites from inactive surface sites, to elucidate the structural and chemical nature of active sites, and to quantify active site concentration. Numerous techniques have been demonstrated to provide compositional and structural information about the active sites within a catalyst. However, each technique has its own limitations and experimental pitfalls that can lead to data misinterpretation or irreproducible results. Further, this work aims to provide an overview of the types of data that can be collected, to outline common experimental challenges and how to avoid them, and to assemble relevant references for the most used active site characterization techniques. More broadly, we aim to outline best practices for researchers to collect, interpret, and report active site characterization data in a way that provides the most benefit to the broader catalysis community. Increasing the rigor and reproducibility of active site characterization offers a strategy to better link properties with catalytic performance and to enable the community to develop consensus concerning these relationships.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

E2C Successful Project Implementation Cohort: Overview of Solar, Microgrid and Resilience Project Development [Slides]

The Energy to Communities (E2C) peer-learning cohort program provides technical assistance to groups of 15 community entities around a common energy topic over the course of 6 months. Every month, participants join a virtual meeting where they hear from experts and exchange strategies and best practices with their peers. This cohort, "Successful Energy Project Implementation" will explore common challenges in implementing energy projects and learn strategies to turn project plans into reality. Each participant will focus on a local energy project or priority as a cornerstone for their learning throughout the series. This presentation overviews the basics of developing solar, microgrid and resilience projects with emphasis on understanding the project development process.

14 SOLAR ENERGY↗

Leveraging Open-Source Tools for Collaborative Macro-energy System Modeling Efforts

The authors are founding team members of a new effort to develop an Open Energy Outlook for the United States. The effort aims to apply best practices of policy-focused energy system modeling, ensure transparency, build a networked community, and work toward a common purpose: examining possible US energy system futures to inform energy and climate policy efforts. Individual author biographies can be found on the project website: https://openenergyoutlook.org/.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Design Consideration for Solar Powered Wastewater Treatment Facility for Agriculture and Potable Usage on Acoma Pueblo Reservation

Environmental stewardship has long been a guiding principle among indigenous peoples. Acoma Pueblo, located approximately 45 miles west of Albuquerque, New Mexico, shares these values. They are exploring how to incorporate these values into future development projects. As such, Acoma recently created a wastewater treatment facility to provide irrigation water to nearby crops. Treatment facilities like this further sustainable practices and benefit the community but may draw power from the grid. This report looks at design considerations for possible photovoltaic utilization at the site to offset current power and monetary costs. Lessons learned from a larger, municipal wastewater treatment center will be applied with special considerations for Acoma Pueblo's values and unique wastewater treatment facility configuration.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Lignin-First Biorefinery Development

Cost-effective biomass fractionation is an enabling, grand challenge for biorefining, especially when both carbohydrates and lignin are targeted for valorization. The advent of Reductive Catalytic Fractionation (RCF) - an active stabilization approach that solubilizes lignin from biomass and catalytically depolymerizes it into a narrow slate of monomers and oligomers - represents a potential step forward for this important goal. In the Lignin-First Biorefinery Development project, we are employing techno-economic analysis (TEA) and life cycle assessment (LCA) to guide bench-scale R&D efforts towards cost-effective RCF-based biorefining. This project is critical to lignin valorization efforts and could enable the use of woody feedstocks in a traditional biochemical conversion context. To date, we have conducted the first rigorous TEA and LCA study of the RCF process, developed a flow-through system to separate biomass and the chemical catalyst in RCF chemistry, developed models for solvolysis chemistry and transport phenomena for poplar, and co-led an international, authoritative perspective on guidelines for the research community on how to best practice lignin-first biorefining. The primary challenges for the lignin-first RCF process going forward are catalyst stability, the need to utilize, recover, and recycle high boiling point solvents to lower RCF reactor pressure, and the challenge of operating RCF continuously - all of which are being directly tackled by this project.

biomass↗

Coal-dependent Communities in Transition: Identifying Best Practices to Ensure Equitable Outcomes

The U.S. coal industry is experiencing a sharp increase in the numbers of retired and/or decommissioned coal-fired power plants across the U.S. In the years between 2010-2019, around 102 gigawatts (GW) of coal-fired generating capacity has been announced to be decommissioned, representing more than 546 coal-fired power plant units, and an additional 17 GW is planned to be decommissioned by 2025. This change in the energy production landscape presents an impact on the social, environmental, and economic prospects of coal-dependent communities. This report examined the role of communities in the coal power plant decommissioning process and provided community-identified best practices to ensure an equitable process. The experiences of four coal-dependent communities—Wise County, VA, Muskegon, MI, Anderson County, TN, and Becker, MN—are presented as case studies to understand the impacts of the decommissioning process, and associated best practices, from the communities’ perspective. The report results highlight the need to recognize that the decommissioning decision-making process must be community-based to be equitable. Each community’s input is key to the transition away from coal power because there is no one-size-fits-all development plan. In other words, each community’s trajectory through the decommissioning process—from the retirement decision-making stage to the final site redevelopment phase—is unique because each community has distinct needs and wants from the energy transition. What is best for one community may not be suited for another. Ultimately, the framework for site development and community revitalization post-decommissioning cannot be universal because each community’s profile—from a social, cultural, and economic perspective—is different. Community impacts of power plant decommissioning are not limited to job and revenue losses. Communities are likely to be impacted culturally, socially, environmentally, and have long-term health-based impacts that should be acknowledged and addressed in post-retirement plans. Commonly identified decommissioning best practices include: Early and continued engagement throughout, with a number of mediums for communication and feedback (e.g., in-person sessions, virtual meetings, written comment opportunities); Early planning of post-decommissioning projects to replace lost jobs, revenue, and economic activity; Recognition (and mitigation, if possible) of social impacts on the community due to plant closure; Transparency throughout the process, with trusted information being provided about the decommissioning process and timeline; potential impacts on the workforce, economy, and environment; and the feasibility of alternative site uses; Identification of funding sources, technical experts, and/or strategic partnerships to support decommissioning and the affected communities upfront; and, Acknowledgment of communities as stakeholders who have a role in the conversation and right to determine their futures. Three key areas for assisting coal-dependent communities affected by the energy transition: Technical assistance: assessment of site feasibility for alternative uses or to repower with new technologies; Cross-partnership engagement and collaboration: facilitate knowledge-sharing of “lessons learned” about the decommissioning process between communities and provide guidance for decision-making processes; and, Financial assistance: access to grant and/or loan programs to assist with redevelopment survey, bolster community economic security through job creation, and cover environmental clean-up costs. Technical assistance, cross-partnership engagement, and financial aid can be mobilized to help communities throughout various stages of the decommissioning process, including the retirement decision, the site reclamation phase, and eventual revitalization of the site and surrounding community.

01 COAL, LIGNITE, AND PEAT↗

Multiple social platforms reveal actionable signals for software vulnerability awareness: A study of GitHub, Twitter and Reddit

Software vulnerabilities are flaws in computer systems that leave users open to attack. In many cases, these vulnerabilities go unnoticed and remain unresolved in codebases. Thus, awareness of software vulnerabilities among the public is crucial to ensure effective cybersecurity practices, the development of high quality software, and ultimately national security. This awareness can be better understood by studying the spread and evolution of software vulnerability discussions in online communities. This work is the first to evaluate and contrast how discussions about software vulnerabilities spread on three social platforms -- Twitter, GitHub, and Reddit. To lay the groundwork, we showcase a novel fundamental framework for measuring information spread that identifies the spread mechanisms and observables across platforms, the units of information, and the groups of measurements that can be applied to focus on a specific phenomena e.g., information cascades. We then analyze and contrast social network topologies for three example social networks and measure the scale and speed of the spread of discussion of specific vulnerabilities to understand how far and how widely they spread, how many users participate in discussions, and the duration of their spread. To demonstrate the awareness of more impactful software vulnerabilities, a subset of our analysis focuses on vulnerabilities targeted during recent major cyber attacks as well as vulnerabilities exploited by advanced persistent threat groups. We discover that usually, vulnerability discussions start on GitHub, before occurring on Twitter and Reddit. While studying how some user-level and content-level characteristics influence vulnerability spread, we observe that Twitter discussions started by users predicted to be humans have larger size, breadth, depth, adoption rate, lifetime, and structural virality compared to those started by users predicted to be bots. On Reddit, we contrast the differences in thread structure that originate from posts with positive, negative and neutral polarity. We find that posts that are positive have larger, deeper and wider discussions compared to negative and neutral posts. We anticipate the results of our analysis to not only increase the understanding of software vulnerability awareness but also inform models for simulating information spread across multiple social environments online.

97 MATHEMATICS AND COMPUTING↗

IROS 2023 Workshop Report: Draft Guidelines on Manufacturing Procedures, Test Methods and Reporting for Soft Robotics

Soft roboticists are facing challenges with reproducibility, which prevents researchers from making holistic comparisons to prior work, impedes full understanding of results, and forces the need to “reinvent the wheel,” delaying fundamental advances. Reproducibility of results is key to advancing science as well as achieving technology transfer from research laboratories to industrial applications. Recently, a discussion-based workshop dedicated to the topic, “Developing Standard Testing and Reporting Guidelines for Soft Robotics,” was held at IROS 2023 in Detroit, MI. The purpose of this document is to record a set of recommendations and voluntary draft guidelines for soft roboticists concerning fabrication/manufacturing, test procedures, and reporting, which were collectively developed at the workshop. Together as a community, we hope to improve the reporting standards of soft robotics and drive the field as a whole toward more rigorous research practices.

43 PARTICLE ACCELERATORS↗

Stepping into the Midwest Bioeconomy: Stakeholder Engagement and Geospatial Tools to Assist in Perennial Bioenergy Crop Decision Making and Entrepreneurship

This project, “Ecosystem Services and Farm Entrepreneurship Technical Assistance,” was a three-year project originally planned for FY22–FY24. Due to a late start and a few extensions, it is being completed in early FY25. This project explored opportunities to support the deployment of a bioeconomy with a circular, more sustainable supply chain. Using a tool developed by Argonne to identify agricultural areas suitable for use in the bioeconomy, we sought to create opportunities in the bioeconomy as biomass producers, bioenergy users, and environmental entrepreneurs. We proposed to focus at the beginning on enhancing the tool’s capabilities, while engaging with key stakeholders to improve and expand the tool’s functionality for all potential stakeholders in the bioeconomy. We believe that expanding our tools and technologies, coupled with conversations in agricultural spaces, will be needed as we continue to explore how best to offer farmers whole-of supply-chain opportunities to participate in the bioeconomy. Through this project we have continued to gain a better understanding of the ways in which farmers, landowners, bioenergy users, and environmental entrepreneurs may approach the bioeconomy. In addition, as we improve our analytic toolkit, we can continue to refine our communication and the ways in which we can valuate the bioeconomy. Refining these tools allows us to dive deeper into conversations around plausible policies and drivers for future bioeconomy investment and engagement by stakeholders. By working with farmers and agricultural landowners to enable a sustainable bioeconomy business model, enhance their energy options, and recover resources from their waste streams, this project directly responds to the Bioenergy Technology Office’s (BETO) priorities of building a resilient energy economy. It addresses BETO’s focus on fostering the development and adoption of energy technologies that enable the conversion of waste to energy, efficient land use, and robust job creation. By establishing a technical assistance program that develops capabilities and practices in agricultural areas to implement a bioeconomy future, this program will develop an important linkage between technology being developed at U.S. Department of Energy national laboratories and the agricultural communities of the Midwest. This project focuses on farmers with lower productivity farmland. Because less productive lands create a more difficult revenue stream for conventional crops, these farmers may therefore be more open to alternative agricultural land management regimes. Consequently, the technical assistance program and the methodologies for targeting perennial bioenergy crop application on marginal land provide a distinct opportunity to engage with and invest in the bioeconomy in these economically stressed areas. Stakeholders in this project include farmers and landowners, local conservation organizations (NRCS, SWCS, etc.), universities, non-profit environmental and agricultural entities, farm consultants, environmental regulators, and industry, including the industries working on conversion technologies, anaerobic digestion, pyrolysis, and biochar generation, and the companies interested in trading or purchasing/supporting the valuation of ecosystem services (ES).

09 BIOMASS FUELS↗

Data Cards for Standardized Metadata Across DOE-Aligned Data Initiatives: Toward Transparent, Interoperable, and Governed Dataset Documentation

As data-intensive research, advanced computing, and artificial intelligence become increasingly central to scientific and operational workflows, the need for consistent, transparent, and machine-actionable documentation has grown correspondingly. Multiple DOE-aligned communities—including Office of Science, Genesis Mission, American Science Cloud (AmSC), National Nuclear Security Administration (NNSA) stewardship and governance, and related cross-laboratory collaborations—have independently developed metadata practices to support discovery, access, reuse, repository deposit, and compliance.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Calista Energy Management Assistance Initiative

The Calista Energy Management Assistance Initiative (CEMAI) provided technical assistance and capacity building for 56 Tribal communities in the Calista Region of Alaska as an effort to reduce costs, improve operational efficiency, enhance human capacity, and job opportunities. CEMAI catalyzed and guided numerous efforts into a consolidated and effective initiative that brought rural energy best practices, economies of scale, operational efficiencies, human capacity, and economic development to the forefront. Calista Corporation (Calista) is one of thirteen Alaska Native Regional Corporations created under the Alaska Native Claims Settlement Act of 1971 (ANCSA) in the settlement of aboriginal land claims. Calista was incorporated in Alaska on June 12, 1972. The Calista Region covers Alaska’s Bethel and Kusilvak (formerly Wade Hampton) Census areas and includes 56 communities. Calista partnered with Nuvista Light and Electric Cooperative (Nuvista) on the Department of Energy, Office of Indian Energy (DOE-OIE), CEMAI project. Nuvista is a non-profit that seeks to reduce energy costs and provide renewable sources of energy to the people of western Alaska. It is founded and led by a non-profit, Tribe, Native Corporations (including Calista), energy organizations, and Alaska Native stakeholders in the Yukon-Kuskokwim Delta (YK-D) Region; covering the same service boundaries and communities served by Calista. This partnership allowed Calista to direct the project work with local energy experts to respond to community needs. In this arrangement, Calista added credibility and regional accountability while Nuvista added energy-specific expertise and skill set in project management. The delivery of the CEMAI Workplan included short-term or on-demand responses to specific technical assistance requests from communities in addition to longer-term strategically directed activities such as workshops, coordinated training, and capacity development efforts across the region. CEMAI’s Workplan aimed to enhance communities’ readiness for establishing renewable energy projects and implementing energy efficiency initiatives. The CEMAI objectives included: (1) Identifying common operational needs and improvement opportunities for entities with an energy interest or responsibility. (2) Providing access to multi-level expertise to address existing challenges. (3) Developing specialized training programs to build local capacity and community readiness. (4) Nurturing the creation of regional support networks. (5) Increasing access to regional, state, and federal energy initiatives, funding, and expertise. (6) Improving technical skills, provide livable wages, and job opportunities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

WRF-ELM v1.0: a regional climate model to study land–atmosphere interactions over heterogeneous land use regions

Abstract. The Energy Exascale Earth System Model (E3SM) Land Model (ELM) is a state-of-the-art land surface model that simulates the intricate interactions between the terrestrial land surface and other components of the Earth system. Originating from the Community Land Model (CLM) version 4.5, ELM has been under active development, with added new features and functionality, including plant hydraulics, radiation–topography interaction, subsurface multiphase flow, and more explicit land use and management practices. This study integrates ELM v2.1 with the Weather Research and Forecasting (WRF; WRF-ELM) model through a modified Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) framework, enabling affordable high-resolution regional modeling by leveraging ELM's innovative features alongside WRF's diverse atmospheric parameterization options. This framework includes a top-level driver for variable communication between WRF and ELM and Earth System Modeling Framework (ESMF) caps for the WRF atmospheric component and ELM workflow control, encompassing initialization, execution, and finalization. Importantly, this LILAC–ESMF framework demonstrates a more modular approach compared to previous coupling efforts between WRF and land surface models. It maintains the integrity of ELM's source code structure and facilitates the transfer of future developments in ELM to WRF-ELM. To test the ability of the coupled model to capture land–atmosphere interactions over regions with a variety of land uses and land covers, we conducted high-resolution (4 km) WRF-ELM ensemble simulations over the Great Lakes region (GLR) in the summer of 2018 and systematically compared the results against observations, reanalysis data, and WRF-CTSM (WRF coupled with the Community Terrestrial Systems Model). In general, the coupled WRF-ELM model has reasonably captured the spatial distribution of surface state variables and fluxes across the GLR, particularly over the natural vegetation areas. The evaluation results provide a baseline reference for further improvements in ELM in the regional application of high-resolution weather and climate predictions. Our work serves as an example to the model development community for expanding an advanced land surface model's capability to represent fully-coupled land–atmosphere interactions at fine spatial scales. The development and release of WRF-ELM marks a significant advancement for the ELM user community, providing opportunities for fine-scale regional representation, parameter calibration in coupled mode, and examination of new schemes with atmospheric feedback.

54 ENVIRONMENTAL SCIENCES↗

Elevating Engagement: Insights for Energy Infrastructure Siting from Oregon Literature

Our study conducts a meta-synthesis of existing Oregon-based literature on stakeholder and community engagement methods across a variety of contexts to identify best practices and lessons learned to inform future engagement processes for Oregon’s energy siting. We analyze and synthesize these strategies to understand what has worked well across engagement practices and how we can integrate and learn from a variety of methods to develop more effective practices for engagement moving forward. We look at the successes and challenges for each method, applying lessons learned to the pre-permitting phase of energy development and infrastructure planning in Oregon. Our results synthesize key recommendations for engagement in the pre-permitting phase for energy infrastructure siting in Oregon, such as consensus and relationship building, local partnerships, and background research to understand community context.

energy infrastructure↗

Principles of the Battery Data Genome

Batteries are central to modern society. They are no longer just a convenience but a critical enabler of the transition to a resilient, low-carbon economy. Battery development capabilities are provided by communities spanning materials discovery, battery chemistry and electrochemistry, cell and pack design, scale-up, manufacturing, and deployments. Despite their relative maturity, data-science practices among these diverse groups are far behind the state of the art in other fields, which have demonstrated an ability to significantly improve innovation and economic impact. The negative consequences of the present paradigm include incremental improvements but few breakthroughs, significant manufacturing uncertainties, and cascading investment risks that collectively slow deployments. The primary roadblock to a battery-data-science renaissance is the requirement for large amounts of high-quality data, which are not available in the current fragmented ecosystem. Here, in this study, we identify gaps and propose principles that enable the solution by building a robust community of data hubs with standardized practices and flexible sharing options that will seed advanced tools spanning innovation to deployment. Precedents are offered that demonstrate that both public good and immense economic gains will arise from sharing valuable battery data. The proposed Battery Data Genome looks to broadly transform innovations and revolutionize their translation from research to societal impact.

25 ENERGY STORAGE↗

LA100 Equity Strategies. Chapter 2: Procedural Justice

The LA100 Equity Strategies project synthesizes community guidance with robust research, modeling, and analysis to identify strategy options that can increase equitable outcomes in Los Angeles' clean energy transition. Grounded in the analysis of past and ongoing energy inequities and engagement with underserved communities, the project presents community-guided and community-tailored strategies that aim to operationalize recognition and procedural justice. This chapter focuses on procedural justice, examining priorities identified during the community engagement portion of the LA100 Equity Strategies project. This process, and our approach to partnering with community-based organizations (CBOs) and the communities they serve, was developed from the baseline analysis in Chapter 1, which centers on recognition justice, examining past and current inequities in LA. Recognition, procedural, and distributional justice are the three tenets of energy justice around which the LA100 Equity Strategies project is organized. Procedural justice prioritizes fair, equitable, and inclusive participation in the decision-making process. This tenet's practical application entails who is invited and able to participate, whose voices are considered as decisions are made, the co-development of procedures to inform this deliberative process, and who has access to formal measures of regulation and accountability. Engaging with Angelenos to examine the causes of inequities and identify impact areas and priorities that center community experiences, values, and goals represents a first step in developing energy equity strategies for the Los Angeles Department of Water and Power (LADWP) to achieve distributional justice - the just and equitable distribution of energy benefits and burdens in LA's energy transition. Equity, as community members insisted, is about making - and following through with - a commitment to prioritize historically underserved and overburdened communities. Community engagement is a principal method for operationalizing this commitment, guiding our analytic approach and potential equity strategies. Using procedural justice as an analytical tool, this chapter presents the LA100 Equity Strategies approach to community engagement from 2021 to 2023 and the results of this process in relation to community-identified barriers and burdens impacting procedural justice outcomes. We analyze the procedural elements of reaching the equity goals Angelenos set to inform future LADWP decision-making and program development.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Transforming Science Through Software: Improving While Delivering 100×

The U.S. Department of Energy (DOE) Exascale Computing Project (ECP) funded the development of new (and the transformation of important existing) applications, libraries, and tools that realized improvement in performance and capabilities of often 100 times or more on emerging exascale computers. This exceptional gain inspired the title of this special issue: Transforming Science through Software: Improving while delivering 100X. The term 100X refers to advancing capabilities in modeling, simulation, and analysis by a factor of 100 or more using some combination of new algorithms, optimization techniques, software libraries, and programming models, coupled with the next generation of hardware for high-performance computing (HPC). The papers in this issue share experiences with the practice and science of scientific software development, with an emphasis on developing a coherent, portable, and sustainable HPC software ecosystem for next-generation computational science. Finally, we hope to foster expanded community efforts related to the fundamental role of sustainable scientific software ecosystems in advancing the computing sciences.

97 MATHEMATICS AND COMPUTING↗

On the compatibility of established methods with emerging artificial intelligence and machine learning methods for disaster risk analysis

Abstract There is growing interest in leveraging advanced analytics, including artificial intelligence (AI) and machine learning (ML), for disaster risk analysis (RA) applications. These emerging methods offer unprecedented abilities to assess risk in settings where threats can emerge and transform quickly by relying on “learning” through datasets. There is a need to understand these emerging methods in comparison to the more established set of risk assessment methods commonly used in practice. These existing methods are generally accepted by the risk community and are grounded in use across various risk application areas. The next frontier in RA with emerging methods is to develop insights for evaluating the compatibility of those risk methods with more recent advancements in AI/ML, particularly with consideration of usefulness, trust, explainability, and other factors. This article leverages inputs from RA and AI experts to investigate the compatibility of various risk assessment methods, including both established methods and an example of a commonly used AI‐based method for disaster RA applications. This article utilizes empirical evidence from expert perspectives to support key insights on those methods and the compatibility of those methods. This article will be of interest to researchers and practitioners in risk‐analytics disciplines who leverage AI/ML methods.

Mathematical Methods In Social Sciences↗

An Update to the NREL Baseline Wind Turbine Controller: Preprint

The NREL 5MW wind turbine model is well established as an industry standard and is often used as a comparison model, or a model on which to build upon. Though effective, the legacy controller for the NREL 5MW wind turbine is built on a simple algorithm that is not up to date with many industry standards. Additionally, as the research community has advanced into more fast-paced development cycles, as systems engineering tools such as WISDEM \cite{WISDEM} are employed, and as a greater focus on controls co-design practices is encouraged, a demand for a generic wind turbine controller has arisen. This work presents updates for the NREL 5MW baseline controller to a more modern control architecture, and establishes a generic tuning framework that can be easily adapted to various wind turbines. Based on initial results, the updated generic controller eases the automatic tuning process, while maintaining or improving upon the performance of the legacy NREL 5MW controller.

17 WIND ENERGY↗