The shift toward electrified steel production, leading to a greater reliance on utilizing renewable energy, has the potential to increase variability of steelworker schedules and job quality. This would allow steel producers to use clean energy when it is readily available and cheaper, produce and store intermediate goods, and finish the manufacturing process at a later date. Doing so, however, introduces temporal and seasonal variabilities into the steel production process that would impact the jobs of steel workers.This grant funds efforts by a team of engineers and social scientists to study the impacts on both steel workers and manufacturing processes associated with this increased adoption of renewable energy in the steel industry. The team is led by Rebecca Ciez, Assistant Professor of Mechanical Engineering and Environmental and Ecological Engineering, and Partha Mukherjee, Professor of Mechanical Engineering, at Purdue University. They team will start by conducting structured interviews with 15-20 steelworkers from across Indiana to develop a framework for understanding worker decision-making processes and how they make tradeoffs about employment opportunities. These interviews will inform the development of a survey of steel workers that will be implemented throughout five states in the Great Lakes region (Indiana, Illinois, Michigan, Ohio, Wisconsin) to help quantify how workers value different attributes of their work schedules, such as hourly wages, shift schedules, number of months worked per year, and overtime provided. Survey respondents will be recruited using a number of modalities, including engaging companies, local steelworker union chapters, and direct mailing to engage rural steel workers in areas where non-unionized steel mills are major employers. Survey results will inform the modeling of electrified hydrogen and steel production processes, focusing on better representing how renewable-based hydrogen processes might impact steelmaking production on a daily, weekly, seasonal, or yearly basis.In addition to survey results and the hydrogen electrolysis modeling framework, outputs are expected to include academic articles, policy briefs, public repositories of shared data and code, and the training of two graduate students and one undergraduate student in survey methodologies and industrial energy systems analysis. While the framework developed will initially focus on electrified and decarbonized steel manufacturing, it may eventually be expanded and applied to other industries and manufacturing processes.

Electrifying industrial manufacturing processes is one of the key pathways to decarbonizing the U.S. energy system, yet decarbonizing industry remains challenging. This grant funds research from a team of scholars led by Erin Mayfield, Assistant Professor of Engineering at Dartmouth College and includes Maron Greenleaf, Assistant Professor of Anthropology, along with researchers at Carbon Solutions. This project will take an industry-wide look at the potential impacts of electrification on steel manufacturing. Two technologies are being developed that can help electrify steel production processes: direct reduction of iron ore using electricity and deploying low-carbon electricity to make hydrogen, which can then be used to make steel. Existing energy system capacity expansion models do not yet represent these electrified production pathways well.The team will model electrified technology options for replacing, retrofitting, or redeveloping the over 130 steel manufacturing sites in the United States and then expand the analysis to assess associated upgrading costs, production capacity, material demand, and labor impacts. Improving understanding as to how these electrified steelmaking processes will be implemented will require close engagement with steel industry stakeholders who are making such transition decisions. To integrate this perspective in the study, the team will conduct technical consultations with 3-5 steel manufacturing and technology development firms, and they will also conduct a set of community engagement activities by engaging local stakeholders across three steel production communities in the Upper Midwest. Additionally, the team will assemble a project advisory committee to provide feedback on the methodology and facilitate community engagement.Along with academic research articles, the primary output from this project will be a multi-objective online planning and mapping platform that can be used to model various industry-wide electrification and decarbonization scenarios, which the team plans to disseminate widely through numerous briefings. The project will involve training of two graduate students and multiple undergraduate students in industrial systems modeling, techno-economic assessment, and environmental justice. To further the community engagement portion of the work, the Sustainable Transitions Lab and Clinic at Dartmouth College will provide support to engage the community-level interview participants.

Rural areas are important, yet challenging, regions in which to advance electrification. In particular, the rural North is in a cold climate, has remote communities, has frequent need for back-up power (like generators) during periods of extreme weather, and has historically been dependent on fossil fuels. At the same time, these rural areas are also becoming likely spots for future renewable energy development, as they tend to have abundant natural resources and sparse population densities.This grant funds an interdisciplinary research team led by Ana Dyreson, Assistant Professor of Mechanical Engineering at Michigan Technological University, who will examine the technical and social barriers and opportunities for electrification in the rural northern region of the United States through three community-engaged case studies in Michigan (Baraga County), Wisconsin (Ashland and Iron counties), and Minnesota (Beltrami and Clearwater counties). Transitions associated with energy system electrification may also raises specific concerns for Tribal Nations in these rural regions, who have longstanding histories of facing energy and environmental extractivism. The project will focus on studying issues associated with electrifying space heating and cooling, a particularly essential and difficult energy load to electrify in this region. Each case study will involve a pair of surveys in each of these communities, one at the beginning of the study to better understand current heating and cooling options and the other at the end to assess perceived barriers and opportunities for electrification. Surveys will be co-designed with the members of the communities themselves, prioritizing the involvement of Tribal Nation representatives. There will also be engineering analyses to assess the potential readiness of homes in these regions to install electrified residential heating and cooling systems under current conditions and future electrification scenarios. Using the survey results and the technical readiness assessment, the team will develop a model of household energy use and combine it with regional datasets to extend their model to the broader regional level. All of this research will be undertaken with a lens toward understanding and identifying the local and regional energy justice implications of these electrification options.Additional research team members based at Michigan Technological University include Chelsea Schelly, Associate Professor of Sociology; Timothy Scarlett, Associate Professor of Archaeology and Anthropology; and Roman Sidortsov, Associate Professor of Energy Policy. To closely engage with the communities under study, Dyreson and her team will partner with the Center for Energy and Environment (CEE), a Minnesota-based non-governmental organization with decades of experience working with rural and Indigenous communities in the region on issues related to energy development. In addition to academic outputs, the team plans to develop an online, geospatial decision-support tool that will compare future home electrification scenarios and highlight accompanying technical, equity, and policy considerations.

This grant funds a research project by a team of scholars led by Noah Dormady, Associate Professor of Public Affairs at The Ohio State University, to better understand the economic, equity, and justice impacts of consumer electricity rate selection in Ohio and Pennsylvania. The academic research team includes Abdollah Shafieezadeh, Associate Professor Civil Engineering at The Ohio State University, and Alberto Lamadrid, Associate Professor of Economics from Lehigh University. They will examine the practice of consumers being offered and selecting above-market or predatory electricity rates using a number of qualitative and quantitative research approaches. His team has assembled a robust electricity market rate database for Ohio, which contains millions of entries on both default standard service offer (SSO) electricity rates and competitive retail electric service (CRES) retail rates offered to consumers. After constructing a similar CRES rate database for Pennsylvania, the team will survey consumers in both states to better understand household electricity rate selection and the distributional impacts of such retail rates among different populations, paying particular attention to engaging low-income and historically underrepresented racial and ethnic populations.The survey will be administered in the Columbus and Cleveland-Youngstown metro areas of Ohio and in the Lehigh Valley, Lancaster, Poconos, and Harrisburg areas of Pennsylvania. The team will then partner with local community organizations in both states to engage underrepresented households in the study. In Ohio, the team will work with the Mid-Ohio Food Collective (MOFC), a large food bank, and the Mahoning-Youngstown Community Action Partnership (MYCAP), a nonprofit that helps administer the Home Energy Assistance Program, and plan to partner with similar local organizations in Pennsylvania.Outputs from this project are expected to include economics and public policy articles reporting on the project’s findings in both Ohio and Pennsylvania. The team will also produce a detailed database containing daily electricity market data for both Ohio and Pennsylvania, as well as a separate database containing residential survey data. All data and code used for the statistical modeling and machine learning activities will also be made public. The team plans to leverage their extensive network of partnerships in government and the private sector to ensure broad dissemination of results to germane consumer protection, industrial, and regulatory communities. Numerous graduate students and undergraduate students will be trained in this project.

This grant funds an ambitious plan by an international collaboration of six laboratories to achieve a milestone that science, and humanity more generally, has imagined for quite some time: building some version of life from scratch. That claim must be qualified by cautions that the effort may not succeed and by clarification that the proposed entity is probably better viewed as a minimal form of life rather than as a (much more complex) natural cell. To be clear about the version of life herein proposed, the goal of this project is to design and build a protocell from nonliving chemicals that is capable of indefinite cycles of genetic replication, growth, and division, and which over "generations" exhibits environmentally driven Darwinian evolution. The project team is led by Jack Szostak, Professor of Chemistry at the University of Chicago and includes researchers Irene Chen (UC Santa Barbara. U.S.), Sheref Mansy (University of Alberta, Canada), Arvind Murugan (University of Chicago, U.S.), John Sutherland (Medical Research Council, United Kingdom), and Anna Wang (University of New South Wales, Australia).Project activities will consist of laboratory experiments guided by theory and computation, organized along three primary research thrusts. First, the team will conduct research to achieve indefinite cycles of RNA replication by achieving high-fidelity copying of the entire RNA-based genome. The two major components of this first thrust are optimizing the chemistry for copying a given gene sequence from a template and ensuring that the entire genome is copied. The second research thrust focuses on achieving indefinite cycles of cell growth and division. Here the primary challenge is understanding and controlling membrane growth and division, and the team will experiment with several different approaches to using fatty-acid vesicles as the primary protocell container. In the third research thrust, the research team will address issues associated with making the genetic and compartmentalization systems mutually compatible. After these major goals are achieved, the team will then observe this primitive living system over several generations as it increases in complexity, adapts and evolves, and as its genome grows to encode more information about the world.

Understanding how cells cooperate to achieve new capabilities is important since cooperation underlies the transition from single-cell life to multicellularity. This grant supports a series of experiments by Karine Gibbs, a Professor of Biology at the University of California, Berkeley, aimed at improving our understanding of the mechanisms that facilitate collective migration (swarming behavior) of the model bacterial organism Proteus mirabilis (P. mirabilis). Understanding the swarming behavior of P. mirabilis may eventually reveal fundamental principles for forming and possibly manipulating biological collectives.Professor Gibbs' work focuses on studying the role kin-recognition plays in P. mirabilis swarming behavior. Kin-recognition is a form of intercellular communication that relies on direct cell-to-cell contact. A filament carrying a toxin at its tip extends through the membrane of a P. mirabilis bacterium and punctures a neighbor's membrane, thereby delivering the toxin to the neighbor. If this neighbor-cell is genetically the same as the 'attacking' cell (i.e. it's a relative, kin) then the neighbor cell encodes the toxin as well as the antidote and the cell lives. If, however, the neighbor is not kin, then it does not encode the toxin nor the antidote and the neighbor dies.Prior studies by Professor Gibbs suggest that kin-recognition plays a role in P. mirabilis swarming and here she will use this model organism to study how collective migration is modified by two loosely-related mechanisms: intentional mutations affecting kin-recognition, and random mutations acted on by fitness-guided selection. Gibbs will leverage her prior work that correlates growth conditions with bacterial colonies exhibiting different levels of collectivity. Specifically, by varying bacterial growth conditions Gibbs is able to create two types of bacterial communities corresponding to fast/cooperative collective migration on the one hand and slow/independent migration on the other. Professor Gibbs will use her recipes for creating fast and slow swarming communities to pursue a research project with three aims.Under Aim 1, she will develop quantitative, physical metrics that can be used to distinguish fast-swarming colonies from slow-swarming colonies. Experiments involving microscopy and subsequent image-analysis will establish quantitative descriptors of cell morphology, physiology, and motility for both single-cells and for the cell-groups observed to facilitate fast swarming. Quantitative descriptors will be developed both for single-cells and for cell-groups in both fast and slow colonies. Potential descriptors include cell area, curvature, instantaneous speed, location and trajectory, adjacency to other cells, and the number of interactions over time, among others.Under Aim 2, Gibbs will use the quantitative descriptors developed in Aim 1 to assess whether and how mutations affecting kin-recognition influence collective migration. Experiments will be performed for two 'environments': growth conditions that enable fast/cooperative swarming and growth conditions that inhibit fast/cooperative swarming (thereby favoring slow/independent migration). The experimental approach involves comparing 'regular', unmutated P. mirabilis to P. mirabilis strains with mutations that disrupt the toxin secretion system used in kin-selection. This will allow Gibbs to test the hypothesis that kin-recognition provides a fitness advantage in environments where efficient swarming is possible but not in environments where independent behaviors dominate (efficient swarming not possible).Under Aim 3, Professor Gibbs will perform experiments intended to identify genes that promote collective fitness; specifically, the ability to participate in efficient swarming. Random mutations arise at some frequency and if you start with a mutant P. mirabilis that can grow but not swarm, the bacterial population will increase (growth) but will largely be constrained to its initial location (no swarming migration). As the number of bacteria increases, eventually a mutant cell will arise that has acquired a mutation that restores the ability to swarm. This mutant will swarm away from the static population, identifying itself by spatial separation and thereby allowing experimenters to capture and genetically sequence this mutant. The researchers will then determine the genome-location of the swarm-enabling mutation as well as the alterations to the descriptors of collective vs. independent behavior.

Research over the past few decades has revealed that many cellular processes require levels of accuracy and sensitivity that cannot be reached near equilibrium; living systems must exist far from thermodynamic equilibrium (TDE) in order to achieve the levels of sensitivity that allow them to survive.This grant supports research by Jordon Horowitz, Assistant Professor of Biophysics and Complex Systems at the University of Michigan, to improve our understand of living systems by studying the biochemical networks active within cells through the lens of thermodynamics. Horowitz will study broad classes of biochemical models in an effort to establish quantitative trade-offs (inequalities) between the maximum achievable sensitivity of any biochemical process and the thermodynamics driving that process. If successful, this line of research will improve our understanding of the factors constraining biological function while also revealing how closely living systems operate from the maximum achievable biochemical sensitivity. 'Sensitivity' here is being used as a flexible term intended to capture a range of bio-performance metrics such as the ability to discriminate between binding to chemical A vs chemical B, or the ability to determine whether there are few or many food molecules in the local environment.Horowitz’s research is divided into three sequential aims. In Aim 1, he will perform numerical analyses of comparatively simple models to gain insight into how network structure and thermodynamics constrain performance in simple biochemical networks. These models are too simple to represent actual cellular processes yet simple enough that numerical analysis of the available phase space is practical. Simulations will be used to study networks with varying topological structure and thermodynamic driving force in order to determine the maximum possible sensitivity, along with the model parameters that achieve that sensitivity. These numerical findings will be captured in a 'library of kinetic networks' classified by sensitivity, network topology, and thermodynamics. In Aim 2, Horowitz will attempt to use graphical methods and the Matrix Tree Theorem to mathematically (analytically) prove that these discovered limitations are in fact rigorous bounds. If successful, the result will be a set of mathematical inequalities that quantify fundamental limitations on sensitivity imposed by network structure and thermodynamic drive.In Aim 3, Horowitz will attempt to expand and apply these findings to more complicated models that have been developed to capture actual cellular process, including generalized ‘butterfly’ networks, the ‘ladder’ model of adaptation, and a generalized bacterial-flagellar-motor model.

This grant provides funding to expand a collaboration between the Digital Public Library of America, a national library composed of some 5000 member libraries, archives, and galleries across the country, and Wikipedia, the largest encyclopedia ever created. Launched with Sloan Foundation support in 2019, the collaboration allows the upload of digital files from DPLA member institution into Wikimedia Commons, Wikipedia’s archive of more than 60 million video, photo, and audio files.Since the collaboration began in 2019, 200 DPLA member institutions have uploaded more than 3 million files into the Commons. Funds from this grant support the expansion of this partnership, resulting in an anticipated five-fold increase in the number of participating DPLA members from 200 to 1000 and an estimated 15 million files uploaded to the Commons. Initial estimates predict that this upload will generate 15 million page views per month, a substantial increase for Wikimedia and an unprecedented boost for DPLA and its participating members.Grant funds will support the creation of a pipeline to more efficiently facilitate continued contributions by DPLA member institutions; marketing and outreach to DPLA network members to raise awareness and solicit new project partners; onboarding of new DPLA hubs to the pipeline; hosting of training workshops and other support to contributing institutions; making necessary software and technical upgrades to accommodate uploads of partner content; developing new reporting tools; and engaging in outreach to the Wikimedia community.The project will make DPLA the first national aggregator whose content will be systematically ingested into Wikimedia Commons, reaching millions of people and establishing a pathway to further access to tens of millions of media files for the benefit of anyone on the web.