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AI-powered municipal solid waste management: a comprehensive review from generation to utilization

The accumulation of municipal solid waste (MSW) continues to rise due to burgeoning population, rapid global urbanization and economic growth, intensifying ecological concerns associated with landfills and greenhouse gas (GHG) emissions. Over the past 2 decades, global waste generation has surged by 50%, with one-third remaining uncollected and about 70% sent to landfills. This review examines the critical role of integrating emerging technologies, such as advanced sensors and artificial intelligence (AI), into end-to-end MSW management to alleviate landfill burdens. The suitability of various AI tools for different stages of MSW management is assessed, alongside the deployment of advanced sensors including hyperspectral cameras, computer vision systems, and internet of things (IoT) devices for material identification. Applications of genetic algorithms and reinforcement learning for optimizing collection routes, reducing costs, and lowering emissions are highlighted. Life cycle assessment (LCA) across all stages of MSW management is also reviewed, along with future trends in leveraging generative AI, natural language processing (NLP), and agent-based AI systems to analyze waste generation patterns and public sentiment. Efficient collection and handling can be enhanced through route optimization with geographic information systems and real-time bin-level monitoring. Furthermore, sensor-embedded, real-time object detection systems paired with robotics enable material characterization and automated sorting, thereby lowering costs and diverting waste from landfills into value-added products for diverse industrial sectors including packaging, chemicals, textiles, metals and glass, transportation, and electronics industries. Without intervention, global waste is projected to reach 4.54 billion tons by 2050, contributing direct economic costs of $\$$400 billion and roughly 2.38 billion tons of CO 2 -equivalent emissions annually. This review demonstrates how AI-driven, end-to-end solutions for MSW management can mitigate economic and environmental challenges, while directly supporting the United Nations Sustainable Development (UNDP) goals related to innovation and infrastructure (SDG 9), sustainable cities (SDG 11), responsible consumption and production (SDG 12), and climate action (SDG 13).

09 BIOMASS FUELS↗

Recent evolution of risk analyses in atomic bomb survivor studies: new methods and applications

Abstract Several decades ago a dramatic leap forward occurred in the development and application of statistical methods for modeling radiation risk at the Radiation Effects Research Foundation (RERF). Poisson regression analysis for grouped person-year cohort data and the linear excess relative risk model were introduced, and subsequently a devoted software system, Epicure® (https://www.hirosoft.com), was developed by researchers at RERF and at the U.S. National Cancer Institute. Numerous advancements in understanding radiation effects on humans were made possible with these methods, which are still the state-of-the-art for risk assessment at RERF and have remained part of the standard toolbox for radiation—and other environmental—epidemiological studies worldwide. Nevertheless, as our understanding of radiation risk has increased, so have the breadth and depth of questions that require answers based on emerging data that are not amenable to these conventional methods. This overview briefly recounts the conventional methods and then describes our recent diversification into the use or development of new statistical approaches to meet the challenges of burgeoning biological data and emerging mechanistic information. We briefly discuss the development and application of new methods, current and planned, that are part of the RERF Statistics Department’s role in supporting institution-wide research, especially in our collaborations involving the Life Span Study, Adult Health Study, and First-generation Offspring Clinical Study. Some approaches to modeling and assessing radiation risk with newer methods mentioned herein have already been published, while some are still in development or are only beginning at the proposal stage.

Oncology↗

Environmental life-cycle analysis of hydrogen technology pathways in the United States

Hydrogen is a zero-carbon energy carrier with potential to decarbonize industrial and transportation sectors, but its life-cycle greenhouse gas (GHG) emissions depend on its energy supply chain and carbon management measures (e.g., carbon capture and storage). Global support for clean hydrogen production and use has recently intensified. In the United States, Congress passed several laws that incentivize the production and use of renewable and low-carbon hydrogen, such as the Bipartisan Infrastructure Law (BIL) in 2021 and the Inflation Reduction Act (IRA) in 2022, which provides tax credits of up to $3/kg depending on the carbon intensity of the produced hydrogen. A comprehensive life-cycle accounting of GHG emissions associated with hydrogen production is needed to determine the carbon intensity of hydrogen throughout its value chain. In the United States, Argonne’s R&D GREET ® (Greenhouse Gases, Regulated emissions, and Energy use in Technologies) model has been widely used for hydrogen carbon intensity calculations. This paper describes the major hydrogen technology pathways considered in the United States and provides data sources and carbon intensity results for each of the hydrogen production and delivery pathways using consistent system boundaries and most recent technology performance and supply chain data.

Elgowainy, Amgad↗

Supporting the Li-Ion Battery Supply Chain via PEV Battery Reuse

The electric vehicle market is growing rapidly and there is significant need for lithium ion batteries and their materials. There is growing concern about the supply chain issues of lithium ion batteries in the US as most of the materials and components come from overseas. The concern about supply chain would be even more of a concern as more lithium ion systems will be installed in the renewable grid. By 2025, it is estimated that 3.5 million used PEVs may be retiring worldwide with commutative capacity of around 150 GWh. The question is what the is best way to deal with these batteries: recycle them right away for re-introduction of valuable materials into the battery supply chain or reused and then recycle them. These batteries usually have between 70-80% of their original capacity and studies have shown second use of these batteries are technically and environmentally – the question has been the economic viability. Most of LIBs has been going into the growing electric vehicle market. Rather than using new LIBs in the future grid, the second-life batteries is a significant resource and could alleviate supply chain issues.

47 OTHER INSTRUMENTATION↗

Task 12 PV Sustainability - Mineral Resource Use Footprints of Residential PV Systems

Resource use intensity is often mentioned as one of the main characteristics of PV systems and PV electricity. Recently, the International Energy Agency published a report on the role of critical minerals in clean energy transitions. The Product Environmental Footprint pilot study on PV electricity quantified (among other environmental impacts) its abiotic depletion potential. So far, a comprehensive assessment of resource use impacts highlighting the different facets of its impacts is however lacking. For the first time, the resource use impacts of PV electricity are quantified simultaneously with four impact category indicators recommended or suggested by the Life Cycle Initiative hosted at UN Environment. The indicators cover distinctly different aspects of resource use, namely resource depletion with the Abiotic Depletion Potential, ultimate reserves (ADP UR ), economic resource scarcity with the Abiotic Depletion Potential, economic reserves (ADP ER ), resource quality with the Surplus Ore Potential, Ultimate Recoverable Resources (SOP URR ) and re-source criticality with the ESSENZ method. The resource use impacts caused from the generation of 1 kWh electricity with a residential scale photovoltaic (PV) system installed in Central Europe using mono- and multi-crystalline silicon panels and CdTe panels, respectively are quantified. The product system includes manufacture, use and end of life treatment (take back and recycling) of the PV panels, cabling, inverter and supporting structure, the supply chains of the raw materials and energy used in PV panel and inverter manufacture as well as transport logistics.

14 SOLAR ENERGY↗

Techno-Economic Impact of a Smart Battery Sorting System

Create analytical framework to capture costs and benefits of the automated sorting into battery recycling including the development and deployment of various types of battery recycling technologies such as pyrometallurgical, hydrometallurgical, and direct recycling. Li Industries, Inc. is a Virginia startup company focused on reinventing how lithium-ion batteries (LIBs) are recycled. Li Industries is focused on developing direct LIB recycling and automated battery sorting technologies in order to reduce the environmental impact of the LIB lifecycle. This work is to be conducted in support of the American-Made Challenges Lithium-Ion Battery Recycling Prize. Li Industries and NREL will work together to understand how novel technologies, such as those being developed by Li Industries, can impact the development and economics of the battery recycling industry. This voucher is being used to evaluate the profitability of an automated sorting system developed by Li Industries and the potential effect this increased value could have on the domestic lithium-ion battery (LIB) recycling industries in the United States. NREL has developed the Lithium-Ion Battery Resources Assessment (LIBRA) system dynamics model to project the future viability of the US LIB manufacturing and recycling industries under varying technoeconomic conditions and battery adoption scenarios over the coming decades. Additional logic was added to LIBRA to analyze the role automated sorting of recycling feedstock could play in the buildout of the industry and the impacts it has on the recovery of end-of-life (EOL) battery materials. This report summarizes the outcomes of this modeling analysis in the US context through a series of sensitivity analyses run for a range of values of a given input dimension and compared across the unsorted or automated sorting cases for LIB recycling feedstock. For greater detail on the process and analysis, the researchers are publishing a forthcoming journal article titled Techno-Economic Impact of a Smart Battery Sorting System for Lithium-Ion Battery Recycling and Mineral Recovery in the United States by Weigl, et al. In the event the article is not accepted by any currently seeking publication in academic or industry journal, it may be published by NREL. CRADA benefit to DOE, Participant, and US Taxpayer: assists laboratory in achieving programmatic scope competencies, uses the laboratory's core competencies.

25 ENERGY STORAGE↗

TRACER-Uncrewed Aircraft System (TRACER-UAS) Field Campaign Report

Convective processes drive the development of clouds across a variety of scales, thereby playing a central role in governing weather and climate globally. These processes help to set the stage for circulations that redistribute heat and moisture throughout the lower atmosphere, and simultaneously develop storms that supply precipitation to regions that depend on such rain events for supporting a variety of societal needs. At the same time, extreme precipitation events can result in localized flooding of low-lying areas, posing hazards to transportation and regional inhabitants, and potentially damaging structures and infrastructure. As a result, there is an inherent need to better understand the drivers and modulators of clouds and precipitation and leverage such understanding to make projections of how these important systems may evolve with a changing climate. With nearly three billion of Earth’s human inhabitants living within 200 km of a shoreline, development of such understanding is particularly important in coastal regimes. Central drivers of convective cloud development and life cycle in coastal environments include synoptic forcing, local meso- and microscale circulation regimes, microphysical evolution, and aerosol properties. Atmospheric boundary layer (ABL) development and its evolution can help drive the formation and organization of convective clouds, which then impart their own controls through dynamic processes related to latent heating and cooling (including cold-pool formation and propagation), three-dimensional radiative effects, and background environmental conditions (Fan et al. 2016). Such clouds have been contributing to record precipitation events in southeast Texas in recent years, relative to the last several decades of data from regional precipitation gauges (Fagnant et al. 2020). The greater Houston urban area has experienced particularly large increases in the frequency of extreme rainfall events, with enhanced intensity of extreme events (stretching of distribution tails) having potentially significant implications for watershed floodplain planning and mapping in greater Houston and Harris County. While the most extreme precipitation events were associated with tropical cyclones (e.g., Tropical Storm Allison and Hurricane Harvey; Blood 2014, Kao et al. 2019), strong thunderstorms can also deliver large amounts of precipitation over the area over relatively short periods.

54 ENVIRONMENTAL SCIENCES↗

Controversy and consensus: common ground and best practices for life cycle assessment of emerging technologies

This manuscript explores six controversial topics regarding LCA of emerging technologies: (1) appropriate use of LCA, (2) uncertainty assessment, (3) comparison with incumbents, (4) adopting standards, (5) system scale-up, and (6) stakeholder engagement. These topics encompass key issues vigorously debated during a series of workshop-style discussions convened by the LCA of Emerging Technologies Research Network (currently hosted by ACLCA). This paper represents the main points of support and opposition for a declarative resolution representing each topic, along with points of consensus, held amongst research network of LCA practitioners and experts. These debates and associated open questions are intended to build awareness amongst practitioners and decision-makers of the common challenges associated with assessing emerging technologies, while fostering evidence-based and context-informed discussions that are both transparent and impactful for the broader community.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Optimizing the Design of Diatom Biosilica-Targeted Fusion Proteins in Biosensor Construction for Bacillus anthracis Detection

In vivo functionalization of diatom biosilica frustules by genetic manipulation requires careful consideration of the overall structure and function of complex fusion proteins. Although we previously had transformed Thalassiosira pseudonana with constructs containing a single domain antibody (sdAb) raised against the Bacillus anthracis Sterne strain, which detected an epitope of the surface layer protein EA1 accessible in lysed spores, we initially were unsuccessful with constructs encoding a similar sdAb that detected an epitope of EA1 accessible in intact spores and vegetative cells. This discrepancy limited the usefulness of the system as an environmental biosensor for B. anthracis. We surmised that to create functional biosilica-localized biosensors with certain constructs, the biosilica targeting and protein trafficking functions of the biosilica-targeting peptide Sil3T8 had to be uncoupled. We found that retaining the ER trafficking sequence at the N-terminus and relocating the Sil3T8 targeting peptide to the C-terminus of the fusion protein resulted in successful detection of EA1 with both sdAbs. Homology modeling of antigen binding by the two sdAbs supported the hypothesis that the rescue of antigen binding in the previously dysfunctional sdAb was due to removal of steric hindrances between the antigen binding loops and the diatom biosilica for that particular sdAb.

59 BASIC BIOLOGICAL SCIENCES↗

Flexible Plant Operation and Generation Technical Program Plan for FY2023

This report presents the Technical Program Plan for Fiscal Years 2023-2027 (FY2023 to FY2027) for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability Program—Flexible Plant Operation and Generation Research Pathway. The objective of this pathway is to carry out the research needed to help nuclear power plants diversify revenue generation for the life of these plants. The purpose of these research and development activities is two fold: (1) to reduce the technical and economic risks of implementing FPOG applications and (2) to provide guidance on relevant safety and environmental operating license reviews, amendments, and renewals. This pathway provides a clear understanding of the benefits of nuclear energy beyond electricity markets. A detailed description of the research and development activities that have been completed and that are planned for FY2023—FY2027 are presented in this report. These activities include completing the development of analysis tools to perform technical and economic assessments of realistic market opportunities for producing secondary energy products near nuclear power plants. They also include developing and demonstrating engineering systems and control concepts to dispatch thermal and electrical power to an industrial user. Additionally, this plan includes developing guidance for addressing potential regulatory and licensing requirements. In addition, the formation, purpose, and activities of a group referred to as the Hydrogen Regulatory Research and Review Group is discussed. An overview is also provided on the potential benefits of the Infrastructure Investment and Jobs Act (IIJA) Bill that will support the commencement of Regional Clean Hydrogen Hubs, and the Inflation Reduction Act (IRA) that provides compelling production tax credits for nuclear electricity and clean hydrogen using nuclear energy.

08 HYDROGEN↗

Hybrid Capture for Net-Negative Emissions

The Energy & Environmental Research Center, in partnership with the U.S. Department of Energy and North Dakota ethanol producer Red Trail Energy, LLC (RTE), completed an initial engineering design (IED) for a potential hybrid capture system at the RTE CCS (carbon capture and storage) site. The RTE CCS Project is currently operating a CO2 capture facility, adjacent to the RTE ethanol facility in western North Dakota, and injecting the CO2 more than a mile below RTE property for permanent storage. This novel process would add capturing CO2 produced from natural gas boilers to the existing bioprocessing capture system to achieve a net-negative CO2 emissions industrial process at commercial scale (~310,000 tonnes/yr CO2). Initial findings of the IED showed the hybrid system to be technically viable with a moderate estimated cost of $55/tonne CO2 captured for the hybrid system. A cradle-to-gate life cycle assessment (LCA) was also conducted, showing preliminary net-negative carbon emissions potential anticipated from implementing a hybrid CCS system at a commercial scale. Recommended next steps toward potential implementation include hybrid capture system demonstration testing for detailed engineering and LCA model comparisons with low-carbon fuel incentive programs for financial support.

01 COAL, LIGNITE, AND PEAT↗

The SrrAB two-component system regulates Staphylococcus aureus pathogenicity through redox sensitive cysteines

Staphylococcus aureus infections can lead to diseases that range from localized skin abscess to life-threatening toxic shock syndrome. The SrrAB two-component system (TCS) is a global regulator of S. aureus virulence and critical for survival under environmental conditions such as hypoxic, oxidative, and nitrosative stress found at sites of infection. Despite the critical role of SrrAB in S. aureus pathogenicity, the mechanism by which the SrrAB TCS senses and responds to these environmental signals remains unknown. Bioinformatics analysis showed that the SrrB histidine kinase contains several domains, including an extracellular Cache domain and a cytoplasmic HAMP-PAS-DHp-CA region. In this work, we show that the PAS domain regulates both kinase and phosphatase enzyme activity of SrrB and present the structure of the DHp-CA catalytic core. Importantly, this structure shows a unique intramolecular cysteine disulfide bond in the ATP-binding domain that significantly affects autophosphorylation kinetics. In vitro data show that the redox state of the disulfide bond affects S. aureus biofilm formation and toxic shock syndrome toxin-1 production. Moreover, with the use of the rabbit infective endocarditis model, we demonstrate that the disulfide bond is a critical regulatory element of SrrB function during S. aureus infection. Our data support a model whereby the disulfide bond and PAS domain of SrrB sense and respond to the cellular redox environment to regulate S. aureus survival and pathogenesis.

59 BASIC BIOLOGICAL SCIENCES↗

Development of the ARM Lagrangian Large-Scale Forcing Data (ARMLAGTRAJ) Value-Added Product Based on the lagtraj Framework

The Atmospheric Radiation Measurement (ARM) large-scale forcing data developed based on the constrained variational analysis (VARANAL) value-added product (VAP) (Zhang and Lin 1997, Zhang et al. 2001, Xie et al. 2004, Tang et al. 2019) has been widely used for single-column models (SCMs), cloud-resolving models (CRMs), and large-eddy simulation models (LESs) to understand and improve physical processes in models. Recently, the U.S. Department of Energy (DOE) ARM user facility conducted several major field campaigns using ship-based moving observational platforms. For example, the Marine ARM GPCI Investigation of Clouds (MAGIC) field campaign focused on the role of subtropical marine-boundary layer (MBL) clouds, and the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) field campaign aimed to improve understanding of the coupled climate systems in the Arctic. Observations from moving platforms are critical to provide a comprehensive characterization of coupled-system processes associated with all stages of the cloud and/or sea-ice life cycle. Traditional ARM large-scale forcing data have been developed at fixed locations. They need to be extended to include these moving platforms to address data needs for ship-based field campaigns or to support LES modeling in a Lagrangian framework. With these considerations in mind, we develop ARM-type Lagrangian large-scale forcing data sets based on the lagtraj framework (Boeing et al. 2020) with notable enhancements in generating forcings that are more suitable for ARM field campaigns. The lagtraj is a novel tool that generates forcings for LES and SCM simulation in both Lagrangian and Eulerian perspective. This technical report focuses on the major changes we performed on the lagtraj algorithm and provides an overview of the ARM Lagrangian Large-Scale Forcing Data (ARMLAGTRAJ) value-added products.

54 ENVIRONMENTAL SCIENCES↗

Use Attainability Analysis for Upper Sandia Canyon

This document presents a use attainability analysis (UAA) for the perennial segment of Upper Sandia Canyon, which is located within the Los Alamos National Laboratory (LANL) property near Los Alamos, New Mexico.1 This UAA is consistent with 20.6.4.15 New Mexico Administrative Code (NMAC) (New Mexico Environment Department [NMED] 2011c), which describes the perennial segment as “Sandia Canyon from Sigma Canyon upstream to LANL [National Pollutant Discharge Elimination System] NPDES outfall 001.” The perennial segment’s designated uses are coldwater aquatic life, livestock watering, wildlife habitat, and secondary contact. 40 Code of Federal Regulations (CFR) § 131.10(g) permits a state to remove a designated use that is not an existing use (as defined in 40 CFR §131.3), if a UAA demonstrates that naturally occurring pollutant concentrations prevent the attainment of the use or if physical conditions related to the natural features of the water body preclude the attainment of the aquatic life protection use. This UAA considers whether natural physical conditions in Upper Sandia Canyon, specifically air and/or water temperatures, prevent the designated aquatic life use water temperature limits (i.e., coldwater) from being attained in the perennial segment. The weight of evidence presented in this UAA supports the conclusion that, based on air-water temperature modeling and instream thermograph data, the coolwater aquatic life designated use is currently the attainable use. Accordingly, it is recommended that the coolwater aquatic life designated use replace the coldwater aquatic life designated use in the Upper Sandia Canyon assessment unit (AU).

54 ENVIRONMENTAL SCIENCES↗

Tracing U.S. fuel life-cycle greenhouse gas emissions in a multi-sector dynamics model using LC-GCAM

Model-based analysis of fuel pathways is essential for informing energy and environmental policy. Two major model types are typically used: multi-sector dynamics models, which capture the broader energy-economy, such as GCAM (Global Change Analysis Model), and life cycle assessment models, such as GREET (Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation). Each has distinct strengths and limitations, and recent studies increasingly adopt hybrid approaches to harness the advantages of both. However, such integration is often time-consuming and complicated by inconsistencies in system boundaries and technology definitions. We present LC-GCAM, a new tool that enables estimation of life-cycle greenhouse gas emissions and primary energy use for any fuel pathway represented in GCAM. We apply LC-GCAM to 300 scenarios designed to explore key uncertainties affecting the life-cycle performance of future fuel options in the U.S. freight sector. To evaluate LC-GCAM, we compare its results with those from GREET for nine fuel types in a 2030 reference scenario. When input assumptions are modestly aligned, LC-GCAM and GREET estimates typically agree within 10% (absolute sum-based mean absolute percentage error). LC-GCAM offers a flexible and efficient approach to generating life-cycle metrics within an integrated modeling framework, supporting robust policy analysis across a wide range of interacting energy system uncertainties.

Wolfram, Paul↗

Green Methanol via an Integrated Direct Air Capture, CO 2 Electrolyzer, and Hydrogenation Reactor

This project pioneered a groundbreaking reactor design to produce green methanol by harnessing the electrochemical CO 2 reduction reaction (eCO 2 RR), a cornerstone of power-to-fuels technology. The effort integrated three innovative technologies to achieve carbon-neutral methanol production at a target cost of under $\$$800/ton: 1. Direct Air Capture (DAC): Using a cutting-edge sorbent material developed at Holocene, scalable models were developed to integrate captured atmospheric CO₂ into the reactor system. 2. Intermediate-Temperature CO 2 Electrolyzer: Developed by the University of Tennessee (UTK), this electrolyzer utilizes a cost-effective, proton-conducting solid acid electrolyte (CsH 2 PO 4 , CDP) and a mixed-metal oxide cathode. It achieves high faradaic efficiencies (>98%) by effectively suppressing hydrogen evolution at high current densities, converting CO 2 to CO with remarkable selectivity. 3. Catalysis and Reactor Engineering: Oak Ridge National Laboratory (ORNL) contributed world-class expertise in heterogeneous catalysis and reactor design. Their advanced ASPEN modeling drove systems integration and supported techno-economic and life cycle analyses. This effort was further bolstered by partnerships with industry leaders Air Company and Plug Power, who provided critical guidance on scaling, systems engineering, and the integration of water electrolyzers into large-scale operations. During Phase 1, the team focused on modeling and validating a lab-scale reactor demonstrating the feasibility of the integrated approach. Key accomplishments include a 52% increase in current density at 0.8 V while maintaining >98% CO faradaic efficiency, successful 10× scale-up of the electrolyzer with performance within 5% of coin-cell results, best-in-class durability (168-hour test at 0.6 V with 0.14 mA/cm 2 -h degradation), validated TEA confirming the $\$$800/ton methanol target, and completed preliminary LCA showing potential for net-negative GHG emissions under renewable energy scenarios.

10 SYNTHETIC FUELS↗

DOE Plasma Science Center - Predictive Control of Plasma Kinetics: Multi-Phase and Bounded Systems (Final Report DE-SC0001939)

Low temperature plasmas (LTPs) are the plasmas of electron-volt (eV) physics and eV technologies. LTPs have characteristic electron temperatures of a few eV and fractional ionizations that are typically small. Since LTPs have electron temperatures commensurate with the threshold energies of excited states in neutral atoms and molecules, power transfer from electrons to these atoms and molecules efficiently produces activated species (e.g., radicals, excited states, photons). Acceleration of ions in the sheaths of LTPs to energies of tens to hundreds of eV enable activation of surface modifying processes – sputtering, etching, deposition. With such properties, LTPs are often and beneficially used in technological devices, ranging from etching and deposition in microelectronics and solar cell fabrication, to hardening of surgical instruments. LTPs harbor fundamental science issues that are intellectually challenging and rewarding. At the same time, there are enormous societal benefits that are enabled by LTPs. The entire present-day and future information technology infrastructure owes its very existence to LTPs. Renewable energy sources, such as solar cell arrays, could not be economically produced in the absence of deposition and etching by LTPs. In acknowledgment of the importance of LTPs, the DOE Office of Fusion Energy Sciences supported the Plasma Science Center for Predictive Control of Plasma Kinetics: Multi-Phase and Bounded Systems from August 2009 to July 2021, consisting of an initial 5-year grant, 3 funded extensions and 2 no-cost extensions. This is the final report of the Center in which the productivity of the Center is discussed in terms of publications, impact and personnel. High-lights of the research performed in the Center are provided.

36 MATERIALS SCIENCE↗

The field of human building interaction for convergent research and innovation for intelligent built environments

Human-Building Interaction (HBI) is a convergent field that represents the growing complexities of the dynamic interplay between human experience and intelligence within built environments. This paper provides core definitions, research dimensions, and an overall vision for the future of HBI as developed through consensus among 25 interdisciplinary experts in a series of facilitated workshops. Three primary areas contribute to and require attention in HBI research: humans (human experiences, performance, and well-being), buildings (building design and operations), and technologies (sensing, inference, and awareness). Three critical interdisciplinary research domains intersect these areas: control systems and decision making, trust and collaboration, and modeling and simulation. Finally, at the core, it is vital for HBI research to center on and support equity, privacy, and sustainability. Compelling research questions are posed for each primary area, research domain, and core principle. State-of-the-art methods used in HBI studies are discussed, and examples of original research are offered to illustrate opportunities for the advancement of HBI research.

42 ENGINEERING↗