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This poster, presented at the 2019 Advanced Manufacturing Office Peer Review Meeting, outlines opportunities, trends and technoeconomic analysis related to sustainable manufacturing.
This poster, presented at the 2019 Advanced Manufacturing Office Peer Review Meeting, outlines opportunities, trends and technoeconomic analysis related to sustainable manufacturing and recycling.
This poster, presented at the U.S. Department of Energy Advanced Manufacturing Office Peer Review Meeting in June 2019, discusses sustainable manufacturing opportunities, trends, and technoeconomic analysis.
C2C provides support to communities at any stage of their clean energy transition through three distinct offerings: in-depth partnerships, peer-learning cohorts, and expert match. This 2023 annual highlights report looks at the program's accomplishments since it launched in January 2023.
The Energy to Communities (E2C) program provides innovative, cross-cutting technical analysis to support community-level efforts to secure abundant, reliable, and affordable energy systems. E2C provides three pathways for assistance: in-depth partnerships, peer-learning cohorts, and expert match. E2C is managed by the National Renewable Energy Laboratory with support from Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, and Pacific Northwest National Laboratory.
Importance Opioid-related overdose accounts for almost 80 000 deaths annually across the US. People who use drugs leaving jails are at particularly high risk for opioid-related overdose and may benefit from take-home naloxone (THN) distribution. Objective To estimate the population impact of THN distribution at jail release to reverse opioid-related overdose among people with opioid use disorders. Design, Setting, and Participants This study developed the agent-based Justice-Community Circulation Model (JCCM) to model a synthetic population of individuals with and without a history of opioid use. Epidemiological data from 2014 to 2020 for Cook County, Illinois, were used to identify parameters pertinent to the synthetic population. Twenty-seven experimental scenarios were examined to capture diverse strategies of THN distribution and use. Sensitivity analysis was performed to identify critical mediating and moderating variables associated with population impact and a proxy metric for cost-effectiveness (ie, the direct costs of THN kits distributed per death averted). Data were analyzed between February 2022 and March 2024. Intervention Modeled interventions included 3 THN distribution channels: community facilities and practitioners; jail, at release; and social network or peers of persons released from jail. Main Outcomes and Measures The primary outcome was the percentage of opioid-related overdose deaths averted with THN in the modeled population relative to a baseline scenario with no intervention. Results Take-home naloxone distribution at jail release had the highest median (IQR) percentage of averted deaths at 11.70% (6.57%-15.75%). The probability of bystander presence at an opioid overdose showed the greatest proportional contribution (27.15%) to the variance in deaths averted in persons released from jail. The estimated costs of distributed THN kits were less than $\$$15 000 per averted death in all 27 scenarios. Conclusions and Relevance This study found that THN distribution at jail release is an economical and feasible approach to substantially reducing opioid-related overdose mortality. Training and preparation of proficient and willing bystanders are central factors in reaching the full potential of this intervention.
Following the 1st release of the "Emerging photovoltaic (PV) reports", the best achievements in the performance of emerging photovoltaic devices in diverse emerging photovoltaic research subjects are summarized, as reported in peer-reviewed articles in academic journals since August 2020. Updated graphs, tables, and analyses are provided with several performance parameters, e.g., power conversion efficiency, open-circuit voltage, short-circuit current density, fill factor, light utilization efficiency, and stability test energy yield. These parameters are presented as a function of the photovoltaic bandgap energy and the average visible transmittance for each technology and application and are put into perspective using, e.g., the detailed balance efficiency limit. The 2nd installment of the "Emerging PV reports" extends the scope toward tandem solar cells and presents the current state-of-the-art in tandem solar cell performance for various material combinations.
Abstract Following the 2nd release of the “Emerging PV reports,” the best achievements in the performance of emerging photovoltaic devices in diverse emerging photovoltaic research subjects are summarized, as reported in peer‐reviewed articles in academic journals since August 2021. Updated graphs, tables, and analyses are provided with several performance parameters, e.g., power conversion efficiency, open‐circuit voltage, short‐circuit current density, fill factor, light utilization efficiency, and stability test energy yield. These parameters are presented as a function of the photovoltaic bandgap energy and the average visible transmittance for each technology and application, and are put into perspective using, e.g., the detailed balance efficiency limit. The 3rd installment of the “Emerging PV reports” extends the scope toward triple junction solar cells.
Abstract By influencing soil organic carbon (SOC), cover crops play a key role in shaping soil health and hence the system's long‐term sustainability. However, the magnitude by which cover crops impacts SOC depends on multiple factors, including soil type, climate, crop rotation, tillage type, cover crop growth, and years under management. To elucidate how these multiple factors influence the relative impact of cover crops on SOC, we conducted a meta‐analysis on the impacts of cover crops within rotations that included corn ( Zea mays L.) on SOC accumulation. Information on climatic conditions, soil characteristics, management, and cover crop performance was extracted, resulting in 198 paired comparisons from 61 peer‐reviewed studies. Over the course of each study, cover crops on average increased SOC by 7.3% (95% CI, 4.9%–9.6%). Furthermore, the impact of cover crop–induced increases in percent change SOC was evaluated across soil textures, cover crop types, crop rotations, biomass amounts, cover crop durations, tillage practices, and climatic zones. Our results suggest that current cover crop–based corn production systems are sequestering 5.5 million Mg of SOC per year in the United States and have the potential to sequester 175 million Mg SOC per year globally. These findings can be used to improve carbon footprint calculations and develop science‐based policy recommendations. Taken altogether, cover cropping is a promising strategy to sequester atmospheric C and hence make corn production systems more resilient to changing climates.
Abstract The novel electrophilic organo‐tantalum catalyst AlS/TaNp x ( 1 ) (Np=neopentyl) is prepared by chemisorption of the alkylidene Np 3 Ta=CH t Bu onto highly Brønsted acidic sulfated alumina (AlS). The proposed catalyst structure is supported by EXAFS, XANES, ICP, DRIFTS, elemental analysis, and SSNMR measurements and is in good agreement with DFT analysis. Catalyst 1 is highly effective for the hydrogenolysis of diverse linear and branched hydrocarbons, ranging from C2 to polyolefins. To the best of our knowledge, 1 exhibits one of the highest polyolefin hydrogenolysis activities (9,800 (CH 2 units) ⋅ mol(Ta) −1 ⋅ h −1 at 200 °C/17 atm H 2 ) reported to date in the peer‐reviewed literature. Unlike the AlS/ZrNp 2 analog, the Ta catalyst is more thermally stable and offers multiple potential C−C bond activation pathways. For hydrogenolysis, AlS/TaNp x is effective for a wide variety of pre‐ and post‐consumer polyolefin plastics and is not significantly deactivated by standard polyolefin additives at typical industrial concentrations.
The novel electrophilic organo-tantalum catalyst AlS/TaNp x (1) (Np=neopentyl) is prepared by chemisorption of the alkylidene Np 3 Ta=CH t Bu onto highly Brønsted acidic sulfated alumina (AlS). Here, the proposed catalyst structure is supported by EXAFS, XANES, ICP, DRIFTS, elemental analysis, and SSNMR measurements and is in good agreement with DFT analysis. Catalyst 1 is highly effective for the hydrogenolysis of diverse linear and branched hydrocarbons, ranging from C2 to polyolefins. To the best of our knowledge, 1 exhibits one of the highest polyolefin hydrogenolysis activities (9,800 (CH 2 units) ⋅ mol(Ta) −1 ⋅ h −1 at 200 °C/17 atm H 2 ) reported to date in the peer-reviewed literature. Unlike the AlS/ZrNp 2 analog, the Ta catalyst is more thermally stable and offers multiple potential C−C bond activation pathways. For hydrogenolysis, AlS/TaNp x is effective for a wide variety of pre- and post-consumer polyolefin plastics and is not significantly deactivated by standard polyolefin additives at typical industrial concentrations.
Abstract In this Review, recent advances in the development of organic bipolar redox‐active molecules (BRMs) for redox‐flow batteries (RFBs) are discussed, with special emphasis on their utilization in non‐aqueous systems. BRMs are single molecules that can be used as both anolyte and catholyte. Their unique redox chemistry enables identical components to be present in RFBs, which has distinct advantages in storage, mitigating crossover and compound degradation. Recent scientific innovations have uncovered three main strategies in preparing these bipolar species: developing stable radicals that are capable of both positive and negative redox reactions, covalently bridging electron donor‐acceptor motifs on one single molecule, and forming biredox eutectic mixtures through physically mixing active components. These approaches not only enabled symmetric flow battery design, but also resulted in electroactive materials with improved properties such as solubility, stability, and cell voltage. Nevertheless, much is still to be done. Importantly, developing BRMs that are competitive with vanadium RFBs in all performance indicators (e. g. solubility >1.0 M, voltage output >2.0 V, and cycling longevity >10 000 cycles) remains a challenge. Mechanistic studies including molecular dynamics, plausible degradation processes, and electrode/solution interface are necessary to peer into key parameters that dominate their battery performance. Accordingly, we review the current status and suggest future opportunities in these areas.
Lithium metal batteries (LMBs) enable much higher energy density than lithium–ion batteries (LIBs) and thus hold great promise for future transportation electrification. However, the adoption of lithium metal (Li) as an anode poses serious concerns about cell safety and performance, which has been hindering LMBs from commercialization. To this end, extensive effort has been invested in understanding the underlying mechanisms theoretically and experimentally and developing technical solutions. In this review, we devote to providing a comprehensive review of the challenges, characterizations, and interfacial engineering of Li anodes in both liquid and solid LMBs. Finally, we expect that this work will stimulate new efforts and help peer researchers find new solutions for the commercialization of LMBs.
This paper by the Energy & Environmental Research Center presents a workflow and modeling approach for delineating a risk-based area of review (AOR) to support a U.S. Environmental Protection Agency (EPA) Class VI permit for a carbon dioxide (CO 2 ) storage project. The approach combines semianalytical solutions for estimating formation fluid leakage through a hypothetical leaky wellbore with the results of numerical reservoir simulations to define the AOR. The modeling utilizes 1) semianalytical solutions from the peer-reviewed literature for formation fluid leakage through abandoned wellbores by Raven (1990) and Avci (1994), 2) a FORTRAN model compiled and described in Cihan et al. (2011, 2012) called ASLMA (Analytical Solution for Leakage in Multilayered Aquifers), and 3) a computational framework for estimating a risk-based AOR first proposed by Oldenburg et al. (2014, 2016). Therefore, the approach builds upon well-established research and underlying hydrogeological principles that have been upheld for nearly three decades. Moreover, the ASLMA model has been broadly applied to an array of storage projects. The work presented herein extends these earlier works using a custom wrapper written in the software environment, R (R Core Team, 2020), which was developed to perform multiple runs of the ASLMA model using given ranges for one or more input parameters. In addition, the current work simulates the pressure buildup within the storage reservoir in response to CO 2 injection using a compositional simulator to better accommodate the temporospatial evolution of pressure buildup within the storage reservoir that is more accurately modeled using a heterogeneous geologic model and a compositional simulator that accounts for the multiphase interactions. The workflow is demonstrated using a case study for a 180,000-metric-ton-per-year storage project located in the PCOR (Plains CO 2 Reduction) Partnership region. For the storage project evaluated here, under the scenario where the leaky wellbore is open to a saline aquifer (thief zone) between the overlying seal (cap rock) and the underground sources of drinking water (USDW), the risk-based AOR essentially collapses to the areal extent of the CO 2 plume in the storage reservoir because the pressure buildup in the storage reservoir beyond the CO 2 plume is insufficient to drive formation fluids up a hypothetical leaky wellbore into the USDW. However, even under the conservative assumption that the leaky wellbore is not open to a thief zone, beyond the areal extent of the CO 2 plume, the incremental leakage is less than 400 m 3 over 20 years, which represents ~0.0001% or less of the total volume of water contained within the USDW rock volume. As discussed in the text, the threshold criterion for defining the risk-based AOR is site-specific and should be informed by the results of the sensitivity analysis and available site characterization data. The approach outlined in this paper is designed to be protective of USDWs and, therefore, comply with the Safe Drinking Water Act requirements and provisions for the U.S. EPA Class VI Underground Injection Control (UIC) Program (Class VI Rule) and North Dakota Administrative Code Chapter 43-05-01.
Abstract We reviewed studies of piscivorous colonial waterbird predation on juvenile salmonids to synthesize current knowledge of factors affecting fish susceptibility to avian predators. Specifically, we examined peer-reviewed publications and reports from academic, governmental, and nongovernmental agencies to identify commonalities and differences in susceptibility of salmonids to avian predation, with a focus on mark–recovery studies in the Columbia River basin. Factors hypothesized to influence salmonid susceptibility to avian predation were grouped into four general categories: (1) salmonid species and populations, (2) environmental factors, (3) prey density, predator density, and migration timing, and (4) prey characteristics. Our review focused on predation by Caspian terns Hydroprogne caspia, double-crested cormorants Nannopterum auritum, and gull species Larus spp. as these are the most well-studied avian predators of salmonids. Results indicated that predator–prey interactions varied across salmonid species and populations and species of avian predator. Inferences across studies supported multiple hypotheses regarding predator–prey dynamics, including environmental factors that influence prey exposure to predators (e.g., river flows, turbidity, alternative prey), variation in predator and prey abundances, predator characteristics (e.g., foraging behavior, colony location), and prey characteristics (e.g., fish length, condition). Mark–recovery studies of avian predation on fish populations have greatly improved our understanding of the factors affecting fish susceptibility to avian predation, the relative contributions of abiotic and biotic factors to predation susceptibility, and the extent to which avian predation affects fish survival and the viability of prey populations. Future studies that jointly model predation and survival and the factors affecting those processes will further broaden our understanding of predator–prey dynamics and directly evaluate the effects of predation on prey population dynamics.
The concept of soil health has evolved over the past several decades, recognizing that dynamic soil property response to management and land use is highly dependent on site-specific factors that must be considered when interpreting soil health measurements. Initially, the Soil Management Assessment Framework (SMAF) and Comprehensive Assessment of Soil Health (CASH) were developed and used globally for scoring soil health indicators. However, both SMAF and CASH frameworks were developed using a relatively small dataset and their interpretation curves were not validated at the nationwide scale. Expanding upon these concepts, we propose the Soil Health Assessment Protocol and Evaluation (SHAPE) tool. The SHAPE was developed using 14,680 soil organic C (SOC) observations from across the United States, and accounts for edaphic and climate factors at the continental scale. Data were compiled from the literature, the Cornell Soil Health Laboratory, and the Kellogg Soil Survey Laboratory. In this approach, scoring curves are Bayesian model-based estimates of the conditional cumulative distribution function (CDF) for defined soil peer groups reflecting five soil texture and five soil suborder classes adjusted for mean annual temperature and precipitation. Specifically, SHAPE produces scores between 0 and 1 (0–100%) for measured SOC values that reflect the quantile or position within the conditional CDF along with measures of uncertainty. Herein, we focus on development of the SHAPE scoring curve for SOC with our case studies. SHAPE is a flexible, quantitative tool that provides a regionally relevant interpretation of this key soil health indicator.
Workforce planning deals with determining the number of employees and associated skills necessary to meet the future operational needs of an organization. A workforce system consists of six elements: recruitment, attrition, promotion, training, retention, and scheduling. Historically, several workforce modeling and analysis methodologies have been developed to capture these elements. This paper reviews the results of workforce and manpower models published within peer-reviewed literature between 1959 and 2021 to provide an in-depth analysis of current models. The focus of this review is on analytical, simulation, and empirical models found in literature that were collected based on a citation requirement and keyword search criteria. Results demonstrate the trends in workforce modeling research and discuss the common uses of each model type and the advantages/disadvantages related to each model. Based on the common attributes of workforce systems, the discussion focuses on the most frequently used model type for each element and the best use for each model. Lastly, recommendations are made for the development of workforce models that allow the most comprehensive view of the workforce systems of the future.
Abstract It was last estimated that in 2020, data centers comprised approximately 2% of total US electricity consumption, with an estimated annual growth rate of 4%. As our country increasingly relies on information technology (IT), our data centers (DCs) will need to increase their energy efficiency (EE) to stabilize their energy consumption. The task of studying EE in DCs is complicated by the interconnected nature of humans and mission-critical technical systems. Moreover, the literature tends to focus on technology solutions such as improvements to IT equipment, cooling infrastructure, and software, without addressing organizational and psychological drivers. Our research demystifies the complex interactions between humans and DCs, by asking What non-technical barriers impede EE investment decision-making and/or implementing energy management strategies? To begin to answer this question, we perform a literature review of 86 resources, ranging from peer-reviewed journal publications to handbooks. We also consider related fields such as organizational behavioral management and energy intensive buildings. We develop a public Zotero library, perform content coding, and complete a rudimentary network analysis. Our findings from the literature review suggest that (1) technological solutions are abundant in the literature but fall short of providing practical guidance on the pitfalls of implementation, (2) making energy efficiency a priority at the executive level of organizations will be largely ineffective if the IT and facilities staff are not directly incentivized to increase EE, and (3) there is minimal current understanding of how the individual psychologies of IT and facilities staff affect EE implementation in DCs. In the next phase of our research, we plan to interview data center operators/experts to ground-truth our literature findings and collaboratively design decarbonization policy solutions that target organizational structure, empower individual staff, and foster a supportive external market.