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DOE OSTI2023

Probabilistic feasibility assessment of sequestration reliance for climate targets

Countries worldwide are transforming their energy systems to achieve Carbon-Neutrality. Investing in renewable resources-based technologies and implementing Carbon Capture and Storage (CCS) are common strategies to achieve higher sequestration levels. Negative emissions through Bioenergy with CCS are expected to play an essential role in the transition to full decarbonization. On top of that, biomass is a limited resource that depends on environmental factors, which create uncertainties related to the amount that can be sustainably provided to the energy system. Here this study emphasizes the relevance of variability in carbon sequestration for achieving climate targets by 2050. Here this paper proposes a probabilistic approach that integrates the Global Change Analysis Model for Latin America (GCAM-LA) with a chance constraint approach. GCAM-LA is used to assess the impact on the energy sector of different limits of sustainable biomass and carbon budget scenarios. The risk associated with exceeding the sequestration capacity of a given region is modeled via Chance Constraint. Results show that electrification is an appropriate long-term decarbonization strategy. It smoothes the effects of uncertainty in sequestration capacity and responds to end-user demands. For this case study, higher levels of electrification are obtained at likelihood levels >66% for end-use sectors.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Developing and Demonstrating a Lab Method for Quantifying Hair Exposure to Environmental Tobacco Smoke with a Forensic Perspective

Forensic science and chemistry curricula often lack hands-on experimental designs that effectively simulate the impact of environmental tobacco smoke (ETS) or other common elements found at crime scenes, such as marijuana, on trace forensic evidence. Hair, a critical form of trace evidence, offers unique advantages for assessing long-term exposure to environmental pollutants, including ETS. This study presents a novel, noninvasive forensic laboratory module designed to evaluate ETS exposure on various human hair types (untreated, dyed, and bleached). The experimental procedure involved controlled cigarette smoke exposure, followed by analysis using UV−visible spectroscopy, FTIR spectroscopy, and zeta potential measurements. Thirteen students participated in the three-week lab module (three sessions per week). Pre- and postlab assessments were conducted to evaluate learning outcomes. The prelab assessment focused on baseline knowledge of forensic hair analysis, as well as student expectations and confidence. The postlab assessment evaluated knowledge gained, technical insights, application of techniques, self-reflection, conceptual understanding, and practical skill development. This design helped students comprehend the effects of chemical treatments that significantly influence hair’s capacity to adsorb ETS residues by altering its physical and chemical properties. Integration of this experiment into the forensic chemistry curriculum led to measurable gains in student understanding, technical competency, and appreciation for realworld forensic applications. This method offers a valuable teaching and investigative tool for assessing individual ETS exposure in forensic contexts.

FTIR↗

DOE OSTI2022

Drivers of Future Physical Water Scarcity and Its Economic Impacts in Latin America and the Caribbean

Future water scarcity is a global concern with significant impacts on the energy, water, and land (EWL) sectors. Countries in Latin America and the Caribbean (LAC) are significant producers of agricultural goods consumed around the world, so disruptions resulting from land and water scarcity in LAC are a source of global supply chain risk. Understanding where water scarcity in LAC could occur and what could drive that scarcity to emerge is critical for strategic resource management and planning, both regionally and globally. Assessing future water scarcity impacts in LAC is challenging given the multisector dynamic interactions among the EWL sectors and the multiple uncertainties acting across different spatial scales. We use scenario discovery to explore the drivers of future water scarcity, considering assumptions related to climate, socioeconomics, and the EWL sectors. Understanding what factors drive uncertainty across outcomes can help stakeholders in targeting long-term solutions and future data collection efforts. To illuminate these dynamics, we use a database consisting of a large ensemble of scenarios representing diverse worlds simulated using the Global Change Analysis Model. We quantify future water scarcity and its economic impacts across the scenarios using three metrics: (1) physical water scarcity, (2) water price, and (3) crop profit. We find that physical water scarcity and water price are driven primarily by reservoir storage capacity assumptions, highlighting the importance of strategic water infrastructure development in maintaining future water availability and accessibility. Crop profit is driven by a combination of water supply and demand assumptions, which emphasizes the complex nature of EWL multisector dynamics. While most of LAC is poised to have abundant land and water resources available for development, water basins in Mexico and along the Pacific coast of South America experience high levels of severity and uncertainty across the future scenarios for at least one of the metrics. We find that the drivers of extreme scarcity vary spatially and across the metrics, further highlighting the heterogeneity of the region and the importance of considering multiple metrics to assess water scarcity vulnerability.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Diversification of JAZ‐MYC signaling function in immune metabolism

Summary Jasmonate (JA) re‐programs metabolism to confer resistance to diverse environmental threats. Jasmonate stimulates the degradation of JASMONATE ZIM‐DOMAIN (JAZ) proteins that repress the activity of MYC transcription factors. In Arabidopsis thaliana , MYC and JAZ are encoded by 4 and 13 genes, respectively. The extent to which expansion of the MYC and JAZ families has contributed to functional diversification of JA responses is not well understood. Here, we investigated the role of MYC and JAZ paralogs in controlling the production of defense compounds derived from aromatic amino acids (AAAs). Analysis of loss‐of‐function and dominant myc mutations identified MYC3 and MYC4 as the major regulators of JA‐induced tryptophan metabolism. We developed a JAZ family‐based, forward genetics approach to screen randomized jaz polymutants for allelic combinations that enhance tryptophan biosynthetic capacity. We found that mutants defective in all members ( JAZ1/2/5/6 ) of JAZ group I over‐accumulate AAA‐derived defense compounds, constitutively express marker genes for the JA–ethylene branch of immunity and are more resistant to necrotrophic pathogens but not insect herbivores. In defining JAZ and MYC paralogs that regulate the production of amino‐acid‐derived defense compounds, our results provide insight into the specificity of JA signaling in immunity.

jasmonate↗

DOE OSTI2024

Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications

To address the need for regularly updated wind resource data, NREL has processed the High-Resolution Rapid Refresh (HRRR) outputs for use in grid integration modeling. The HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA) (Dowell et al., 2022). Several barriers have prevented the HRRR's widespread proliferation in the wind energy industry: missing timesteps (prior to 2019), challenging file format for wind energy analysis, limited vertical height resolution, and negative bias versus legacy WIND Toolkit data (2007-2013). NREL has applied re-gridding, interpolation, and bias-correction to the native HRRR data to overcome these limitations. This results in the now-publicly-available bias corrected and interpolated HRRR (BC-HRRR) dataset for weather years 2015 to 2023. Bias correction is necessary for wind resource consistency across weather years to be used simultaneously in planning-focused grid integration studies alongside the original WIND Toolkit data. We show that quantile mapping with the WIND Toolkit as a historical baseline is an effective method for bias correcting the interpolated HRRR data: the BC-HRRR has reduced mean bias versus comparable gridded wind resource datasets (+0.12 m/s versus Vortex) and has very low mean bias versus ground measurement stations (+0.01 m/s) (Buster et al., 2024). BC-HRRR's consistency with the legacy WIND Toolkit allows NREL to extend grid integration analysis to 15+ weather years of wind data with low-overhead extensibility to future years as they are made available by NOAA. As with historical datasets like the WIND Toolkit, BC-HRRR is intended for use in grid integration modeling (e.g., capacity expansion, production cost, and resource adequacy modeling) both independently and alongside the legacy WIND Toolkit.

Array↗

DOE OSTI2021

Cabin Thermal Management Analysis for SuperTruck II Next-Generation Hybrid Electric Truck Design

In this article, we present a multistage, coupled thermal management simulation approach, informed by physical testing where available, to aid design decisions for PACCAR's SuperTruck II hybrid truck cabin concept. Focus areas include cabin insulation, battery sizing, and sleeper curtain position, as well as heating, ventilating, and air-conditioning (HVAC) component and accessory configurations, to maintain or improve thermal comfort while saving energy. The authors analyzed weather data and determined the national vehicle miles traveled weighted temperature and solar conditions for long-haul trucks. Example weather day profiles were selected to approximate the 5th and 95th percentile weighted conditions. A daylong drive cycle was developed to impose appropriate external wind conditions during rest and driving periods. Using the National Renewable Energy Laboratory's vehicle HVAC modeling and simulation tool VTCab, HVAC load design trade-off studies for the new truck geometry concept were completed. Parameters analyzed included effects of paint color, insulation, glass transmissivity, and curtain location. Simulation results helped with early design material selections for efficient cabin climate control. A detailed three-dimensional computer-aided engineering (CAE), computational fluid dynamics (CFD), radiation, and human physiology co-simulation, referred to in this article as CAE Thermal-CFD, was used to evaluate thermal comfort and energy impacts of diffuser configurations and air supply settings in driving and hoteling modes. Analysis revealed that it is more difficult to heat the cabin in hoteling mode during the winter than to cool the space in the summer. This seasonal load profile drives the requirement of additional energy storage for heating comfort. To determine the battery capacity requirement, multiday HVAC operation drive cycle simulations were then completed, showing that a 15-kWh battery would be required for HVAC operation during hoteling. Results helped reduce cabin thermal loads, determine component sizing requirements, and improve occupant comfort to save fuel and contribute to the economic viability of the hybrid system.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

Techno-Economic Analysis of Biofuel Production via Catalytic Upgrading of Carbohydrates in Paper Sludge

A full-plant model was developed using correlations from a rigorous mass and energy balance and based on experimental results to determine the MFSP and its Sensitivity Analysis in the production of a hydrocarbon product from Paper Sludge. In this base case a preliminary MFSP of $5.97/GGE has been determined. This value is higher than the results reported in recent NREL reports. The difference is explained since much larger capacity plants are considered in those reports, and because we are not considering the production of co-products that bring the fuel costs down. The obtained model is being used to guide the next steps in our laboratory work since the team is now aware of which are the more sensitive process parameters "impacting" the MFSP of the final product.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Task 2.1: Adsorption-Based ISPR for BETO-Relevant Bioproducts

This task focuses on the development of adsorption-based in situ product recovery (ISPR) integrated with simulated moving bed chromatography for the recovery and purification of carboxylate products that are relevant to BETO. ISPR has been pursued previously in the Separations Consortium to recover carboxylic acids near or below their pKa values with liquid-liquid extraction coupled to downstream distillation. However, there are many acid products in the BETO portfolio that require neutralization well above their pKa values wherein ISPR could still be a major benefit to the bioprocess performance, including muconic acid, beta-ketoadipic acid, 3-hydroxypropionic acid, itaconic acid, butyric acid, and others. In this task, we are combining dynamic filtration with a rotating ceramic disk, resin capacity measurements, tailored resin synthesis, and simulated moving bed chromatography into an ISPR system that can be used to recover BETO-relevant carboxylates from bioreactor cultivations. We are working across process scales and using computational modeling where applicable alongside techno-economic analysis and life cycle assessment to understand major cost, energy, and GHG emissions drivers. The impact of this project will be a bench-scale integrated approach to recover carboxylate products in situ, which will reduce the waste generation from biological carboxylate production processes and improve the productivities of biological systems.

bio-based acid↗

DOE OSTI2020

Risk Model for EM Decision Support Toolsets

The Government Office of Accountability (GAO) has published several reports identifying the need for the Department of Energy (DOE) Office of Environmental Management (EM) to address mounting costs for DoE's cleanup program. DOEEM could greatly benefit from independent decision tool-sets/models that would allow them to evaluate options and inform business decision at the enterprise level considering site-specific life cycle costs and system plans. Program goals: Develop a tool-set that enables EM to independently evaluate alternatives, assess outcomes from different contracting strategies, and inform critical decisions for the enterprise. Project goals: Adaption of a Risk Model for integration with complimentary tool-sets for project level decision making. Operational Events: Discrete event model that evaluates operational variables (e.g. capacity, throughput, maintenance constraints) and identify bottlenecks. Identifying and Bounding Project Risk: Identify risks that impact confidence in meeting goals (e.g. production). Life cycle Cost: Evaluate impacts of staffing levels, inventory, and capital investments on life cycle costs. Methods and approach: Monte Carlo Analysis is being executed to generate results: Input derives from Risk Register Data; Tied to Projected and Target Schedules; Incorporates float duration within the model. Assumes associated risk mitigation actions being completed within a timeline of five fiscal years. Metrics include: Confidence in Meeting Production Goal; Confidence in Safety Standards; Confidence in Continuous Operation; Other Metrics can be added as appropriate regarding specific site needs. The adapted risk model can be used as a stand alone decision tool or can be integrated complementary tool-sets (i.e. process and cost models) for project-specific decisions. These support tool-sets can then be integrated with others for site- and complex- level evaluations. Future work includes designing an adaptable and modular framework that would allow integration of multiple tool-sets for holistic and/or targeted evaluation of alternative strategies for decision making that could lead to risk and cost reduction across the enterprise.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Colloidal State Machines as Smart Tracers for Chemical Reactor Analysis

A widely utilized tool in reactor analysis is passive tracers that report the residence time distribution, allowing estimation of the conversion and other properties of the system. Recently, advances in microrobotics have introduced powered and functional entities with sizes comparable to some traditional tracers. This has motivated the concept of Smart Tracers that could record the local chemical concentrations, temperature, or other conditions as they progress through reactors. Herein, the design constraints and advantages of Smart Tracers by simulating their operation in a laminar flow reactor model conducting chemical reactions of various orders are analyzed. It is noted that far fewer particles are necessary to completely map even the most complex concentration gradients compared with their conventional counterparts. Design criteria explored herein include sampling frequency, memory storage capacity, and ensemble number necessary to achieve the required accuracy to inform a reactor model. Cases of severe particle diffusion and sensor noise appear to bind the functional upper limit of such probes and require consideration for future design. The results of the study provide a starting framework for applying the new technology of microrobotics to the broad and impactful set of problems classified as chemical reactor analysis.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Stabilized Electrode/Electrolyte Interphase by a Saturated Ionic Liquid Electrolyte for High-Voltage NMC532/Si-Graphite Cells

Nonaqueous electrolyte has become one of the technical barriers in enabling Li-ion battery comprising of a high voltage cathode and high capacity anode. Here, we demonstrate a saturated piperidinum bis(fluorosulfonyl)imide ionic liquid (IL) with a LiFSI salt not only supports the redox reaction on the cathode at high voltages, but also shows exceptional kinetic stability on the lithiated anode as evidenced by its improved cycling performance in a NMC532/Si-graphite full cells cycled between 4.6 and 3.0 V. On the basis of the spectroscopic/microscopic analysis and molecular dynamics (MD) simulations, the superior performance of the cells is attributed to the formation of solid-electrolyte-interphase on both electrode as well as unique solvation structure where a deadlocked coordination network is established at the saturated state, which prevents transition metal dissolution into the electrolyte via a solvation process.

25 ENERGY STORAGE↗

DOE OSTI2020

Critical Infrastructure Classification via CNN-based Modeling and Image Analysis

With recent advances in the fields of satellite imagery and machine learning we now have the ability to develop explainable deep learning models that enhance critical infrastructure analysis. Funded through Idaho National Laboratory’s (INL) Laboratory Directed Research and Development (LDRD) office we are in the process of developing a deep learning model capable of identifying critical infrastructure facilities and embedded features within those facilities. Utilizing current limit of practice techniques in the machine learning areas of explainability and transfer learning our model, once complete, will have the capacity to be used on multiple different imagery data sets and produce results that not only classify critical infrastructure facilities, but also explain why a critical infrastructure facility was classified as a certain type of facility. These advancements eliminate the ‘black box’ approach deep learning models have had in the past, where a user will have to trust the conclusion of a model without understanding what reasoning when into the model’s classification process. They also expand a model’s usefulness, traditionally a deep learning model will have to use the same data set it was originally trained on. Given the long training times of deep learning models this is impractical in a number of scenarios. By utilizing transfer learning advancements, we are eliminating the need to train our model on the same data set it is then run on to classify critical infrastructure facilities. We are also enabling the analysis and classification of data sets that are potentially too small to be divided into a training and testing data set. Once completed this model can provide a foundation to enhanced critical infrastructure analysis, dependency analysis, and potential disaster relief efforts.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

The National Transmission Planning Study: Chapter 5: Stress Analysis for 2035 Scenarios

The National Transmission Planning Study (NTP Study) was led by the U.S. Department of Energy's Grid Deployment Office, in partnership with the National Renewable Energy Laboratory and Pacific Northwest National Laboratory. The study sought to develop new national grid-scale planning tools and methods that can be used by industry, especially when planning for interregional transmission capacity needs; identify potential transmission solutions that will provide broad-scale benefits to electric customers under a wide range of potential futures; inform planning processes for regional and interregional transmission; and identify interregional and national strategies to maintain grid reliability as the grid transitions, including to a reliance on low- and zero-carbon energy resources. The NTP Study is presented as a collection of six chapters.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗

DOE OSTI2024

The National Transmission Planning Study: Chapter 4: AC Power Flow Analysis for 2035 Scenarios

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗

DOE OSTI2023

Membrane Adsorbents Comprising Self-Assembled Inorganic Nanocages (SINCs) for Super-fast Direct Air Capture Enabled by Passive Cooling

The objectives of the proposed project were to develop highly porous membrane adsorbents comprising CO 2 -philic polymers and self-assembled inorganic nanocages (SINCs) for rapid temperature swing adsorption using electricity-free solar heating and radiative cooling, enabling an economically viable approach for direct air capture (DAC). Our core technical activities combine three key innovations. (1) Highly porous flat-sheet membrane adsorbents contain CO 2 -philic amines that can be easily produced using a phase inversion method. (2) CO 2 -philic SINCs can be easily dispersed in the polymers with great stability (compared with the metal-organic frameworks or MOFs). (3) The adsorption and desorption are integrated with solar heating and radiative cooling for rapid continuous operation, in contrast to traditional long-cycle separate operation. The membrane adsorbents containing amines, polymers, and SINCs were produced using a one-step industrial process. The porous membranes coupled with porous SINCs offer low resistance for gas flow and fast CO 2 sorption/desorption cycles, while the incorporation of the additional amine groups provides high CO 2 sorption capacity. The key achievements are summarized below. (1) Membrane adsorbents with high PEI loading (>40%), high porosity of >80%, and low gasflow resistance were prepared in one step using commercially available, low-cost materials. (2) Membrane adsorbents based on Solupor and PEI show CO 2 sorption capacity of >1.5 mmol/g using air containing 400 ppm at a relative humidity of 15%. (3) Effect of the adsorbent compositions (such as PEI type, PEI content, SINC content, porosity) on the CO 2 sorption was systematically investigated. (4) Effect of the processing conditions (such as CO 2 content, temperature, and relative humidity) on the CO 2 sorption was systematically investigated; (5) The stability of the membrane adsorption against many cycles of sorption and desorption was studied. The higher molecular weight of PEI (PEI25k) shows better stability than PEI800. (6) Advanced materials with radiative cooling were developed, which can decrease the temperature by 5-7 °C compared to the ambient temperature. (7) Preliminary techno-economic analysis shows that our process may achieve a capture cost of $1,343/tonne CO 2 with a total OPEX cost of $1,112/tonne CO 2 . The adsorbent replacement cost accounted for 52% of the total OPEX cost. Membrane adsorbents with lower costs and longer operation life can significantly decrease the cost. The proposed project directly addresses the requirement of DE-FOA-0002188, i.e., novel materials with CO 2 adsorption capacity for direct air capture with integrated solar heating and radiative cooling to reduce the cost of the DAC. Our future work will focus on the development of low-cost adsorbents that can be stable at the sorption and desorption conditions for long term.

14 SOLAR ENERGY↗

DOE OSTI2022

Increasing the Pressure‐Free Stripping Capacity of the Lithium Metal Anode in Solid‐State‐Batteries by Carbon Nanotubes

Abstract Lithium metal is the key anode material for solid‐state‐batteries as its successful implementation will drastically increase their energy and power densities. However, anode contact loss during stripping leads to dendrites upon plating and subsequent cell failure. Design strategies to mitigate these issues are crucial to enable the use of lithium metal anodes. This paper reports the dissolution kinetics of composite anodes made of lithium metal and carbon nanotubes (CNTs) with a garnet‐type solid electrolyte (SE). In addition to an enhancement of the effective diffusion within the anode, its dissolution is fundamentally changed from being 2D to 3D. By maintaining contact with the SE, the CNTs facilitate lithium transport to the interface, which yields more than 20 mAh cm −2 discharge capacity at 100 µ A cm −2 without the application of external stack pressure ( > 1 MPa). Conclusions drawn from electrochemical data on the anode microstructure are validated using cryo‐focused‐ion‐beam scanning electron microscopy and correlated with the mechanical properties. Micro‐indentation, acoustic analysis, and stress–strain testing show that mechanical properties of the anode, like yield strength and hardness, are adjustable. Overall, it is shown that the mechanical and electrochemical properties of Li–CNT composite electrodes can be tailored to suit the requirements of a practical cell.

Fuchs, Till↗

DOE OSTI2022

Adsorptive separation and recovery of triacetic acid lactone from fermentation broth

Triacetic acid lactone (TAL), an emerging bioprivileged molecule, can be produced microbially and further chemically upgraded to several high-value chemicals. In this work, several acidic and basic ion-exchange resins and activated charcoal were evaluated for their ability to adsorb microbially produced TAL. Activated charcoal and a weak base resin, Dowex 66, showed similar TAL adsorption capacity of 0.18 ± 0.002 g/g. At 15% w/v activated charcoal, about 98% of TAL present in fermentation broth could be adsorbed. Further, ethanol washing allowed recovery of 72% of adsorbed TAL. A biorefinery producing TAL from sucrose was designed, simulated, and evaluated (through technoeconomic analysis) under uncertainty, for an estimated TAL minimum product selling price (MPSP) of $\$4.27$/kg ($\$3.71$–4.94/kg; 5th–95th percentiles) given the current state of technology and $\$2.83$/kg ($\$2.46$–3.29/kg) following potential near-term improvements to fermentation. This work provides an adsorptive process for the recovery of microbially produced TAL that can be upgraded chemically to a range of industrial products.

09 BIOMASS FUELS↗

DOE OSTI2026

Governing in Time: Temporal Capacity and the Feasibility of Energy Transitions

Energy systems function as both technological systems and temporal institutions that shape how societies coordinate, justify, and support collective choices over time. This paper introduces the concept of governance horizons to explain why energy transitions can remain morally supported yet become institutionally weak under increasing pressure. We argue that governability depends on institutions' capacity to synchronize across multiple timeframes - aligning short-term decisions with intermediate coordination and long-term commitments. When this synchronization fails, transitions struggle not because their goals are dismissed, but because governance lacks sufficient time to justify, coordinate, and uphold decisions. Comparative analysis of San Antonio, Texas, and Interior Alaska reveals how energy system pressures generate distinct temporal configurations: San Antonio exhibits governance horizon stretching, where institutions must simultaneously meet near-term reliability demands and long-term transformation goals, while Interior Alaska exhibits horizon compression, where extreme environmental constraints force decision-making into short stabilization cycles. In both contexts, public support for sustainability goals coexists with institutional strain because evaluative judgments are unevenly distributed over time. A temporal configuration analysis is introduced as a diagnostic analytic stance for identifying these patterns. By treating temporal alignment as an explanatory variable rather than a background condition, this approach clarifies how feasibility, sequencing, and legitimacy are shaped by constraints on institutional time. The analysis demonstrates that successful energy transitions depend not only on technological innovation or institutional support, but on governance systems’ ability to sustain credible coordination across multiple time horizons.

Comparative case study↗