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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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The efficacy, economics, and sustainability of a bio-based insecticide produced from the catalytic fast pyrolysis of biomass is reported. This synergistic approach to fuels and agrochemical production can improve both energy and food sectors.
In this study, a novel ammonia-based pretreatment for densified lignocellulosic biomass was developed to reduce ammonia usage and integrate with viable biomass logistics scenarios. The COmpacted Biomass with Recycled Ammonia (COBRA) pretreatment performed at 100 °C allows >95% conversion of sugarcane bagasse (SCB) carbohydrates into soluble monomeric and oligomeric sugars (glucose and xylose) using industrially relevant 6% glucan loading (~21% solids loading) enzymatic hydrolysis conditions at reduced enzyme loadings. Pretreatment via COBRA with simultaneous lignin extraction (COBRA-LE) improved Saccharomyces cerevisiae 424A(LNH-ST) metabolic yield from 89% to 97.5% relative to COBRA without delignification, allowing a process ethanol yield of 71.6%. A technoeconomic analysis on SCB biorefining to ethanol in the state of São Paulo, Brazil, compared COBRA to other mature technologies, such as AFEX and steam-explosion. Amongst all scenarios studied, biorefineries based on COBRA-LE pretreatment offered the lowest average minimum ethanol selling price of US$1.45 per gallon ethanol. COBRA pretreatment was subsequently tested on perennial grasses and hardwoods, and >80% total sugar yields were achieved for all cases.
The combustion of middle distillates (diesel and jet fuel) is responsible for the emission of more than 2 GTon of CO 2 per year worldwide. While sustainable alternatives exist for gasoline and jet fuel, we still lack sustainable alternatives for diesel. This fact is especially relevant if we consider that electrification of sectors where diesel is used is challenging. One sustainable approach for diesel production is the catalytic upgrading of ethanol. While most work in this field has focused on the dehydration/oligomerization of ethanol, this approach is limited to producing fuels that have a high degree of branching and low cetane number. Another approach is the sequential use of ethanol Guerbet coupling, leading to higher alcohols, followed by etherification, leading to large ethers which, importantly, result in a product with high cetane number. In this work, we explore the catalytic upgrading of ethanol into diesel following an approach based on the initial Guerbet coupling of ethanol followed by etherification. The results presented are a collaborative and synergic effort among process and systems engineers, experimentalist in the area of catalysis, and fuel property modelers. Here, we demonstrate experimentally the feasibility of upgrading ethanol into a diesel fuel with properties that surpass its fossil counterpart. The diesel produced has a predicted cetane number of ~70 and outstanding cold flow properties, while maintaining other properties (viscosity, density, and flash point) within expected ranges. A technoeconomic analysis performed based on a detailed biorefinery model shows that the MFSP is ~5.89$ per Gal in 2021 dollars when lignocellulosic ethanol is used, with the most relevant economic driver the cost of the ethanol feedstock. The upgrading process can be performed with a net energy gain (EROI = 1.49 > 1). An LCA analysis of greenhouse gas (GHG) emissions reveals that the use of lignocellulosic ethanol may lead to more than 50% reduction in GHG emissions compared to fossil diesel. Depending on the CO 2 emissions associated with the production of ethanol we show that in some instances the production of carbon neutral diesel fuel is possible.
Creating pathways to renewable fuels, chemicals, and materials through improved catalyst formulations and integrated process development.
Hydrothermal liquefaction of wet wastes (e.g., food waste and sewage sludge) offers a promising avenue for producing biocrude, but the resulting product is often contaminated with metals and water, impacting the biocrude upgrading steps to produce final fuel (e.g., jet and diesel). Here this study investigates the use of aqueous solutions of formic acid for desalting biocrudes and improving their quality. The results show that this approach significantly reduces both metal and water content, enabling mild hydrotreatment with reduced hydrogen consumption to further enhance the biocrude's quality. A preliminary technoeconomic analysis based on these experimental results shows that even without optimization, this washing process can yield biocrude with a minimum selling price of $1.87/GGE. Overall, our study demonstrates the potential for using dilute formic acid aqueous solutions to improve the quality of biocrudes, which can lead to more efficient and cost-effective conversion into biofuels.
Meeting aggressive decarbonization targets set by the International Civil Aviation Organization (ICAO) will require the rapid development of technologies to produce sustainable aviation fuel (SAF). Catalytic fast pyrolysis (CFP) can support these efforts by opening pathways for the conversion of woody biomass into an upgraded biogenic oil that can be further processed to SAF and other fuels. However, the absence of end-to-end experimental data for the process leads to uncertainty in the yield, product quality, costs, and sustainability of the pathway. The research presented here serves to address these needs through a series of integrated experimental campaigns in which real biomass feedstocks are converted to a final SAF product using large bench-scale continuous reactor systems. For these campaigns, the degree of catalytic upgrading during CFP was varied to produce CFP-oils with oxygen contents of 17 and 20 wt% on a dry basis. The CFP-oils were then hydrotreated and distilled into gasoline, diesel, and SAF fractions. Detailed yield and compositional data were obtained for each step of the process to inform technoeconomic and lifecycle analyses, and the fuel properties of the SAF fraction were evaluated to provide first-of-its-kind insight into the quality of the final product. This research reveals opportunities to optimize process carbon efficiency by tuning the degree of catalytic upgrading during the CFP step and highlights routes to produce a high-quality cycloalkane-rich SAF with 85–92% reduction in greenhouse gas emissions compared to fossil-based pathways.
The global plastic waste crisis has increased in severity in recent years: annual plastic production is projected to reach 500 million metric tons by 2025, and plastic waste accumulation is expected to surpass 12 billion metric tons. Despite these growing volumes, only ∼9% of plastic waste is currently recycled; the majority is either landfilled, incinerated, or mismanaged, contributing to escalating greenhouse gas emissions—from 1.7 Gt carbon dioxide equivalent (CO 2 -eq.) in 2015 to an estimated 6.5 Gt CO 2 -eq. by 2050—and physical environmental pollution. This review provides a comprehensive overview of advanced plastic upcycling strategies to address this issue and recover value from diverse plastic waste streams. Recent developments in solvent-based dissolution, chemical depolymerization, and thermochemical conversions are examined for major plastic types, including polyolefins, polycondensation polymers, and PVC. Underlying reaction pathways, catalyst designs, and processing parameters that govern product selectivity, efficiency, and conversion yields are discussed in depth. Emerging techniques such as microwave-assisted depolymerization, tandem catalysis, and co-processing approaches are highlighted for their potential to enhance efficiency under milder conditions. Emphasis is also placed on the production of high-value products such as monomers, naphtha-range hydrocarbons, and syngas, and discussion is provided on catalyst stability, contaminant removal, scalability, life cycle effects on the environment, and technoeconomic viability. Finally, the review outlines future research directions focused on catalyst innovation, integrated process design, supportive policy frameworks, and interdisciplinary collaboration. All recommendations are aimed at accelerating large-scale implementation of plastic upcycling technologies and advancing the global circular plastics economy.
Lithium-ion battery recycling remains constrained by processes that recover metals at the expense of electrode integrity, while even direct recycling typically requires shredding to black mass followed by binder removal, separation, and full electrode refabrication. Here, we introduce direct electrode-to-electrode regeneration (DEER), a simultaneous electrochemical regeneration of used NMC and graphite electrodes from end-of-life batteries in their intact form by dissolving the passivating electrode–electrolyte interphase (EEI). DEER employs 1,3-dimethyl-2-imidazolidinone (DMI), a high donor number solvent that creates a thermodynamic environment favorable for solubilizing redox inactive EEI components. DEER dissolves the thick EEI on both used electrodes while preserving electrode integrity, enabling up to 95% capacity regain and improved cycling stability with a residual LiF-rich interphase. Operando Raman, operando IR, and post-mortem NMR directly track the electrochemically driven dissolution of carbonate-derived EEI species in the used DMI-based recycling electrolyte. Technoeconomic and life-cycle analyses show that DEER reduces the cost of recycled cell manufacturing by 56% relative to pyro- and hydrometallurgy, while lowering energy use and greenhouse gas emissions. Overall, DEER establishes the first validated pathway to directly regenerate and reuse electrodes harvested from truly end-of-life batteries, converting the key interfacial bottleneck into a controllable dissolution process and opening a practical route toward electrode level circularity.
Abstract Limiting anthropogenic global climate warming since the start of the industrial period to less than 2 °C will very likely require both deep and rapid reductions in anthropogenic greenhouse gas emissions and a range of approaches toward carbon dioxide removal (CDR). One prominent CDR approach is enhanced weathering (EW), in which crushed silicate rock is applied on land or in the open ocean to accelerate natural weathering processes that absorb carbon dioxide from Earth’s ocean–atmosphere system. However, in addition to a range of potential environmental, socioeconomic, and ethical issues associated with this pathway, bottlenecks in feedstock sourcing represent a key barrier for deployment of EW at scale. Here, we evaluate the potential of silicate wastes produced from industrial processes—such as steel slag and cement waste—as feedstocks for the EW process. An empirical model that links industrial alkaline waste production to gross domestic product at purchase power parity is developed to forecast waste production in the alternative futures described by the shared socioeconomic pathway (SSP) framework. By incorporating these results into an intermediate-complexity Earth system model, we also explore the impacts of EW using industrial waste on changes to global temperature, ocean pH, and ocean aragonite saturation state, while also quantifying overall CDR efficiency through the end of the century. We estimate a maximum cumulative end-of-century capture potential of ∼400 GtCO 2 for industrial waste, which could represent a significant fraction of the projected CDR requirement of many mitigation scenarios in the SSP framework. However, feedstock-dependent environmental impacts and the technoeconomics of feedstock redistribution may ultimately limit deployment scope.
Wind energy is among the most mature renewable energy technologies, accounting for 11% of the current US electricity generation in 2024, with the lowest average levelized cost. While it is known that substantial opportunity exists for further development, a key question has been where wind energy is best suited compared to other technologies. This study leverages an immense dataset of parcel-resolved technoeconomic potential for the contiguous United States, focusing on distributed wind (DW) energy—a configuration where one or more turbines, typically 30–60 m in height are used to satisfy nearby energy needs. The analysis is conducted at multiple spatial scales and considers land use, crop land, census, and incentive program data to determine the most opportune areas for market development. The results show that rural, agricultural and residential areas are most suited to DW. Connection type (in front of, or behind the meter) and regulations determine the best application, while siting constraints, economics, demand and the wind resource determines the optimal size of turbine.
Abstract Low carbon synfuel can reduce dependence on fossil fuels like diesel and jet fuel, and, with large-scale cost-effective production, contribute to global transportation sector decarbonization, Simultaneously, nuclear power plants are struggling economically due to falling wholesale electricity prices. Converting existing nuclear plants for synfuel production could preserve these low-carbon assets and enable large-scale synfuel production, yet no comprehensive technoeconomic analysis exists. This study evaluates the potential of integrating synthetic fuel production with five US nuclear plants, considering electricity and fuel markets and carbon dioxide source access. Such integration could enhance nuclear plant profitability by up to $792 million and offer a 10% return on investment over 20 years. The hydrogen production tax credit from the 2022 Inflation Reduction Act is crucial, comprising 75% of revenues on average. Carbon feedstock transportation has the highest cost at 35%, followed closely by synfuel production capital costs. Incentive policies are thus key for the decarbonization of the transportation sector and the economic importance of the geographic location of Integrated Energy Systems.
We report an industrially relevant approach to both scalable and fast open-air perovskite photovoltaic (PV) module production. This work resolves some of the most formidable barriers to module-level scaling that the perovskite community has been facing. Key advances include scalable large-area spray deposition, new monolithic integration scribing techniques, advanced photoluminescence characterization, and reproducible high-throughput manufacturability. Our rapid spray processing techniques enabled the highest perovskite PV efficiency produced in open-air. Innovations in scribing techniques enabled the first single-source laser process to achieve perovskite module monolithic integration and technoeconomic analysis led to a comprehensive cost model for perovskite module manufacturing. We report significant progress in reducing perovskite manufacturing costs necessary to potentially compete with incumbent Si-based PV for utility-scale power generation.
As renewable power generation becomes the mainstream new-built energy source, energy storage will become an indispensable need to complement the uncertainty of renewable resources to firm the power supply. When phasing out fossil-fuel power plants to meet the carbon neutral utility target in the midcentury around the world, large capacity of energy storage will be needed to provide reliable grid power. The renewable power integration with storage can support future carbon-free utility and has several significant impacts including increasing the value of renewable generation to the grid, improving the peak-load response, and balancing the electricity supply and demand. Long-duration energy storage (10–100 hours duration) can potentially complement the reduction of fossil-fuel baseload generation that otherwise would risk grid security when a large portion of grid power comes from variable renewable sources. Current energy storage methods based on pumped storage hydropower or batteries have many limitations. Thermal energy storage (TES) has unique advantages in scale and siting flexibility to provide grid-scale storage capacity. A particle-based TES system has promising cost and performance for the future growing energy storage needs. This paper introduces the system and components required for the particle TES to be technically and economically competitive. A technoeconomic analysis based on preliminary component designs and performance shows that the particle TES integrated with an efficient air-Brayton combined cycle power system can provide power for several days by low-cost, high-performance storage cycles. It addresses grid storage needs by enabling large-scale grid integration of intermittent renewables like wind and solar, thereby increasing their grid value. The design specifications and cost estimations of major components in a commercial scale system are presented in this paper. The cost model provides insights for further development and cost comparison with competing technologies.
More than 30% of electrical energy passes through power electronics today with speculation that in the next decade this could grow to 80%. The wide bandgap semiconductor market is already approaching $1 billon USD in 2019 and is projected to be almost $7 billion USD in 2028. Even with its high cost, SiC, is starting to dislodge the incumbent Si technology in some applications, such as hybrid and electric vehicles, due to smaller size, and higher efficiency. We review and report the IHS Markit’s market predictions for wide bandgap semiconductor technologies, and highlight the technoeconomic analysis results for the manufacturing cost of Ga2O3 wafers. Specifically, we focus on the potential for Ga2O3 to be more economically advantageous than SiC using current manufacturing methods and then identify opportunities where research can further reduce the volume cost of Ga2O3 wafers.
Bioconversion of a heterogeneous mixture of lignin-related aromatic compounds (LRCs) to a single product via microbial biocatalysts is a promising approach to valorize lignin. Here, Pseudomonas putida KT2440 was engineered to convert mixed p-coumaroyl– and coniferyl-type LRCs to β-ketoadipic acid, a precursor for performance-advantaged polymers. Expression of enzymes mediating aromatic O-demethylation, hydroxylation, and ring-opening steps was tuned, and a global regulator was deleted. β-ketoadipate titers of 44.5 and 25 grams per liter and productivities of 1.15 and 0.66 grams per liter per hour were achieved from model LRCs and corn stover-derived LRCs, respectively, the latter representing an overall yield of 0.10 grams per gram corn stover-derived lignin. Technoeconomic analysis of the bioprocess and downstream processing predicted a β-ketoadipate minimum selling price of $\$2.01$ per kilogram, which is cost competitive with fossil carbon-derived adipic acid ($\$1.10$ to 1.80 per kilogram). Overall, this work achieved bioproduction metrics with economic relevance for conversion of lignin-derived streams into a performance-advantaged bioproduct.
Synthetic biology generates vast combinatorial designs, yet high-throughput analytical methods to screen them are poorly matched to interrogate this search space. We address this challenge by developing a biosensor-driven, growth-coupled selection strategy in Pseudomonas putida for isoprenol, a potential aviation fuel precursor. We found and characterized a noncanonical signaling pathway, revealing a functional and physical complex between a hybrid histidine kinase and an alcohol dehydrogenase, whose activity is tuned by heterodimerization. Leveraging this biosensor in a pooled CRISPRi library selection, we identified key host limitations. Iterative combinatorial strain engineering derived from these hits yielded a 36-fold titer increase to ~900 milligrams per liter. Integrated omics analysis revealed that metabolic rewiring toward amino acid catabolism was crucial for this improvement. This observation was found to be beneficial by technoeconomic analysis. Our modular workflow provides a powerful strategy for optimizing complex heterologous pathways and uncovering emergent host biology.
Large-scale deployment of negative emissions technologies (NETs) that permanently remove CO 2 from the atmosphere is now considered essential for limiting the global temperature increase to less than 2°C by the end of this century. One promising NET is direct air capture (DAC), a technology that employs engineered chemical processes to remove atmospheric carbon dioxide, potentially at the scale of billions of metric tons per year. This review highlights one of the two main approaches to DAC based on aqueous solvents. The discussion focuses on different aspects of DAC with solvents, starting with the fundamental chemistry that includes the chemical species and reactions involved and the thermodynamics and kinetics of CO 2 binding and release. Chemical engineering aspects are also discussed, including air–liquid contactor design, process development, and technoeconomic assessments to estimate the cost of the DAC technologies. Various solvents employed in DAC are reviewed, from aqueous alkaline solutions (NaOH, KOH) to aqueous amines, amino acids, and peptides, along with different solvent regeneration methods, from the traditional thermal swinging to the more exploratory carbonate crystallization with guanidines or electrochemical methods.
Various modeling techniques are used to predict the capacity fade of Li-ion batteries. Algebraic reduced-order models, which are inherently interpretable and computationally fast, are ideal for use in battery controllers, technoeconomic models, and multi-objective optimizations. For Li-ion batteries with graphite anodes, solid-electrolyte-interphase (SEI) growth on the graphite surface dominates fade. This fade is often modeled using physically informed equations, such as square-root of time for predicting solvent-diffusion limited SEI growth, and Arrhenius and Tafel-like equations predicting the temperature and state-of-charge rate dependencies. In some cases, completely empirical relationships are proposed. However, statistical validation is rarely conducted to evaluate model optimality, and only a handful of possible models are usually investigated. This article demonstrates a novel procedure for automatically identifying reduced-order degradation models from millions of algorithmically generated equations via bi-level optimization and symbolic regression. Identified models are statistically validated using cross-validation, sensitivity analysis, and uncertainty quantification via bootstrapping. On a LiFePO 4 /Graphite cell calendar aging data set, automatically identified models utilizing square-root, power law, stretched exponential, and sigmoidal functions result in greater accuracy and lower uncertainty than models identified by human experts, and demonstrate that previously known physical relationships can be empirically "rediscovered" using machine learning.