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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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At least 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Measured CO 2 sorption isotherms with 25 Bakken Petroleum System rock samples from the Lower and Upper Shales, Middle Bakken, and Three Forks formations

Isotherms were measured with 25 Bakken Petroleum System (BPS) rock samples using a magnetic suspension balance at reservoir conditions of 110 °C and pressures up to 345 bar. Samples from four wells represented the Middle Bakken (MB) and Three Forks (TF) production zones, and the Upper Bakken Shale (UBS) and Lower Bakken Shale (LBS) source shales. UBS and LBS CO 2 sorption capacities at 345 bar averaged 12–14 g/kg rock compared to 1.3 to 2.5 g/kg rock for MB and TF. Increasing pressure from 150 to 345 bar resulted in only small increases in CO 2 sorption for all lithofacies. For the UBS and LBS source shales, the higher average total organic carbon (TOC) values (14.7 and 11.4 wt.%) and clay values (25 and 28 wt.%) corresponded to their higher CO 2 sorption values while for the MB and TF samples, lower TOCs (0.3 and 0.5 wt.%) and clay values (8.2 and 18.2 wt.%) corresponded to lower CO 2 sorption values. Here, when all 25 samples (from all lithofacies) were evaluated as a group, sorption capacities were highly correlated with TOC (Spearman's rho values +0.84 to +0.85), with rock density (rho values -0.75 to -0.76), and clay content (rho values +0.66). However, correlations with porosity and thermal maturity (Tmax) were weak. Measured sorption capacities and rock porosities showed that sorption accounted for about 10-times as much CO 2 storage as the available pore space for the UBS and LBS lithofacies. In contrast, the pore space dominated the storage resource of the TF and MB lithofacies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Containment strategy for subsurface H 2 storage based on time-dependent soft solids

Here, we propose an innovative containment strategy based on time-dependent soft solids, namely 2 wt% Laponite suspensions, to reinforce natural subsurface seals and engineer flow barriers, with an eye toward making H 2 subsurface storage scalable and geographically agnostic. This suspension can be injected at its initial low viscosity and elasticity into a porous medium, allowing for easy pumping and targeted delivery. Once inside the target zone, it matures into a soft solid with much higher viscosity and elasticity, acting as a potential flow barrier. We discuss the rheological properties of the suspensions and demonstrate that hydrogen does not adversely affect their microstructure, but rather increases the suspensions’ viscosity and elasticity. Moreover, the suspensions enhance the rock samples’ compressive strength, while hydrogen exposure increases their stiffness and ductility. The ability of rock samples saturated with the suspensions to contain higher injected gas pressures is enhanced by aging at higher temperatures.

08 HYDROGEN↗
DOE OSTI2025

Cost analysis of alternative large-scale high-temperature solid oxide electrolysis hydrogen production facilities

We extend our past cost analysis of gigawatt-scale solid oxide electrolysis (SOE) facilities that produce high purity hydrogen gas from water by estimating construction and operating costs for three new alternative design cases: (1) offsite feed steam generation; (2) near-atmospheric pressure (NAP) stack; and (3) onsite electric boiler feed steam generation. Pressure effects on hydrogen electrode-(cathode-)supported SOE cell (SOEC) stack performance are estimated for the same assumed cell and stack construction and used to determine facility-wide stack capital costs for achieving a fixed H2 production at different pressures. Modular balance of plant (BOP) process equipment capital costs are estimated for each new alternative design case using our past equipment sizing, design, and cost data and scaling relationships. Furthermore, we update BOP equipment sizing and design for the NAP case using Aspen®. Vendor quotes for electric boilers are used to estimate costs for the electric boiler design case. Factory and onsite assembly and installation costs for SOEC stacks and BOP equipment are calculated using our past simplified first-principles approach. First-of-a-kind (FOAK) and N th -of-a-kind (NOAK) production maturity cost estimates are included for all results. The case with NAP stacks offers the lowest facility total capital cost (TCC, ~23% lower than base) while use of small electric boilers requires the highest TCC (~3% higher than base). H 2 production prices decrease from the base of ~$\$2.17$ /kgH 2 to ~$\$1.92$/kgH 2 for 1 GW e DC SIP facilities utilizing NAP stacks supplied by offsites steam situated in large modules and blocks for $\$0.030$/kWh e and $0.009/kWh t prices for electricity and thermal energy, respectively. We report all costs in 2021 US dollars.

Balance of plant (BOP) process equipment↗
DOE OSTI2026

Hydrogen production from full-strength corn stover fermentation effluent in single-chamber replaceable-cathode microbial electrolysis cells

Lignocellulosic residual biomass generated by the agricultural sector is an abundant feedstock for biohydrogen production via dark fermentation. However, this process is intrinsically inefficient, converting only ~30% of the reductant energy into H2 and leaving substantial amounts of reduced byproducts. These byproducts, mostly found in the fermentation effluents, can be further valorized in microbial electrolysis cells (MECs) to enhance the overall H2 recovery. However, current MEC configurations are typically dual- or single-chamber systems, yet both suffer from key inefficiencies. Dual-chamber systems rely on proton exchange membranes that are costly and prone to rapid biofouling, whereas single-chamber, membraneless systems are limited by reduced productivity due to H2 recycling and methanogenic consumption In this study, three single-chamber, 50-mL replaceable-cathode microbial electrolysis cells (RC-MECs) were 3D-printed and equipped with a physical separator to isolate anode and cathode compartments and limit H2 migration. Full-strength milled corn stover (MCS) fermentation effluent (COD of ~23.8 g-COD/L) was treated in fed-batch mode over two operational periods spanning 21 (Run 1) and 80 (Run 2) days. The RC-MECs exhibited comparable performance in both runs: after biofilm maturation, current densities exceeded 100 A/m²_cathode, COD removal reached up to 43%. Notably, extended RC-MECs operation led to a substantial methanogenic activity with the CH4 fraction in the cathode gas increasing to as high as 80% of the total biogas. Additions of a methanogenesis inhibitor 2-bromoethanesulfonate (2-BES) produced transient increases in hydrogen yields (11.51 and 5.12 L-H2/L_reactor/day in Runs 1 and 2, respectively); however, sustained 2-BES addition in subsequent cycles reduced total biogas production, decreased COD removal, and led to volatile fatty acid accumulation. Overall, single-chamber MECs can treat high-strength dark fermentation effluents while improving H2 recovery, but methanogenesis remains a key bottleneck, and complete long-term inhibition may be operationally unsustainable.

Hydrogen Production↗
DOE OSTI2020

Deep learning interfacial momentum closures in coarse-mesh CFD two-phase flow simulation using validation data

Multiphase flow phenomena have been widely observed in the industrial applications while it remains a challenging yet unsolved problems. Three-dimensional computational fluid dynamics (CFD) approaches resolve the flow fields on a finer special and temporal scales which can complement the dedicated experimental study. However, closures have to be introduced to reflect the underlying physics in multiphase flow. Among them, the interfacial forces, including drag, lift, turbulent dispersion and wall lubrication forces, play in important role on the bubble’s distribution and migration in liquid-vapor two-phase flow. Development of those closures traditionally rely on the experimental data and analytical derivation with simplified assumptions which usually cannot deliver a universal solution across wide range of flow conditions. In this paper, a data-driven approach, named as Feature Similarity Measurement (FSM), is developed and applied to improve the simulation capability of two-phase flow with coarse-mesh CFD approach. Interfacial momentum transfer in adiabatic bubbly flow serves as the focus of the present study. Both a mature and a simplified set of interfacial closures are taken as the low fidelity data. Experimental data and fine mesh CFD simulations results are adopted as high-fidelity data. Qualitative and quantitative analysis are performed in this paper which reveals that FSM can substantially improve the prediction of coarse mesh CFD model regardless of the choice of interfacial closures and it provides scalability and consistency across discontinuous flow regimes. Furthermore, it demonstrates that data-driven method can aid the multiphase flow modeling by exploring the connections between local physical features and simulation errors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

An integrated data management and informatics framework for continuous drug product manufacturing processes: A case study on two pilot plants

The pharmaceutical industry continuously looks for ways to improve its development and manufacturing efficiency. In recent years, such efforts have been driven by the transition from batch to continuous manufacturing and digitalization in process development. To facilitate this transition, integrated data management and informatics tools need to be developed and implemented within the framework of Industry 4.0 technology. Here, in this regard, the work aims to guide the data integration development of continuous pharmaceutical manufacturing processes under the Industry 4.0 framework, improving digital maturity and enabling the development of digital twins. This paper demonstrates two instances where a data integration framework has been successfully employed in academic continuous pharmaceutical manufacturing pilot plants. Details of the integration structure and information flows are comprehensively showcased. Approaches to mitigate concerns in incorporating complex data streams, including integrating multiple process analytical technology tools and legacy equipment, connecting cloud data and simulation models, and safeguarding cyber-physical security, are discussed. Critical challenges and opportunities for practical considerations are highlighted.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Creep anisotropy modeling and uncertainty quantification of an additively manufactured Ni-based superalloy

The advantages offered by additive manufacturing over traditional processes has driven a great deal of industrial and academic interest in recent years. However, the process is relatively new and requires additional investigation to become sufficiently mature for wide scale industrial adoption. Electron beam melting powder bed fusion is one technology that has shown promise for fabricating high temperature resistant materials such as nickel based superalloys. The resulting microstructures typically exhibit a strong fiber texture in the build direction giving rise to anisotropic time-dependent deformation behavior. In order to accelerate the qualification of these materials for industrial adoption accurate numerical models are needed for simulating their behavior. In this work a crystal plasticity model including non-Schmid effects is presented for capturing creep anisotropy observed in additively manufactured IN738LC. The model is calibrated via a probabilistic framework where model parameters are treated as random variables. An iterative sequential design strategy is utilized to efficiently identify the probability density of the unknown model parameters. As a case study the model is utilized to investigate the behavior of randomly oriented equiaxed grain clusters sometimes observed embedded in the additively manufactured columnar structure. A synthetic realization is simulated and uncertainty is propagated through to the full-field response. Results indicate that these features are the source of significant creep relaxation and strain accumulation which partially explains observed grain boundary decohesion at these locations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Influence of cementation on the yield surface of rocks numerically determined from digital microstructures

Digital Rock Physics has reached a level of maturity on the characterisation of primary properties that depend on the microstructure – such as porosity, permeability or elastic moduli – by numerically solving field equations on μCT scan images of rock. After small deformations or at depth though, most rocks eventually reach their limit of elasticity and the complementary plastic properties are needed to describe the full mechanical behaviour. Currently, determination of a rock’s yield surface from its microstructure is often restricted to semi-analytical criteria derived by limit analysis or numerical simulations performed on idealised geometries. Such simplification lacks representativeness, particularly for processes that affect directly the pore-grain interface such as the cementation phenomenon, happening during diagenesis. Eventually, only direct numerical simulation of elasto-plasticity performed on digitalised microstructures can be used to assess the strength of different cemented materials and its evolution with the alteration of the microstructure. In this study, we provide a comprehensive parametric study on the impact of cementation on rock strength for real microstructures of cemented granular materials. Compared to most previous studies, the whole yield surface is determined numerically (using Finite Element Method) in order to assess the influence of cementation for different stress-paths. The previously known tendency of rock to strengthen with increasing cementation volume is verified. New results on the influence of cement property namely Young’s modulus, friction and cohesion on the rock’s yield surface are explored. The envelopes obtained are compared to the ones obtained by experimental data and existing models. Finally, the framework presented in this study showcases the wider possibility of determining any rock’s or porous material’s yield surface from its microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Long-Term Outcomes of Radical Radiation Therapy with Hypoxia Modification with Biomarker Discovery for Stratification: 10-Year Update of the BCON (Bladder Carbogen Nicotinamide) Phase 3 Randomized Trial (ISRCTN45938399)

Many muscle-invasive bladder cancers are hypoxic, which limits the efficacy of radiation therapy. Hypoxia modification using carbogen and nicotinamide has been tested in a phase 3 trial, Bladder Carbogen Nicotinamide. We present mature follow-up data with biomarker predictions of outcomes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Profiling B cell immunodominance after SARS-CoV-2infection reveals antibody evolution to non-neutralizing viral targets

Dissecting the evolution of memory B cells (MBCs) against SARS-CoV-2 is critical for understanding antibody recall upon secondary exposure. Here, we used single-cell sequencing to profile SARS-CoV-2-reactive B cells in 38 COVID-19 patients. Using oligo-tagged antigen baits, we isolated B cells specific to the SARS-CoV-2 spike, nucleoprotein (NP), open reading frame 8 (ORF8), and endemic human coronavirus (HCoV) spike proteins. SARS-CoV-2 spike-specific cells were enriched in the memory compartment of acutely infected and convalescent patients several months post symptom onset. With severe acute infection, substantial populations of endemic HCoV-reactive antibody-secreting cells were identified and possessed highly mutated variable genes, signifying preexisting immunity. Finally, MBCs exhibited pronounced maturation to NP and ORF8 over time, especially in older patients. Monoclonal antibodies against these targets were non-neutralizing and non-protective in vivo. These findings reveal antibody adaptation to non-neutralizing intracellular antigens during infection, emphasizing the importance of vaccination for inducing neutralizing spike-specific MBCs.

antibody↗
DOE OSTI2022

Forecasting distributed energy resources adoption for power systems

Failing to incorporate accurate distributed energy resource penetration forecasts into long-term resource and transmission planning can lead to cost inefficiencies at best and system failures at worst. We have developed an open-source tool that employs an advanced Bass specification to calibrate and forecast technology adoption. The advanced specification includes geographic clustering, exogenously estimated market size, and dynamic time steps. Training on historical adoption of rooftop photovoltaics at the U.S. county-level and using detailed techno-economic estimates, our model achieves a two-year average mean-absolute-percentage-error of 19% in predicting system counts at the county-level, weighted by population. Model error was negatively correlated with market maturity - the error was 12% for counties in states with at least 28 W-per-capita of installed capacity. The advanced specification significantly reduces unweighted forecasting percent error compared to a conventional Bass specification: from 196% to 25% for capacity and from 226% to 22% for system count.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Monitoring leaf phenology in moist tropical forests by applying a superpixel-based deep learning method to time-series images of tree canopies

Tropical leaf phenology-particularly its variability at the tree-crown scale-dominates the seasonality of carbon and water fluxes. However, given enormous species diversity, accurate means of monitoring leaf phenology in tropical forests is still lacking. Time series of the Green Chromatic Coordinate (GCC) metric derived from tower-based red-green-blue (RGB) phenocams have been widely used to monitor leaf phenology in temperate forests, but its application in the tropics remains problematic. To improve monitoring of tropical phenology, we explored the use of a deep learning model (i.e. superpixel-based Residual Networks 50, SP-ResNet50) to automatically differentiate leaves from non-leaves in phenocam images and to derive leaf fraction at the tree-crown scale. To evaluate our model, we used a year of data from six phenocams in two contrasting forests in Panama. Here, we first built a comprehensive library of leaf and non-leaf pixels across various acquisition times, exposure conditions and specific phenocams. We then divided this library into training and testing components. We evaluated the model at three levels: 1) superpixel level with a testing set, 2) crown level by comparing the model-derived leaf fractions with those derived using image-specific supervised classification, and 3) temporally using all daily images to assess the diurnal stability of the model-derived leaf fraction. Finally, we compared the model-derived leaf fraction phenology with leaf phenology derived from GCC. Our results show that: 1) the SP-ResNet50 model accurately differentiates leaves from non-leaves (overall accuracy of 93%) and is robust across all three levels of evaluations; 2) the model accurately quantifies leaf fraction phenology across tree-crowns and forest ecosystems; and 3) the combined use of leaf fraction and GCC helps infer the timing of leaf emergence, maturation and senescence, critical information for modeling photosynthetic seasonality of tropical forests. Collectively, this study offers an improved means for automated tropical phenology monitoring using phenocams.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Be₂C as a neutron moderator for molten salt reactors: A first-principles study of structural, electronic, and defect properties

Beryllium carbide (Be 2 C), valued for its high neutron moderation efficiency and low absorption cross section, is a promising high-temperature neutron moderator for molten salt reactors. Its practical adoption, however, demands significant technological maturation, requiring comprehensive theoretical and experimental studies of its response to different conditions, including high temperature and irradiation. Here, we report initial results on the fundamental properties and radiation-induced defects of Be 2 C, focusing on antisites, vacancies, interstitial atoms, and Frenkel pairs in the Be and C sublattices. Using density functional theory (DFT) and ab initio molecular dynamics (AIMD), we calculate the defects formation and binding energies, evaluating their dependence on the supercell size, charge states, and chemical environment. In general, carbon defects exhibit higher formation energies, greater sensitivity to cell size, and stronger impacts on the density of states compared to beryllium defects, with charged state the effects being more pronounced. Static DFT reveals multiple metastable interstitial configurations, while AIMD identifies ground states as C-C <100> dumbbells and octahedral Be interstitials. In conclusion, the diversity of metastable configurations and defect states complicates the diffusion mechanisms, requiring further molecular dynamics analysis to elucidate the mechanisms and rates of radiation-induced atomic transport, as well as the structural stability of Be2C.

Ab initio modeling↗
DOE OSTI2026

Finite-element boundary-integral simulation of thin wires and inhomogeneous penetrable bodies in subsurface multilayered anisotropic media

With the prevailing presence of drilling wells near the subsurface in mature oil and gas fields, the application of electromagnetic methods can be particularly challenging where the electromagnetic field is affected by the steel casing. In the past decades, borehole-to-surface and crosswell electromagnetic methods have been utilized for monitoring of reservoir and underground CO 2 storage. This paper presents a unified finite-element boundary-integral (FEBI) method capable of simultaneously modeling the complex electromagnetic interactions between thin metallic wires (representing steel casings) with 3D trajectory and arbitrary 3D inhomogeneous penetrable bodies (such as CO 2 plumes or hydrocarbon reservoirs) within anisotropic multilayered subsurface environments. Unlike existing approaches that treat these components separately or require dense discretization, or are limited to vertical wells, our unified formulation preserves flexible electromagnetic coupling while delivering improved computational efficiency. Assuming the background formation is multilayered anisotropic media, the surface integral equation method is applied to model the thin wires and boundaries of the inhomogeneous bodies. Meanwhile, the finite element method is applied to model the volume of inhomogeneous bodies. Here, the performance of the proposed FEBI method is assessed through comparison with reference numerical results and its practical significance is demonstrated through CO 2 plume monitoring scenarios.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Zinc dynamics regulate early ovarian follicle development

Zinc fluctuations regulate key steps in late oocyte and pre-implantation embryo development; however, roles for zinc in preceding stages in early ovarian follicle development, when cooperative interactions exist between the oocyte and somatic cells, are unknown. To understand the roles of zinc during early follicle development, we applied single cell X-ray fluorescence microscopy, a radioactive zinc tracer, and a labile zinc probe to measure zinc in individual mouse oocytes and associated somatic cells within early follicles. Here, we report a significant stage-specific increase and compartmental redistribution in oocyte zinc content upon the initiation of early follicle growth. The increase in zinc correlates with the increased expression of specific zinc transporters, including two that are essential in oocyte maturation. While oocytes in follicles exhibit high tolerance to pronounced changes in zinc availability, somatic survival and proliferation are significantly more sensitive to zinc chelation or supplementation. Finally, transcriptomic, proteomic, and zinc loading analyses reveal enrichment of zinc targets in the ubiquitination pathway. Overall, these results demonstrate that distinct cell type- specific zinc regulations are required for follicle growth and indicate that physiological fluctuation in the localization and availability of this inorganic cofactor has fundamental functions in early gamete development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Cleavage at the nsp5–nsp6 site of SARS-CoV-2 main protease intermediate precursor is faster from a monomer than a dimer form

Our previous studies of severe acute respiratory syndrome coronavirus 2 main protease (MPro) precursor monomer indicate that the initial N-terminal nonstructural protein (nsp)4/nsp5 cleavage occurs intramolecularly, with a small fraction of the active site loop equilibrium being in the active state. To understand the influence of dimer formation of MPro upon N-terminal cleavage on the subsequent C-terminal nsp5/nsp6 intermolecular cleavage kinetics, the stepwise processing of a monomeric, inactive precursor containing the native terminal cleavage sites of MPro (MBP- (−6) MPro C145A(+3) -GB1-6H, 86.2 kDa) by mature WT MPro (MPro WT ) was investigated. Differential scanning fluorimetry and analytical ultracentrifugation measurements of various MPro constructs suggest that the C145A mutation decreases the dimer dissociation constant (K dimer ) by ∼26-fold, relative to WT C145 and H41A. The monomeric precursor’s nsp4–nsp5 site appears to saturate MProWT’s active sites and cleave faster, followed by a slower first-order cleavage at the C-terminal site. No detectable product resulting from the C-terminal cleavage is observed until most of the N-terminal cleavage is complete. The initial intermediate product (termed MPro C145A-IP ) is a homodimer with an estimated K dimer of <0.05 μM. In contrast, the first-order kinetics observed for the cleavage of the monomeric form of the intermediate product is at least 300 times faster than that of the dimer form. Room-temperature X-ray structure of the MPro C145A-IP –ensitrelvir complex is like that of the MPro WT –ensitrelvir complex and reveals a dynamic C-terminal region including MPro residues 302 to 306. These results are interpreted from the point of view of a mechanism in which nsp5–nsp6 cleavage may occur from a monomeric intermediate, and dimer formation restricts this cleavage.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Passive and active peer effects in the spatial diffusion of residential solar panels: A case study of the Las Vegas Valley

This research analyzes the role of peer influences on the adoption of residential rooftop solar photovoltaic panels (PV) within the context of the Diffusion of Innovation Theory. PV literature indicates that adopters are influenced by word of mouth (WOM) information exchange with peers, i.e., active peer effects, while other studies suggest that living near households with visible rooftop PV installations influences adoption, i.e., passive peer effects. We bridge the gap in this literature by conducting a mixed methods analysis. We develop and administer a survey to Las Vegas Valley (LVV) residents to identify current and potential PV adopters' perceptions of peer-effects and consumer intention variables. We conduct a spatial analysis of Google's Project Sunroof data to identify LVV neighborhoods in the later stages of the PV diffusion process, i.e., those with the highest PV adoption rates. Key results show that current PV adopters living in early diffusion areas report significantly higher active and passive peer effects compared to adopters in later diffusion areas. Potential adopters in later diffusion areas report higher passive peer effects than those in early diffusion areas. Overall, because LVV has a low PV adoption rate (<3%), short term strategies aimed at increasing PV adoption should emphasize WOM active peer effects. Here, we caution against long-term green marketing strategies focusing solely on peer-effects as the PV market matures.

14 SOLAR ENERGY↗
DOE OSTI2022

Energy-effective and low-cost carbon capture from point-sources enabled by water-lean solvents

Aqueous amines, as the most mature carbon capture technology, are subject to high energy and cost penalties due to the large water content in their formulations. Emerging technologies are in demand to enable a transition to a low-carbon global economy. However, rigorous process modeling and techno-economic analyses are limited for emerging carbon capture technologies. Here, four CO 2 -Binding Organic Liquids (CO 2 BOLs), all water-lean solvents were presented as promising options towards energy-effective and low-cost carbon capture from point sources. Rigorous solvent property and process models were developed in Aspen Plus for a coal-fired power plant with CO 2 BOL-based carbon capture unit. Techno-economic analyses were conducted in 2018 US pricing basis. The results suggest that water-lean formulations can minimize water condensation and vaporization, leading to a 36% energy saving compared with aqueous amines. Indeed, these CO 2 BOLs can capture up to 97–99% CO 2 from coal fired plant. The estimated carbon capture cost is about $40/tonne CO 2 at 90–97% carbon capture rate, about 12–23% less expensive than the conventional aqueous amine technology. The comparison between these CO 2 BOLs showed that in addition to vapor liquid equilibrium and kinetics (key properties for aqueous solvents), viscosity, volatility, and hydrophobicity, also have strong impacts on the performance of water-lean solvents. The methods presented in this work can be used to evaluate other emerging carbon capture technologies, while the results linking costs and performance of carbon capture solvents with their properties. Additionally, this work identifies research directions and targets for further reductions in total costs of capture from either cost or energy perspectives for these leading water-lean solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗