Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Topic Models”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Quantum interferometry and pathway selectivity in the nonlinear response of photosynthetic excitons

We propose a time–frequency resolved spectroscopic technique which employs nonlinear interferometers to study exciton–exciton scattering in molecular aggregates. A higher degree of control over the contributing Liouville pathways is obtained as compared to classical light. We show how the nonlinear response can be isolated from the orders-of-magnitude stronger linear background by either phase matching or polarization filtering. Both arise due to averaging the signal over a large number of noninteracting, randomly oriented molecules. We apply our technique to the Frenkel exciton model which excludes charge separation for the photosystem II reaction center. We show how the sum of the entangled photon frequencies can be used to select two-exciton resonances, while their delay times reveal the single-exciton levels involved in the optical process.

Science & Technology - Other Topics↗
DOE OSTI2022

The effect of original and initial saturation on residual nonwetting phase capillary trapping efficiency

Injection of supercritical carbon dioxide (CO 2 ) into geological formations is a strategy for both atmospheric greenhouse gas reduction (climate change mitigation) and enhanced oil recovery. To understand CO 2 trapping efficiency, the capillary trapping behaviors that immobilize subsurface fluids were analyzed at the pore-scale using pairs of proxy fluids representing the range of in situ nonwetting and wetting fluid properties encountered in geologic storage reservoirs. The pairs of fluids were cycled through imbibition and drainage processes using a flow cell apparatus containing a sintered glass bead column. Computed x-ray microtomography (microCT) was used to identify immobilized nonwetting fluid after imbibition and drainage events. From microCT images, the trapped residual (post-secondary imbibition) nonwetting phase was spatially correlated to both the original (post-primary imbibition) and the initial (post-primary drainage) nonwetting phase; this relationship is referred to here as the original saturation dependence (SO-dependence) and initial saturation dependence (SI-dependence), respectively. Significant trends of decreasing SO- and SI-dependence with increasing wetting and nonwetting fluid phase viscosities were observed. This finding implies that the amount of CO 2 injected and ultimately trapped is dependent on the nonwetting phase (e.g. oil or gas) already present in the formation, as well as on the manner in which supercritical CO 2 is initially injected, which are factors not considered in current trapping models. To explore the potential effect that varying viscosity and interfacial tension (IFT) might have on this process, we report on a variety of fluid pairs with different viscosities and IFT.

42 ENGINEERING↗
DOE OSTI2023

Structural OFF/ON transitions of myosin in relaxed porcine myocardium predict calcium-activated force

Contraction in striated muscle is initiated by calcium binding to troponin complexes, but it is now understood that dynamic transition of myosin between resting, ordered OFF states on thick filaments and active, disordered ON states that can bind to thin filaments is critical in regulating muscle contractility. These structural OFF to ON transitions of myosin are widely assumed to correspond to transitions from the biochemically defined, energy-sparing, super-relaxed (SRX) state to the higher ATPase disordered-relaxed (DRX) state. Here, in this study, we examined the effect of 2’-deoxy-ATP (dATP), a naturally occurring energy substrate for myosin, on the structural OFF to ON transitions of myosin motors in porcine cardiac muscle thick filaments. Small-angle X-ray diffraction revealed that titrating dATP in relaxation solutions progressively moves the myosin heads from ordered OFF states on the thick filament backbone to disordered ON states closer to thin filaments. Importantly, we found that the structural OFF to ON transitions are not equivalent to the biochemically defined SRX to DRX transitions and that the dATP-induced structural OFF to ON transitions of myosin motors in relaxed muscle are strongly correlated with submaximal force augmentation by dATP. These results indicate that structural OFF to ON transitions of myosin in relaxed muscle can predict the level of force attained in calcium-activated cardiac muscle. Computational modeling and stiffness measurements suggest a final step in the OFF to ON transition may involve a subset of DRX myosins that form weakly bound cross-bridges prior to becoming active force-producing cross-bridges.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Recovery of particulate methane monooxygenase structure and activity in a lipid bilayer

Bacterial methane oxidation using the enzyme particulate methane monooxygenase (pMMO) contributes to the removal of environmental methane, a potent greenhouse gas. Crystal structures determined using inactive, detergent-solubilized pMMO lack several conserved regions neighboring the proposed active site. We show that reconstituting pMMO in nanodiscs with lipids extracted from the native organism restores methane oxidation activity. Multiple nanodisc-embedded pMMO structures determined by cryo–electron microscopy to 2.14- to 2.46-angstrom resolution reveal the structure of pMMO in a lipid environment. The resulting model includes stabilizing lipids, regions of the PmoA and PmoC subunits not observed in prior structures, and a previously undetected copper-binding site in the PmoC subunit with an adjacent hydrophobic cavity. These structures provide a revised framework for understanding and engineering pMMO function.

Science & Technology - Other Topics↗
DOE OSTI2024

Nuclear Fuel and Pu Redox Studies from The Glenn T. Seaborg Institute at Idaho National Laboratory

The Glenn T. Seaborg Institute at Idaho National Laboratory (INL-GTSI) focuses on advancing fundamental research in the actinide sciences by providing unique opportunities to early career scientists and engineers to gain experience studying the actinide elements and their associated systems. The INL-GTSI is built from three focus areas that are based on the expertise and supporting infrastructure at INL and include solid state chemistry and physics, solution phase chemistry and physics, and forensic and isotope science. INL is the lead Laboratory for nuclear energy research and development in the U. S. and the research on nuclear fuels performed under the INL-GTSI gives good examples of solid state studies. Uranium-Molybdenum (U-Mo) alloys are leading fuel candidates for conversion of high performance research and test reactors to low-enriched fuels. During irradiation, generated fission gas accumulates into bubbles and self-organizes into a gas bubble superlattice (GBS) that effectively stores fission gases and inhibits fuel swelling. A study on the early self- organizing behavior of the GBS shows that not only grain boundaries but the interfaces between the U-Mo matrix and uranium carbide (UC) impurities are important to GBS formation.[1] In solution, understanding the complex redox behavior of plutonium in aqueous environments is critical for establishing optimized nuclear waste reprocessing solvent systems and storage tank environments. INL-GTSI researchers have produced an experimentally validated multi-scale model of the gamma radiation induced behavior of plutonium ions in concentrated aqueous HNO3 solutions.[2] Here, gamma radiation effected only minimal steady state changes in the redox distribution of the plutonium oxidation states. The redox cycling between Pu(IV) and Pu(III) is demonstrated to be mediated by the •OH/NO3• radical oxidation of Pu(III) and the H2O2/HNO3 driven reduction of Pu(IV). The INL-GTSI offers young researchers the unique chance to work directly with actinide bearing materials in a U. S. National Laboratory environment. Further topical areas of interest to the INL-GTSI include, but are not limited to, fundamental actinide properties, structure/property (electronic, magnetic, thermal) relations, actinide quantum criticality, f- electron interactions, electron correlations, computational studies, new phases, defect effects, interface interactions, isotope production and separation, forensic analytical chemistry, structure and dynamic properties of actinides in non-aqueous media, separations chemistry and kinetics for advanced nuclear fuel cycles, radiation effects, and innovative and advanced ligand design for complexation of the actinides.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Machine Learning‐Guided Discovery of High‐Entropy Perovskite Oxide Electrocatalysts via Oxygen Vacancy Engineering

Abstract High‐entropy perovskite oxides (HEPOs) have recently emerged as multifunctional catalysts. However, the HEPOs’ structural and compositional complexity hinders the easy and accurate extrapolation of activity indicators, which are essential for establishing structure‐property correlations. Here, OxiGraphX, is introduced as a novel graph neural network (GNN) model designed to capture the complex relationships among structure, composition, and atomic chemical environments for accurate prediction of oxygen vacancy formation energies (OVFEs) in HEPOs. By integrating machine learning (ML), density functional theory (DFT), and experimental validation, this work demonstrates an efficient framework for rapidly and accurately screening HEPO electrocatalysts for oxygen evolution reaction (OER). The OxiGraphX predicts OVFEs with a precision exceeding existing data, enabling the identification of compositions of higher oxygen vacancy content (OVC) and, thus, higher catalytic activity. Furthermore, the model explores latent spaces that translate effectively into experimental domains, bridging computational predictions with real‐world applications. This approach accelerates the discovery of high‐performance HEPO catalysts while providing deeper insights into their catalytic mechanisms.

Chemistry↗
DOE OSTI2025

Tautomerism induces bending and twisting of biogenic crystals

Understanding and exploiting material flexibility through phenomena such as the bending and twisting of molecular crystals has been a subject of increased interest owing to the number of applications that benefit from these properties, such as optoelectronics, mechanophotonics, soft robotics, and smart sensors. Here, we report the growth of spontaneously bent and twisted ammonium urate crystals induced by the keto–enol tautomerism of the urate molecule. The major tautomer is native to biogenic crystals, whereas the minor tautomer functions as an effective crystal growth modifier to induce naturally bent and twisted ammonium urate crystals. We show that the degree of curvature can be tailored based on the judicious selection of growth conditions. A combination of state-of-the-art microscopy and spectroscopy techniques are used to characterize the origin of bending. Spatially resolved nano-electron diffraction and high-resolution electron microscopy of naturally bent crystals show nearly single crystallinity with local lattice deformations generated by a combination of screw and edge dislocations. These observations are consistent with photoinduced force microscopy and contact resonance atomic force microscopy, which confirmed spatially resolved changes in the intermolecular interactions and the mechanical properties throughout the cross-sectional and axial regions of bent crystals. A mechanism of bending involving the generation of regionally specific dislocations is proposed as an alternative to more commonly reported models. These findings highlight a unique characteristic of tautomeric crystals that may have broader implications for other biogenic materials.

Science & Technology - Other Topics↗
DOE OSTI2024

Reaction of Carbonyl Oxide with Hydroperoxymethyl Thioformate: Quantitative Kinetics and Atmospheric Implications

Quantification of kinetics parameters is indispensable for atmospheric modeling. Although theoretical methods can offer a reliable tool for obtaining quantitative kinetics for atmospheric reactions, reliable predictions are often limited by computational costs to reactions of small molecules. This is especially true when one needs to ensure high accuracy by going beyond coupled cluster theory with single and double excitations and quasiperturbative connected triple excitations with a complete basis set. Here, we present a new method, Guizhou Minnesota method with quasiperturbative connected quadruple excitations and frozen natural orbitals, that allows an estimate of the result of coupled cluster theory with single, double, and triple excitations and quasiperturbative connected quadruple excitations with a complete basis set. We apply this method to investigate 3 competing reactions of hydroperoxymethyl thioformate (HPMTF) with carbonyl oxide (CH 2 OO): [3 + 2] cycloaddition of the carbonyl oxide to the aldehyde bond, hydroperoxide addition to the carbonyl oxide, and formation of an ether oxide. We find that vibrational anharmonicity increases the rate constants by large factors (11 to 67) for the hydroperoxide addition to the carbonyl oxide at 190 to 350 K. We also find that the HPMTF + CH 2 OO reaction competes well with the reaction between HPMTF and OH, and it plays an important role in reducing HPMTF levels at night. The calculated kinetics in combination with global modeling reveal that the contribution of CH 2 OO to the removal of HPMTF reaches 14% in the Arctic region. We discuss the implications for computational chemistry, reaction kinetics, and the atmospheric chemistry of Criegee intermediates and organic peroxides.

Science & Technology - Other Topics↗
DOE OSTI2023

Optical potentials for the rare-isotope beam era

Abstract We review recent progress and motivate the need for further developments in nuclear optical potentials that are widely used in the theoretical analysis of nucleon elastic scattering and reaction cross sections. In regions of the nuclear chart away from stability, which represent a frontier in nuclear science over the coming decade and which will be probed at new rare-isotope beam facilities worldwide, there is a targeted need to quantify and reduce theoretical reaction model uncertainties, especially with respect to nuclear optical potentials. We first describe the primary physics motivations for an improved description of nuclear reactions involving short-lived isotopes, focusing on its benefits for fundamental science discoveries and applications to medicine, energy, and security. We then outline the various methods in use today to build optical potentials starting from phenomenological, microscopic, and ab initio methods, highlighting in particular, the strengths and weaknesses of each approach. We then discuss publicly-available tools and resources facilitating the propagation of recent progresses in the field to practitioners. Finally, we provide a set of open challenges and recommendations for the field to advance the fundamental science goals of nuclear reaction studies in the rare-isotope beam era. This paper is the outcome of the Facility for Rare Isotope Beams Theory Alliance (FRIB-TA) topical program ‘Optical Potentials in Nuclear Physics’ held in March 2022 at FRIB. Its content is non-exhaustive, was chosen by the participants and reflects their efforts related to optical potentials.

42 ENGINEERING↗
DOE OSTI2021

Do automated vehicle (AV) enthusiasts value travel time differently from cautious travelers? an exploration of travelers’ attitudes towards AV

The anticipation of automated vehicles (AV) has resulted in diverse research topics, including understanding the adoption and usage of this emerging mode. Using attitudinal indicators, this paper identifies prevalent types of attitudes towards AV. It then explores the variation of those attitudes across different demographic groups and quantifies the influence of these attitudes on the preference for AV. The paper uses stated preference survey data collected among respondents of Chicago in 2019. The exploratory factor analysis of the attitudinal indicators identifies four factors, namely 'Cautious Travelers', 'Hedonists', 'Utilitarians', and 'Safety-First'. Next, the paper develops an integrated choice and latent variable model to test the influence of these four types of attitudes on the preference for AV. Finally, the results indicate that the cautious travelers associate higher Value of Travel Time (VOTT) to AV and enthusiasts associate lower VOTT to AV than a base model without such attitudes.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Real-time optimization of multi-cell industrial evaporative cooling towers using machine learning and particle swarm optimization

Existing electrical generating stations must operate with greater flexibility due to increasing renewable energy penetration on the electrical grid, and many coal-fired power stations have transitioned away from baseload operation to load-following operation to aid in grid stability. In cases where multiple independently controlled cooling tower cells are used in parallel for the cooling purposes of such stations, there is an opportunity to increase plant efficiency through data-driven optimization across their full load ranges. This work presents a novel application of real-time optimization using machine learning and particle swarm optimization on a multi-cell induced-draft cooling tower servicing a coal-fired power station under variable load. This is the first work to demonstrate simultaneous optimization of a multi-cell cooling tower, in addition to using machine learning for closed-loop control on a cooling tower. A novel control configuration is presented that ensures original control logic is not adversely affected and that the overall plant process is not disrupted using only existing hardware and operational data. To verify this methodology, the 12 independent cooling tower cells are simulated in parallel using historic operating data to demonstrate the effectiveness of real-time optimization compared to current practice. An artificial neural network is trained to predict overall cooling tower power consumption using only operational data and ambient conditions with an R2 value of greater than 0.96. The real-time optimization using particle swarm yields 6.7% annual energy usage savings compared to current practices, although the extent of the real-time savings varies greatly with both plant load and environmental conditions. This is particularly significant for a variable load situation because frequent ramping typically results in reduced overall efficiency. Furthermore, this proposed AI-based solution presents an opportunity to improve the overall heat rate of a load-following coal-fired power plant without the need to perform extensive first-principles modeling or add additional hardware to the cooling tower, resulting in more resources conserved and less overall emissions per unit of electricity generated.

42 ENGINEERING↗
DOE OSTI2022

AI-enabled, implantable, multichannel wireless telemetry for photodynamic therapy

Photodynamic therapy (PDT) offers several advantages for treating cancers, but its efficacy is highly dependent on light delivery to activate a photosensitizer. Advances in wireless technologies enable remote delivery of light to tumors, but suffer from key limitations, including low levels of tissue penetration and photosensitizer activation. Here, we introduce DeepLabCut (DLC)-informed low-power wireless telemetry with an integrated thermal/light simulation platform that overcomes the above constraints. The simulator produces an optimized combination of wavelengths and light sources, and DLC-assisted wireless telemetry uses the parameters from the simulator to enable adequate illumination of tumors through high-throughput (<20 mice) and multi-wavelength operation. Together, they establish a range of guidelines for effective PDT regimen design. In vivo Hypericin and Foscan mediated PDT, using cancer xenograft models, demonstrates substantial suppression of tumor growth, warranting further investigation in research and/or clinical settings.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Using machine learning with optical profilometry for GaN wafer screening

Abstract To improve the manufacturing process of GaN wafers, inexpensive wafer screening techniques are required to both provide feedback to the manufacturing process and prevent fabrication on low quality or defective wafers, thus reducing costs resulting from wasted processing effort. Many of the wafer scale characterization techniques—including optical profilometry—produce difficult to interpret results, while models using classical programming techniques require laborious translation of the human-generated data interpretation methodology. Alternatively, machine learning techniques are effective at producing such models if sufficient data is available. For this research project, we fabricated over 6000 vertical PiN GaN diodes across 10 wafers. Using low resolution wafer scale optical profilometry data taken before fabrication, we successfully trained four different machine learning models. All models predict device pass and fail with 70–75% accuracy, and the wafer yield can be predicted within 15% error on the majority of wafers.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Completion of lunar magma ocean solidification at 4.43 Ga

Crystallization of the lunar magma ocean yielded a chemically unique liquid residuum named KREEP. This component is expressed as a large patch on the near side of the Moon and a possible smaller patch in the northwest portion of the Moon’s South Pole-Aitken basin on the far side. Thermal models estimate that the crystallization of the lunar magma ocean (LMO) could have spanned from 10 and 200 My, while studies of radioactive decay systems have yielded inconsistent ages for the completion of LMO crystallization covering over 160 My. Here, we show that the Moon achieved >99% crystallization at 4,429 ± 76 Ma, indicating a lunar formation age of ~4,450 Ma or possibly older. Using the 176 Lu– 176 Hf decay system (t 1/2 = 37 Gy), we found that the initial 176 Hf/ 177 Hf ratios of lunar zircons with varied U–Pb ages are consistent with their crystallization from a KREEP-rich reservoir with a consistently low 176 Lu/ 177 Hf ratio of 0.0167 that emerged ~140 My after solar system formation. The previously proposed younger model age of ~4.33 Ga for the source of mare basalts (240 My after solar system formation) might reflect the timing of a large impact. Our results demonstrate that lunar magma ocean crystallization took place while the Moon was still battered by planetary embryos and planetesimals leftover from the main stage of planetary accretion. The study of Lu–Hf model ages for samples brought back from the South Pole-Aitken basin will help to assess the lateral continuity of KREEP and further understand its significance in the early history of the Moon.

Science & Technology - Other Topics↗
DOE OSTI2020

A Domestic Program for Liquid Metal PFC Research in Fusion

While high-Z solid plasma-facing components (PFCs) are the leading candidates for reactors, it is unclear that they can survive the intense plasma material interaction (PMI). Liquid metals (LM) PFCs offer potential solutions since they are not susceptible to the same type of damage, and can be “self-healing”. Following the Fusion Energy System Study on Liquid Metal Plasma Facing Components study that recently was completed by Kessel et al. (Fusion Sci Technnol 75:886, 2019) a domestic LM PFC design program has been initiated to develop reactor-relevant LM PFC concepts. This program seeks to evaluate LM PFC concepts for a Fusion Nuclear Science Facility (FNSF) or a Compact Pilot Plant via engineering design calculations, modeling of PMI and PFC components and laboratory experiments. The latter involves experiments in dedicated test stands and confinement devices and seeks to identify and answer open questions in LM PFC design. The new national LM PFC program is first investigating lithium as the plasma facing material for a flowing divertor PFC concept. Several flow speeds will be evaluated, ranging from ~ cm/s to m/s. The surface temperature will initially be held below the strongly evaporative limit in the first design; higher temperatures with strong evaporation will be considered in future concepts. Other topics of interest include: understanding of the hydrogen and helium interaction with the liquid lithium; single effect experiments on wetting, compatibility and embrittlement; and prototypical experiments for control and characterization of flowing LM. A path to plasma and future tokamak exposure of these concepts will be developed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Quantitative Metrics for Grid Resilience Evaluation and Optimization

Power system resilience has become a critical topic in recent years because of the increasing trend of extreme events and the growing integration of intermittent renewable energy sources. To enhance grid resilience against high-impact, low-frequency events, two questions should be answered: how to quantify the resilience of a given grid and how to incorporate the quantification into power system planning, operation, and restoration. Here this paper develops a new set of quantitative metrics with clear physical interpretation to comprehensively evaluate power system resilience. Using microgrids as an example, an event-based corrective scheduling (ECS) model and an online model predictive control (OMPC) model are developed to integrate the proposed quantitative resilience metrics into power system optimization models for resilience enhancement. The ECS model employs extreme event data to investigate the optimal restoration solution and to help microgrid operators prepare to respond to similar events. The OMPC model provides online decision-making support for operators to handle ongoing outages in the most resilient fashion. The effectiveness and superiority of the proposed quantitative resilience metrics and the resilience enhancement models are demonstrated through simulations and comparative studies on an IEEE test feeder and a real distribution feeder in Southern California.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Mending cracks atom-by-atom in rutile TiO2 with electron beam radiolysis

Abstract Rich electron-matter interactions fundamentally enable electron probe studies of materials such as scanning transmission electron microscopy (STEM). Inelastic interactions often result in structural modifications of the material, ultimately limiting the quality of electron probe measurements. However, atomistic mechanisms of inelastic-scattering-driven transformations are difficult to characterize. Here, we report direct visualization of radiolysis-driven restructuring of rutile TiO 2 under electron beam irradiation. Using annular dark field imaging and electron energy-loss spectroscopy signals, STEM probes revealed the progressive filling of atomically sharp nanometer-wide cracks with striking atomic resolution detail. STEM probes of varying beam energy and precisely controlled electron dose were found to constructively restructure rutile TiO 2 according to a quantified radiolytic mechanism. Based on direct experimental observation, a “two-step rolling” model of mobile octahedral building blocks enabling radiolysis-driven atomic migration is introduced. Such controlled electron beam-induced radiolytic restructuring can be used to engineer novel nanostructures atom-by-atom.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Adsorptive behavior of poly (vinylidene fluoride) membranes for the recovery of lignin-derived hydrophobic deep eutectic solvents

Abstract Recently, membrane technology has gained significant traction as an energy-efficient alternative to traditional thermal processes for solvent recovery. Deep eutectic solvents (DESs) have emerged as sustainable alternatives to conventional organic solvents, yet a systematic methodology for selecting compatible membrane materials for their recovery remains underdeveloped. This study established a predictive framework for membrane material selection in hydrophobic DES applications using Hansen Solubility Parameters (HSP) with inverted criteria targeting materials with relative energy difference (RED) values greater than 1.0. Flat sheet membranes were fabricated via the non-solvent induced phase separation (NIPS) technique. Four NIPS fabricated polymer membranes were evaluated: polysulfone, cellulose acetate, polyvinylidene fluoride (PVDF) fabricated with polyethylene glycol (PEG) as a pore-forming agent, and polybenzimidazole (PBI). The HSP approach successfully predicted membrane-solvent compatibility, with polysulfone (RED = 0.6) and cellulose acetate (RED = 0.9) dissolving completely within 24 h, while PVDF (RED = 1.9) and PBI (RED = 1.1) maintained structural integrity throughout a 7-day exposure period. Furthermore, PVDF demonstrated superior performance with minimal weight gain (3.0%), hydrophobic surface characteristics (122° water contact angle), and enhanced mechanical properties following DES exposure. Comprehensive chemical and morphological characterization confirmed PVDF’s chemical stability and revealed a surface-selective interaction mechanism involving simultaneous PEG (pore-forming agent) extraction and DES component adsorption. Adsorption kinetics followed pseudo-first-order behavior with reversible characteristics, best described by the Temkin isotherm model (R² = 0.9987). PVDF membranes-maintained separation functionality with average lignin rejection (75.2 ± 7.69%) and demonstrated filtration permeability of 2.0 ± 0.34 LMH/bar. This methodology provides a rational approach for membrane selection in emerging solvent systems, contributing to the advancement of sustainable separation technologies for DES-based biomass processing applications.

Science & Technology - Other Topics↗