SEARCH · Engineering Papers

Results for “scope”

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.

SourceResearch connectionFrom yearThrough year

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

At least 127 records · Page 7

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Finite element procedure for thermomechanical and structural integrity analysis of beam intercepting devices subjected to free electron laser

High-energy particles, including photons (x-ray, γ-ray, bremsstrahlung), electrons, and protons, possess the capability to penetrate materials and deposit energy within them. The degree of absorption depends on both the energy and type of particles, as well as the properties of the materials with which they interact. This energy deposition can manifest either at the material's surface or throughout its volume, potentially resulting in various failure modes. The primary aim of this paper is to establish a structured analysis methodology for evaluating the structural integrity of beam-intercepting devices when subjected to high-energy particles. Here, the paper also reviews some of the underlying physics, pertinent to the scope of the thermomechanical analysis, potential failure modes, and introduces verification and validation methodologies. Engineers and researchers can utilize the guidelines presented in this paper to effectively plan the development of beam intercepting devices, thereby ensuring their reliability and performance in the presence of high-energy particle exposure.

Finite element analysis↗

DOE OSTI2025

MOOSE-based Tritium Migration Analysis Program, Version 8 (TMAP8) for advanced open-source tritium transport and fuel cycle modeling

Tritium management is critical for the safety, sustainability, and economics of fusion energy systems, and advanced and reliable modeling tools help accelerate the development of tritium technologies. This paper presents the Tritium Migration Analysis Program, Version 8 (TMAP8), an open-source, MOOSE-based application developed to provide state-of-the-art tritium transport and fuel cycle modeling capabilities. TMAP8 aims to expand the capabilities of previous versions (i.e., TMAP4 and TMAP7) by leveraging modern computational techniques, ensuring high software quality assurance standards (key to building trust), and enabling multispecies, multiscale, and multiphysics simulations for integrated tritium transport modeling in complex geometries. This paper outlines TMAP8’s scope and rigorous development practices, emphasizing its transparency, accessibility, modularity, and reliability. We present the current suite of verification and validation cases based on those from TMAP4, demonstrating TMAP8’s accuracy and reliability against analytical solutions and experimental data. Additionally, the paper showcases TMAP8’s integrated fuel cycle modeling capabilities, highlighting its applicability at various scales and levels. The TMAP8 code and documentation are openly available, promoting collaborative development and widespread adoption within the fusion community. Future work will soon expand TMAP8’s verification and validation suite to include those from TMAP7 and other recent experimental studies for validation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

A generalizable machine learning-assisted fast Fourier transform algorithm to simulate the large strain phenomena in polycrystalline materials

Machine learning methods have shown initial promise in constitutive modeling for single crystals or homogenized polycrystals, delivering notable computational efficiency. However, existing machine learning-based constitutive models often lack generalizability, limiting their application across diverse boundary value problems. This study introduces a thermodynamics-informed artificial neural network model to accelerate rate-tangent crystal plasticity fast Fourier transform simulations for cross-scale deformation behaviors of polycrystals under complex loading. Our model integrates microstructural variability and local interactions effectively. To address local effects in each grain, we employ K-means clustering to group Gauss points within the microstructure into clusters assumed to be in similar mechanical states. This approach, based on self-clustering analysis, extends model scope from macroscopic stress response to the granular level, capturing mechanical responses and orientation evolution across grains. This reduces the number of nonlinear problems to solve, with cluster responses propagated throughout each group. The thermodynamics-based artificial neural network-extracted features are further processed using local material state clusters to account for history-dependent deformation and evolving microstructures. Additionally, representative volume element simulations with rate-tangent crystal plasticity fast Fourier transform provide reliable datasets for model training. The proposed model demonstrates high efficiency, accuracy, self-consistency, and enhanced generalizability in predicting strain–stress responses and orientation evolution at both individual grain and aggregate scales under complex loading conditions, such as biaxial tension and arbitrary loading scenarios.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Organic superbases in Lewis pair catalyzed hydrogenations of imines

Organic superbases have recently emerged as powerful components in metal-free catalytic systems, yet their role in frustrated Lewis pair (FLP) catalyzed hydrogenation reactions remain underexplored. In this article, we investigate the diphosphazene superbases P 2 - t Bu (1) and P 2 -Et (2) as base components combined with electronically tunable boranes of formula 9-(X n -C 6 H 5-n )BBN, where X n = 4-NMe₂, 4-OMe, 4-Me, 4-H, 4-F, 4-OCF 3 , 4-CF 3 , 3,5-(CF3), in FLP-catalyzed hydrogenations of imines. While the more sterically encumbered base 1 forms persistent FLPs whose activity correlates with the hydride affinity of the borane, less hindered base 2 generates Lewis acid–base adducts and displays superior catalytic performance, especially with boranes of lower hydride affinity. A systematic screening identified the adduct 2/9-(4-MeO-C 6 H 4 )BBN as the most active catalytic system, achieving quantitative hydrogenation of N-benzylidene aniline at 80 °C and H 2 pressures as low as 40 bar in THF. Multinuclear NMR spectroscopic studies and DFT calculations support a mechanistic scenario in which reversible adduct formation and subsequent dissociation to the free acid–base pair precede heterolytic H₂ cleavage, with adduct stability and borane electrophilicity concurrently dictating catalytic activity. Under optimized conditions, the most active catalyst system, 2/9-(4-MeO-C 6 H 4 )BBN, hydrogenates a broad range of aldimines, including electron-rich 4-NMe₂ and push-pull substrates, mono- and bis-ortho-substituted imines, and selected heteroaryl imines, with excellent yields and selectivity. Collectively, these findings establish design principles for tuning BBN-derived FLP systems and expand the scope of metal-free hydrogenation catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Apolipoprotein A5 reduces clearance of VLDL by altering apolipoprotein E content

Apolipoprotein A-V (APOA5) is a critical regulator of circulating triglyceride (TG) levels. Its deletion leads to elevated plasma TG concentrations by altering the metabolism of very low-density lipoprotein (VLDL) particles in vivo. One way APOA5 exerts its effects is through modulation of lipoprotein lipase (LPL) activity, specifically by disrupting inhibitory interactions between LPL and angiopoietin-like proteins (ANGPTLs). However, the impact of APOA5 on VLDL composition and its potential to alter VLDL metabolism in other ways remains poorly understood. To address this, we investigated the influence of APOA5 on the VLDL proteome, LPL activation, and hepatic remnant uptake. Using VLDL from Apoa5 knockout (KO) and wild-type (WT) mice, we found no evidence that APOA5 directly enhances LPL activity in purified or plasma systems. However, VLDL from Apoa5 K mice was cleared significantly more slowly by cultured hepatocytes. Proteomics experiments from two independent laboratories identified consistent depletion of 17 proteins involved in lipoprotein metabolism, inflammation, and immune response in Apoa5 KO VLDL, including APOE and serum amyloid A1 (SAA1). Remarkably, reintroduction of recombinant mouse APOA5 to the KO plasma partially restored the WT VLDL proteome, including APOE, and normalized VLDL uptake by hepatocytes without altering LPL lipolysis. These findings reveal that APOA5 influences hepatic clearance of VLDL remnants by modulating particle composition, particularly APOE content. This study expands the functional scope of APOA5 in TG metabolism and underscores its role in VLDL remodeling and remnant clearance, offering new insights with implications for understanding hypertriglyceridemia and its roles in inflammation and immune response.

LPL↗

DOE OSTI2025

Protecting air/moisture-sensitive samples using perdeuterated paraffin wax for solid-state NMR experiments under magic-angle spinning

Solid-state nuclear magnetic resonance (SSNMR) spectroscopy is a powerful technique for materials characterization, yet its application to air- and moisture-sensitive materials is often hindered by the difficulty in maintaining an inert environment during magic-angle spinning (MAS). This is particularly true for fast-MAS rotors that do not generally provide tight seals. Herein, we present a generalizable approach employing perdeuterated paraffin waxes—n-icosane-d42 and c-dodecane-d24—as protective embedding media to analyze sensitive organometallic catalysts using SSNMR. We demonstrate that these waxes significantly slow oxidative degradation under MAS conditions. Weak background 1 H and 13 C NMR signals from the waxes are effectively suppressed using double-quantum filtration and cross-polarization techniques. In conclusion, these findings offer a robust method for expanding the scope of SSNMR to air-sensitive systems, with implications for the structural study of reactive materials and catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Multi-faceted framework for extrapolating early age flexural strength to facilitate rapid lifting/handling of high-volume fly ash precast members

Maintaining adequate early-age structural performance for precast concrete components has grown in importance as more sustainable mix designs become more widespread. Achieving high-early flexural strength is particularly crucial to facilitate rapid removal of hardened concrete components from formwork, often within 24 h after fresh concrete placement. Limited research has assessed the effectiveness of traditional design methods in correlating flexural strength with compressive strength for next-generation mix designs, or demonstrated extrapolation of such material performance to larger-scale structural tests. This paper presents a multi-faceted framework to reassess early-age flexural strength for concretes made with relatively high proportions of fly ash from both fresh and harvested sources. Here, the framework provides several pathways, from which the user can select based upon available resources and the specific application, to improve accuracy of early-age cracking moment calculations. Furthermore, the scope includes evaluation of strength performance under curing conditions emulative of those in a precast facility, recommending modulus of rupture equations which are more performance-driven than current design provisions, and experimental tests on prefabricated concrete beams to validate the proposed methodologies. Correlations of early-age strength with both concrete age and maturity measurements compare the effectiveness of utilizing in-situ data to further enhance the prediction methods. Ultimately, the proposed framework helped reduce errors when calculating cracking moment capacity at early ages by tailoring calculations to reflect mix-dependent behavior. Furthermore, most estimates of cracking moment were within 25 % of their corresponding experimental test results, thus promoting confidence for using these strategies with high-volume fly ash precast structures.

42 ENGINEERING↗

DOE OSTI2025

Mapping of fracture and ionic conductivity changes in ion implanted solid electrolytes: Insights from molecular dynamics

Ion implantation emerges as a promising technique to address the persistent challenge of lithium (Li) filament growth in solid-state electrolytes as it can induce compressive stresses inhibiting crack growth and deflect dendrites, de facto mitigating early electrolyte failure. In this study, we examine the potential paradox of ion implantation: while aiming to enhance electrolyte performance, the radiation damage associated with implantation might inadvertently compromise both the ionic conductivity and the intrinsic fracture toughness of the material, rendering the material unsuitable for battery applications. Specifically, we employed molecular dynamics simulations to examine the scope of the downsides of ion implantation, specifically: (i) reduced ionic conductivity (due to radiation-induced amorphization) and (ii) mechanical stability (due to radiation-induced embrittlement) in ion-implanted Li 7 La 3 Zr 2 O 12 (LLZO) solid-state electrolytes. We explore how radiation damage impacts LLZO’s crystalline structure, Li-ion diffusion, and fracture properties at various temperatures and radiation damage levels. The study aims to provide insights into the competing effects of ion implantation and suggest potential engineering strategies for developing more robust solid-state electrolytes with improved conductivity and dendrite resistance.

Conductivity↗

DOE OSTI2025

Under-capacitated and over-powered? Rural austerity and asymmetrical negotiating relationships in US wind energy development

Though rural local governments are central actors in renewable energy development, local governments in the United States (US) remain systematically under-funded. This paper considers what the manifestations of austerity in local governments broadly and rural localities specifically mean for renewable energy development and for energy transitions. Drawing on a survey of 262 elected county officials with experience with wind energy in eight US states, this paper asks how local officials understand the impacts of wind development, how local governments are involved in wind energy negotiations, how the resources and expertise needed to navigate negotiations are distributed among counties, and analyze the relationship between local capacity, access to resources, and involvement in negotiations. We find that local officials express simultaneously affective and material concerns with the impacts of wind development and see negotiations with the developer as central to realizing local benefits. However, the expertise and staffing needed to negotiate with developers is less accessible to poorer or sparsely populated counties, and counties with lower overall revenues have narrower scopes of negotiation, and counties incre. Our results suggest that uneven rural capacity heightens an already asymmetrical relationship between localities and developers. In analyzing how infrastructure developments are shaped by relationships between localities and developers that are conditioned by austerity and (under)capacity, this paper contributes to and bridges scholarly discussions on rural austerity, rescaling, and renewable energy transitions. These results challenge conventional wisdoms around centralizing energy siting processes, contextualize popular and academic debates about opposition to renewable energy development, and highlight the need for rural reinvestment to realize meaningfully participatory energy developments.

Elmallah, Salma↗

DOE OSTI2025

Corrigendum to ‘Under-capacitated and over-powered? Rural austerity and asymmetrical negotiating relationships in US wind energy development’ [J. Rural Stud., 119 (2025) 1–14]

The authors regret that there is an incomplete sentence in the abstract of the article, and request that the portion “, and counties incre” be deleted from the abstract (found at the end of the sentence beginning with “However …”). The portion to be deleted is underlined and bolded below. The authors would like to apologise for any inconvenience caused. Current abstract: Though rural local governments are central actors in renewable energy development, local governments in the United States (US) remain systematically under-funded. This paper considers what the manifestations of austerity in local governments broadly and rural localities specifically mean for renewable energy development and for energy transitions. Drawing on a survey of 262 elected county officials with experience with wind energy in eight US states, this paper asks how local officials understand the impacts of wind development, how local governments are involved in wind energy negotiations, how the resources and expertise needed to navigate negotiations are distributed among counties, and analyze the relationship between local capacity, access to resources, and involvement in negotiations. We find that local officials express simultaneously affective and material concerns with the impacts of wind development and see negotiations with the developer as central to realizing local benefits. However, the expertise and staffing needed to negotiate with developers is less accessible to poorer or sparsely populated counties, and counties with lower overall revenues have narrower scopes of negotiation, and counties incre. Our results suggest that uneven rural capacity heightens an already asymmetrical relationship between localities and developers. In analyzing how infrastructure developments are shaped by relationships between localities and developers that are conditioned by austerity and (under)capacity, this paper contributes to and bridges scholarly discussions on rural austerity, rescaling, and renewable energy transitions. These results challenge conventional wisdoms around centralizing energy siting processes, contextualize popular and academic debates about opposition to renewable energy development, and highlight the need for rural reinvestment to realize meaningfully participatory energy developments.

Elmallah, Salma↗

DOE OSTI2025

Design of the ECCE detector for the Electron Ion Collider

The EIC Comprehensive Chromodynamics Experiment (ECCE) detector has been designed to address the full scope of the proposed Electron Ion Collider (EIC) physics program as presented by the National Academy of Science and provide a deeper understanding of the quark-gluon structure of matter. To accomplish this, the ECCE detector offers nearly acceptance and energy coverage along with excellent tracking and particle identification. The ECCE detector was designed to be built within the budget envelope set out by the EIC project while simultaneously managing cost and schedule risks. Finally, this detector concept has been selected to be the basis for the EIC project detector.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Performance of neutron and proton irradiated AC-LGAD sensors

Characterization of strip and pixel AC-LGAD devices with both laser TCT and probe station (IV/CV) will be shown on AC-LGADs irradiated with 1 MeV reactor neutrons at JSI/Ljubljana and with 400 MeV protons at FNAL ITA to fluences from 1e13~$n_{eq}/cm^2$ to a few times 1e15~$n_{eq}/cm^2$. This study was conducted within the scope of the ePIC detector time of flight (TOF) layer R&D program at the EIC, which will feature AC-LGADs with strip and pixel geometry. Sensors in the TOF layer will receive up to 1e13 $n_{eq}/cm^2$ fluence over the lifetime of the experiment.

AC-LGAD strips↗

DOE OSTI2026

A dual dynamic shutter system for accelerating ion irradiation sample throughput via lateral gas implantation gradients

Ion irradiation for material performance testing is limited due to its serial nature, which allows for only one value of the implantation (appm) versus dose (dpa) parameter space to be explored for each ion and experiment at a time. While ion irradiation can accelerate the process by up to three orders of magnitude compared to neutron irradiation experiments, the sample throughput for ion irradiation remains relatively low. To address these limitations, a novel capability has been developed at the Michigan Ion Beam Laboratory (MIBL), enabling for the creation of single- and two-dimensional lateral ion implantation gradients using recently installed motorized-controlled ion-beam shutters. This advancement can generate a wide scope of the two-dimensional (H+, He2+) implantation parameter space within a single sample. Integration of this new capability now allows for dual- and triple-ion beam experiments to be performed with full user control over not only the ion implantation depth, but also laterally across the sample by imposing ion implantation concentration gradients, thus providing researchers with a high-throughput means for material testing under various irradiation conditions. Furthermore, recent improvements in MIBL's microbeam ion-beam analysis (IBA) target station now allow for probing these concentration gradients in irradiated alloys with exceptional spatial resolution, down to 10 µm. These two approaches promise to significantly improve ion irradiation capabilities and increase the sample throughput by several orders of magnitude. The application of the shutter technique plus the subsequent microbeam characterization of the imposed implantation gradients are showcased by two proof-of-principle ion-irradiated experiments, one performed on single-crystal Si and the other on the fusion-candidate alloy F82H-IEA. These advancements mark a substantial leap in ion-beam technology, offering researchers a robust, high-throughput method to efficiently investigate candidate alloys with high technological readiness for both advanced fission and fusion reactor applications, in a time- and cost-effective manner.

36 - MATERIALS SCIENCE↗

DOE OSTI2024

Improving the modeling of near-wall interphase heat transfer in porous media models of Pebble Bed Reactors

Here, this work aims to improve capabilities for modeling localized effects in porous media models of Pebble Bed Reactors. The wall-channeling effect is the primary local phenomenon of interest in a PBR, where the presence of the reflector wall disrupts the pebble packing, causing the pebbles near the wall to pack less efficiently and creating large void regions. Accurate modeling of the near-wall region is important as it will affect core bypass flow and temperature predictions. Porous media models are commonly used for design scoping and plant-level simulations of PBRs. Although these models have some capabilities to model the near-wall region, the correlations that are available in porous media codes are often inaccurate when a multi-region model is used to discretize the near-wall region. This work employs a high-to-low analysis to study the accuracy of available interphase heat transfer closures. NekRS, a spectral element computational fluid dynamics code, is used to perform Large Eddy Simulations. These LES simulation results are compared to porous media model results from the Pronghorn porous media code. The friction term of the KTA drag closure is first improved, reducing the error in the prediction of the near-wall velocity from over 50% to less than 5%. This is combined with improvements to the form term from previous works to produce a drag closure that is capable of accurately modeling the wall-channeling effect across a variety of flow conditions. The Nusselt number predictions of several heat transfer correlations are compared to the high-fidelity results where it is found that the KTA heat transfer correlation is capable of accurately predicting the local Nusselt numbers that were determined in the high-fidelity simulation. Comparison of the radial solid temperature profiles, however, reveal discrepancies between NekRS and Pronghorn. It is discovered that the implementation of the interphase heat transfer coefficient that exists in many current porous media codes is not valid when local porosities are modeled. Instead, it is suggested that the interphase heat transfer coefficient should be dependent on the local porosity, the Nusselt number, and the local solid surface-to-volume ratio. Implementation of this change produces improvement in the agreement between the results obtained by NekRS and Pronghorn while using the KTA heat transfer correlation.

interphase heat transfer↗

DOE OSTI2025

Development and application of two-step uncertainty propagation and sensitivity analysis methodology for fast reactor safety analysis

Uncertainty quantification (UQ) in nuclear reactors for transients is directly linked with safety assessment through the cross-sections uncertainties, provided as a covariance matrix, which are propagated through the reactor system to output of interest pertaining to reactor safety, such as peak temperatures in fuel/clad/coolant. Using a two-step approach, uncertainties are first quantified and propagated from basic input variables (such as reaction cross-sections) to intermediate quantities (such as reactivity feedback coefficients) through lattice level calculations. Uncertainties of intermediate quantities (from the first step) are then propagated through the system transient calculations, in the second step, to obtain uncertainties on reactor safety output parameters of interest. The scope of this work consists of Uncertainty Quantification & Propagation of nuclear data uncertainties that are highly correlated through unprotected transient overpower and unprotected loss of flow to assess their impact on core safety parameters. This two-step approach in the presence of covariance renders the sensitivity analysis very challenging. In fact, usually the sensitivity analysis is restricted to each step, which limits its application since the sensitivities between the system output quantities and the basic input variables are difficult to obtain. Here, in this work, we address this issue by proposing a simple, general methodology to combine the sensitivity indices obtained in each step by assuming the model behavior being linear. For the first step Generalized Perturbation theory based indices are used while in the second step the recently studied Johnson indices. The uncertainty quantification and sensitivity methodologies discussed here are demonstrated on a generic LFR design which is based on the 500 MWth demonstration Lead-cooled fast reactor (DLFR) using oxide fuel, developed by Westinghouse Electric Company (WEC).

42 - ENGINEERING↗

DOE OSTI2026

Learning from nature’s plant engineers: Hijacking metabolism and development beyond genetics

Plant metabolism underpins the food, fiber, and fuel that support our economy, driving strong interest in new strategies to rewire plant metabolism for emerging applications. While most synthetic biology efforts are reliant on genetic engineering, plants can be manipulated in many other ways that remain comparatively underexplored. Across nature, diverse organisms, including bacteria, fungi, and insects, have evolved sophisticated mechanisms to exploit plant metabolic richness, reshaping it for purposes that span from basic nutrition to the construction of complex, novel structures for shelters. These interspecies interactions and non-model systems represent unique manners in which plants can be reprogrammed or hijacked by other organisms, offering inspiration for novel approaches to engineering plant metabolism. By better understanding the basis of how organisms induce these remarkable transformations in plants, we can expand the conceptual boundaries of synthetic biology and reveal alternative routes to manipulating plants for the production of a diverse array of valuable compounds and materials. Deeper insight into these mechanisms will yield novel blueprints for rethinking the scope and breadth in which we can redesign plant metabolism across many applications.

Sarkiss, Anthony E. [University of California, Ber↗

DOE OSTI2025

Understanding latent timescales in neural ordinary differential equation models of advection-dominated dynamical systems

The neural ordinary differential equation (ODE) framework has shown considerable promise in recent years in developing highly accelerated surrogate models for complex physical systems characterized by partial differential equations (PDEs). For PDE-based systems, state-of-the-art neural ODE strategies leverage a two-step procedure to achieve this acceleration: a nonlinear dimensionality reduction step provided by an autoencoder, and a time integration step provided by a neural-network based model for the resultant latent space dynamics (the neural ODE). This work explores the applicability of such autoencoder-based neural ODE strategies for PDEs in which advection terms play a critical role. More specifically, alongside predictive demonstrations, physical insight into the sources of model acceleration (i.e., how the neural ODE achieves its acceleration) is the scope of the current study. Such investigations are performed by quantifying the effects of both autoencoder and neural ODE components on latent system time-scales using eigenvalue analysis of dynamical system Jacobians. To this end, the sensitivity of various critical training parameters – de-coupled versus end-to-end training, latent space dimensionality, and the role of training trajectory length, for example – to both model accuracy and the discovered latent system timescales is quantified. Furthermore, this work specifically uncovers the key role played by the training trajectory length (the number of rollout steps in the loss function during training) on the latent system timescales: larger trajectory lengths correlate with an increase in limiting neural ODE time-scales, and optimal neural ODEs are found to recover the largest time-scales of the full-order (ground-truth) system. Demonstrations are performed across fundamentally different unsteady fluid dynamics configurations influenced by advection: (1) the Kuramoto–Sivashinsky equations (2) Hydrogen-Air channel detonations (the compressible reacting Navier–Stokes equations with detailed chemistry), and (3) 2D Atmospheric flow.

Advection-dominated dynamical systems↗

DOE OSTI2025

Emergence of deep eutectic solvents (DES): chemistry, preparation, properties, and applications in biorefineries and critical materials

The emergence of renewable deep eutectic solvents (DES) as clean and efficient catalysts and solvents has created new opportunities for lignocellulosic biorefineries and critical material sectors, including chemical, energy, pharmaceutical, textile, and hydrometallurgical industries. This review provides an in-depth overview of DES, covering their chemistry, classifications, preparation methods, processing characteristics, and recyclability, while highlighting their unique attributes and industry relevant applications. Emphasis is placed on the integration of DES into advanced biorefinery systems, focusing on their tunable physicochemical and thermodynamic properties for biomass pretreatment and the production of value-added products. The review explores how DES can be tuned for selective dissolution of biomass components and evaluates production and valorization of DES-derived biochemicals, with attention to lignin extraction mechanisms and conversion of biomass into bioproducts and biofuels. Beyond biorefineries, the scope extends to DES applications in electrochemical energy devices, where they serve as electrolytes, synthesis media for electrode materials, and leaching agents in battery recycling. The multifunctional roles of DES in pharmaceutical, hydrometallurgical, and textile sectors are also explored for contributions to sustainable processing. Finally, the review identifies future research directions, outlining benefits, challenges, and knowledge gaps, for continued industrial development.

09 BIOMASS FUELS↗