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At least 1,099 records · Page 61

Comparison of ammonia with methanol, liquefied natural gas and conventional marine transportation fuels through life cycle cost and emissions analysis

This work evaluates ammonia as a potential marine fuel for a SUEZMAX tanker and compares it with methanol, liquefied natural gas, and conventional fuel oils. The motivation arises from the need to identify low-emission, cost-competitive fuel options that can reduce greenhouse gas emissions from international shipping. The central hypothesis is that ammonia produced from renewable energy sources can achieve lower well-to-wake greenhouse gas emissions with varying life cycle costs based on the region. Life cycle assessment and techno-economic analysis were performed for a thirty-year vessel lifetime on two representative trade routes: from Saudi Arabia to Japan and from Saudi Arabia to the Netherlands. Four ammonia production pathways were assessed: natural gas, natural gas with carbon capture, natural gas pyrolysis, and renewable electricity–based synthesis. Results show that wind-based ammonia produced in Saudi Arabia achieved the lowest life cycle well-to-wake greenhouse gas emissions, between 0.58 and 0.64 million metric tons, among all fuels when using regional grid process electricity. With renewable process electricity, ammonia produced from natural gas pyrolysis in Saudi Arabia showed comparable emissions of 0.37 to 0.44 million metric tons with wind-based ammonia of 0.37 to 0.43 million metric tons. Liquefied natural gas exhibited the lowest life cycle cost, between 402 and 412 million United States dollars, and the only negative carbon abatement cost, ranging from −277 to –322 United States dollars per metric ton of greenhouse gas, compared with high sulfur fuel oil. The findings indicate that renewable ammonia offers a promising long-term pathway for reducing shipping emissions, while liquefied natural gas remains the most cost-effective option in the near term.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Impact of non-irrigation on 1G and 2G bioethanol potential of oilcane feedstock: A field to fuel pipeline study

This study evaluates the bioethanol potential in response to irrigation (IR) and non-irrigation (NIR) of oilcane (OC) during a seasonal drought prior harvest. The juice was extracted through mechanical pressing of stems and fermented by Ethanol Red® yeast to produce first-generation bioethanol. Hydrothermal pretreatment followed by enzymatic hydrolysis of bagasse was performed to produce monomeric sugars from structural carbohydrates. The hydrolysates were fermented with engineered yeast for second-generation bioethanol production. The irrigated oilcane juice (276.3 ± 8.9 g/L) constitutes higher sugar concentrations than non-irrigated oilcane juice (236.5 ± 2.2 g/L). The enzymatic hydrolysis of IR-OC and NIR-OC pretreated bagasse yielded similar concentrations of 247.5 ± 2.22 and 249.7 ± 4.98 g/L fermentable sugars. Industry-relevant bioethanol titers of ≥99 g/L and ≥75 g/L were achieved from juice and hydrolysates, respectively. Therefore, the non-irrigation regime did not impact the 1G and 2G bioethanol titers. However, the overall bioethanol yield can be lower due to the reduction of stem yield (8 %) per hectare.

09 BIOMASS FUELS↗

Bat activity at ecovoltaic solar energy developments in the Midwestern United States

As global photovoltaic (PV) solar electricity generation continues to increase, some PV sites are co-prioritizing electricity generation and ecosystem function (“ecovoltaics”) to align renewable energy development with biodiversity conservation. Thus far, positive responses of plant and insect communities to native habitats at ecovoltaic sites have been observed, but there has been little research on bat responses to ecovoltaic designs in the U.S. We conducted passive ultrasonic monitoring in 2023 and 2024 at 12 solar sites and paired reference sites (agricultural fields) to investigate bat activity responses to ecovoltaic facilities in the Midwestern U.S. We found that average weekly overall bat activity was approximately 50?% higher within ecovoltaic sites than reference sites in the first half of the monitoring season. We also found species-specific differences in bat responses to ecovoltaic sites, with Hoary Bats showing higher activity on ecovoltaic sites throughout most of the monitoring season, Big Brown Bats showing higher activity on ecovoltaic sites during the first one-third of the monitoring season, and Silver-haired Bats showing no difference in activity between ecovoltaic sites and reference sites. There were no weeks in which bat activity was statistically greater on reference sites, suggesting that bats in the Midwestern U.S. do not avoid ecovoltaic solar sites. Rather, our results suggest that ecovoltaic sites in this region may provide early season (May-June) habitat at a time of year when resources may be limited in the surrounding landscape. These findings support a growing body of evidence on the positive ecological outcomes of ecovoltaic designs. Further investigations of the types of bat calls being recorded at PV sites and relationships with insect prey abundance are needed to understand the underlying drivers of species-specific responses to PV developments.

14 SOLAR ENERGY↗

A robust spectral element implementation of the $k - τ$ RANS model in Nek5000/NekRS

The $k - ω$ Reynolds Averaged Navier Stokes (RANS) model is one of the industry standard approaches for modeling of turbulent flows. It performs better than the $k - ϵ$ model for low Reynolds number flows and is also more suitable for boundary layers with adverse pressure gradients. Major drawback of the model, however, is that the asymptotic value of $ω$ at the walls is singular, necessitating the use of a contrived “sufficiently” large value for $ω$ as the boundary condition for its transport equation. Here, this invariably leads to the solution being sensitive to near wall grid spacing. While an acceptable solution for low order (finite volume) methods, the excessive near wall gradients lead to persistent numerical stability issues in high order codes. To alleviate the problem, specifically in the context of the high order spectral element code Nek5000, a regularized $k - ω$ approach was formulated in our prior work (Tomboulides et al., 2018). The formulation, however, relies on the use of wall distance and its gradients for modeling the closure terms and can pose problems for simulations in complex geometries. This work presents a novel implementation of the $k - τ$ RANS model in Nek5000, where $τ = 1/ω$, eliminating the need for regularization, owing to the asymptotically bounded behavior of the source terms in the $τ$ transport equation, and also eliminating dependence on wall distance. Robustness and stability of the $k - τ$ model is ensured through implicit treatment of the source terms and their careful numerical implementation and demonstrated through several cases aimed at verification and validation. Studies include both canonical and engineering relevant problems, viz., turbulent channel flow, pipe flow, backward facing step, flow over NACA 0012 airfoil and flow in a T-junction. Results from the $k - τ$ model are shown to be consistent with regularized $k - ω$ model and also with the $k - ω$ SST model in OpenFOAM (for select studies). Comparison with experimental data is also shown, where available, to bolster validation efforts for the $k - τ$ model implementation through prediction of key turbulent quantities of interest.

Nek5000↗

Modeling and analysis of synthetic liquid fuel production from CO 2 and nuclear energy using methanol-to-diesel process

Electrofuels (e-fuels) are synthetic fuels produced from carbon dioxide (CO 2 ) and electricity for blending with or replacing petroleum fuels. Nuclear energy is an attractive energy feedstock for e-fuel production because of its low environmental footprint and its ability to provide steady heat and power essential for e-fuels production. We modeled and evaluated the cost and environmental footprint of e-fuels production in the distillate range for three nuclear power scales, 100, 500, and 1000 MWe, through methanol and olefins intermediates leveraging commercial or high technology readiness level (TRL) processes. Compared to the commonly studied e-fuels from Fischer Tropsch process that has a distillate yield of <70% with the rest being low value naphtha, the proposed process via methanol intermediate increases the product selectivity with distillate yield of 96% and only 4% naphtha. The modeled process has a carbon conversion ratio of 98%, and a process energy efficiency of 56% relative to the total equivalent nuclear electricity input. The e-fuel plant economics and GHG emissions were estimated by considering CO 2 collected from ethanol plants adjacent to nuclear power plants. The estimated minimum fuel selling prices (MFSP) of e-fuel is in the range of $5.7-$9.1/gal depending on e-fuel plant scale, electricity cost, and CO 2 transportation distance. The corresponding e-fuels life cycle GHG emissions is estimated in the range of 5-6 gCO 2 e/MJ of liquid fuel using the R&D Greenhouse gases, Regulated Emissions, and Energy use in Technologies (R&D GREET) model.

10 SYNTHETIC FUELS↗

Characterization of in-situ and ex-situ ion-irradiated additively manufactured 316L and 316H stainless steels

Additively manufactured (AM) 316 stainless steel (SS) differs from its wrought counterpart in its unique dislocation cell structure and the presence of segregation and oxide particles at the cell walls. This work investigated the evolution of the microstructure in laser powder bed fusion (LPBF) 316L and 316H SS under in-situ 1 MeV Kr ion irradiation at 600 °C to 5 dpa, and ex-situ 4 MeV Ni ion irradiation at 300 °C and 600 °C from 0.2 dpa to 10 dpa, with a dose rate for all experiments of 10 -3 dpa/s. The results reveal that the dislocation cell structure results in heterogeneous formation of dislocation loops and voids, particularly at 600 °C, where loops tend to form within the cell interiors while voids form at the cell boundaries. LPBF 316H has a reduced level of swelling compared to LPBF 316L due to prolonged incubation. Energy Dispersive X-ray Spectroscopy (EDS) mapping indicates Ni and Si segregation at void surfaces due to radiation-induced segregation. At 300 °C, where voids are absent, the distribution of dislocation loops and stacking fault tetrahedra appears to be uniform. Dislocation cell structures mostly disappeared by 2 dpa for all conditions in this work. M 23 C 6 carbides were observed in LPBF 316H at 600 °C as early as 0.2 dpa, but not in LPBF 316L. Nanoindentation was performed to obtain the hardness of irradiated materials. In conclusion, this work illustrated the influence of additive manufacturing processes on microstructure evolution under irradiation, revealing the differences as well as the similarities as compared with wrought 316 SS, and the AM-related phenomenon that can potentially occur under neutron irradiation in nuclear reactors.

36 - MATERIALS SCIENCE↗

Surface engineering of polymeric membranes with metal oxides for improved fouling resistance and superior oil-water separation

Rapid industrial growth has increased the need for efficient membranes to separate oil-water emulsions. Polyvinylidene fluoride (PVDF) membranes, although widely used due to their chemical inertness and favorable mechanical properties, suffer from fouling due to their intrinsic hydrophobicity. Modifying these membranes after fabrication offers a practical solution as it easily fits into existing large-scale manufacturing processes. Atomic layer deposition (ALD), an atomically-precise vapor phase surface modification technique, can create ultrathin metal oxide layers that greatly improve membrane hydrophilicity without significantly affecting the original pore size. However, PVDF's lack of reactive chemical moieties makes ALD challenging. Here, in this study, we present a simple alkali treatment that greatly enhances ALD nucleation and growth on PVDF membranes. This treatment imparts exceptional oil-water emulsion separation capabilities and antifouling behavior in PVDF membranes after just a few ALD cycles, surpassing the performance of PVDF membranes coated with hundreds of ALD cycles. This dramatic reduction in the number of ALD cycles required could enable cost-effective modification of commercial PVDF membranes at scale using spatial, roll-to-roll ALD. These modified membranes outperform reported modified PVDF membranes, with >99 % permeance recovery and <1 % irreversible loss of permeance and >98 % oil rejection from oil-water emulsions over 100 h continuous operation, making them promising for advanced water purification technologies.

Atomic layer deposition↗

Control of wakefield in sub-THz dielectric-lined waveguides using multiple-bunch excitation

Beam-driven wakefield accelerators offer the potential to achieve accelerating fields approaching the sub-GV/m range, paving the way for compact and cost-effective next-generation high-energy colliders. This method typically employs a two-bunch system: a drive bunch that excites an electromagnetic wakefield in a solid-state or plasma medium, and a witness bunch that extracts energy from the wake for acceleration. Our research focuses on two key challenges in wakefield acceleration using structures. First, we investigate strategies to suppress transverse instabilities by employing non-cylindrical geometries that damp dipole modes. Second, we explore methods to precisely terminate the wakefield after the interaction region, thereby improving the efficiency of energy transfer. This paper presents detailed simulation results and the corresponding experimental design developed to validate these concepts. Furthermore, the proposed experiment will be carried out at the Argonne Wakefield Accelerator (AWA) facility, focusing on controlling wakefield duration through tailored drive and witness bunch configurations and evaluating dielectric-lined structures with non-cylindrical cross sections.

43 PARTICLE ACCELERATORS↗

Beam test performance of AstroPix sensor with 120 GeV protons

AstroPix is a High-Voltage CMOS Monolithic Active Pixel Sensor (HV-CMOS MAPS) developed for precision gamma-ray imaging and spectroscopy in the medium-energy regime, as well as for precise shower imaging and tracking in the Barrel Imaging Calorimeter (BIC) of the Electron Proton/Ion Collider (ePIC) detector at the future Electron–Ion Collider (EIC). We present beam test results of the AstroPix_v3 sensor using a 120 GeV proton beam at the Fermilab Test Beam Facility (FTBF), performed as part of the broader experimental campaign for the BIC prototype calorimeter. The sensor’s 500 µm pixel pitch enabled precise measurement of the beam profile, providing important information for the calorimeter performance studies. Using the measured 120 GeV proton data, we measure the energy deposit of minimum ionizing particles (MIP) and use them to extract the corresponding effective depletion depth at a single bias voltage of −150 V .

AstroPix↗

Quantum fisher information reveals UV-IR mixing in the strange metal

The density-density response in optimally doped Bi 2 Sr 2 CaCu 2 O 8+$x$ has recently been shown to exhibit conformal symmetry. Using, the experimentally inferred conformal dynamic susceptibility, we compute the resultant quantum Fisher information (QFI), a witness to multi-partite entanglement. For a Fermi liquid, we find that the QFI grows quadratically as the temperature increases, consistent then with the phase space available for scattering in the standard theory of metals. By contrast, the QFI in a strange metal increases as a power law at as the temperature decreases, but ultimately extrapolates to a constant at T=0. The constant is of the form, ω$^{2Δ}_g$, where Δ is the conformal dimension and ω g is the UV cutoff which is on the order of the pseudogap. As this constant depends on both UV and IR properties, it illustrates that multipartite entanglement in a strange metal exhibits UV-IR mixing, a benchmark feature of doped Mott insulators as exemplified by dynamical spectral weight transfer. We conclude with a discussion of the implication of our results for low-energy reductions of the Hubbard model.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Knowledge-guided graph machine learning for spatially distributed prediction of daily discharge and nitrogen export dynamics

Spatially distributed prediction of streamflow and nitrogen export dynamics is essential for precision management of agricultural watersheds. While temporal deep learning models such as Long Short-Term Memory (LSTM) have shown strong performance at basin scales, their ability to generalize spatially is limited by insufficient representation of spatial dependencies and flow paths, particularly under data-scarce conditions. To address this gap, we propose HydroGraphNet, a knowledge-guided graph machine learning framework that integrates process-based knowledge and explicit spatial learning into temporal modeling. This framework incorporates directed graph topology to encode watershed connectivity and upstream inflows, with mass balance constraints to improve physical consistency. To enhance generalization in sparsely monitored regions, HydroGraphNet is pretrained on synthetic data generated by the SWAT+ (Soil and Water Assessment Tool Plus) model. We evaluated HydroGraphNet in the Upper Sangamon River Basin (44 HUC-12 subwatersheds, 2001–2020) against two LSTM baselines: a lumped basin-level model and a distributed variant. When benchmarked on SWAT+ simulations in pretraining, HydroGraphNet improved test NSEs by 8.9% (discharge) and 13.7% (NO₃–N load) in temporal extrapolation, and by 27.1% and 34.7% in spatial extrapolation, relative to the Lumped LSTM baseline. After fine-tuning with USGS monitoring data, the model achieved mean test NSE (KGE) scores of 0.768 (0.861) for discharge and 0.626 (0.664) for NO₃–N load, substantially outperforming baselines. Attribution analysis further highlighted the importance of upstream inflow representation and graph-based spatial learning in capturing cross-subwatershed dependencies. The model also reproduced seasonal hydrological and biogeochemical patterns consistent with known processes, demonstrating its robustness and process fidelity for spatially distributed prediction. Altogether, HydroGraphNet advances the integration of physical knowledge and spatially explicit learning in hydrological modeling, offering a generalizable framework for distributed modeling to support spatially targeted water quality management in data-scarce watersheds.

54 ENVIRONMENTAL SCIENCES↗

Population Balance Models for Catalytic Depolymerization: From Elementary Steps to Multiphase Reactors

Here, the ongoing accumulation of plastic waste in landfills and in the environment is driving research on chemical processes and catalysts to recycle polymers. Traditional modeling strategies are not applicable to these processes because they involve too many reactants and intermediates, one for each molecular weight and each functionalization. To model the kinetics, we have developed population balance models (PBMs) that account for macromolecular reactants in the bulk and macromolecular catalytic intermediates. These PBMs couple to each other through polymer adsorption and desorption models and to traditional rate equations for small molecule products and co-reactants (like hydrogen or ethylene). The models, in combination with experimental data, are being used in many ways: (i) to test mechanistic hypotheses, (ii) to extract rate parameters, (iii) to quantitatively compare catalyst activities, (iv) to account for mass transfer and vapor–liquid partitioning in two-phase reactors, and (v) to design novel support architectures and catalysts that mimic the processive action of natural depolymerization enzymes. Some key theoretical advances allow PBMs to be constructed from elementary rates and mechanisms, as opposed to traditional formulations with pseudoelementary rate parameters invoked as fitting parameters. We discuss ways to build these models “bottom-up” from first-principles calculations and ways to extract model parameters from “top down” analyses of rate data. The combination provides a quantitative bridge between first-principles calculations and the kinetics of complex macromolecular transformations for polymer upcycling and beyond.

Manis, Lela K. [University of Illinois at Urbana-C↗

Integrating Experiments and Simulations to Reveal Anisotropic Growth Mechanisms and Interfaces of a One-Dimensional Zeolite

Zeolites are nanoporous crystalline materials critical for diverse industrial applications, yet their growth mechanisms are poorly understood. Here, this study presents a novel integrated framework combining experimental synthesis, high-resolution imaging, coarse-grained molecular dynamics simulations, and computer vision to uncover the mechanisms of growth of SSZ-24, a 1D channel zeolite. We demonstrate how synthesis conditions, such as temperature and reactant concentration, govern crystal anisotropy and surface roughness with growth dynamics differing markedly by crystallographic orientation. Along the channels, growth involves minimal energy barriers and rapid nucleation, resulting in rough surfaces. In contrast, growth perpendicular to the channels requires cooperative molecular organization and is highly sensitive to thermodynamic and kinetic conditions, yielding smooth anisotropic surfaces under low driving forces. By simulating transmission electron microscopy (TEM) images, we bridge molecular-scale simulations with experimental observations, identifying distinct growth mechanisms along different crystal planes. This work offers molecular-level insights into zeolite crystallization, advancing the rational design of nanoporous materials. The integration of cross-disciplinary methodologies establishes a transformative framework for optimizing zeolite synthesis, with implications for broader classes of materials.

Bertolazzo, Andressa A. [Univ. of Utah, Salt Lake ↗

Microstructurally Strained Pyrochlore–Perovskite Biphasic Electrocatalysts for the Oxygen Evolution Reaction

Efficiency of water splitting for hydrogen production is often limited by the sluggish kinetics of multiple electronic transfers required in the heterogeneous oxygen evolution reaction (OER). Catalyst design for reducing the high OER overpotential remains a major scientific challenge. Lattice-strain engineering, a method for tuning the electronic structure and surface geometric configuration of active sites, may greatly affect the interaction between adsorbates and catalytic surfaces for high activity and stability. Here, in this study, we present the synthesis of biphasic oxides of YPrSrRuMnO x , which consists of distinct phases of Y 2 Ru 2 O 7 pyrochlore and (Pr 0.7 Sr 0.3 )MnO 3 perovskite, and the development of a suitable analytical approach to study the strain–catalytic property relationship. Linear sweep voltammetry results reveal that the biphasic oxide exhibits approximately 3.1 times greater mass activity and 2.4 times larger turnover frequency (TOF) than single-phase Y 2 Ru 2 O 7 in the 0.1 M HClO 4 electrolyte. The biphasic catalyst is also about 3 times more stable than the single-phase oxide under acidic conditions. X-ray photoelectron spectroscopy, nitrogen isotherm, and electrochemical surface area analyses indicate that the oxidation state, specific surface area, and electrochemical surface area do not cause enough difference in the observed enhancement of OER performance. We examined the effects of microstrain on electrocatalysis, originating from lattice mismatch between different phases, using three different structural models. Specifically, we compared the Williamson–Hall method, standard stress–strain analysis, and Rietveld refinement in analyzing the structure–property relationship. Strain mapping using geometric phase analysis (GPA) further revealed significant microstrain and lattice dislocations localized near phase boundaries in the biphasic oxide, in contrast to the uniform strain in single-phase materials. The results reveal that the increased microstrain correlates well with the improved OER performance, as the biphasic oxide catalyst exhibits 2–3 times greater microstrain than Y 2 Ru 2 O 7 pyrochlore.

electrocatalysts↗

Effect of Annealing on Direct Recycled NMC Cathodes

A substantial number of electric vehicle batteries are poised to reach end-of-life conditions in the next decade. Direct recycling has advantages over typical recycling processes because it preserves the chemical structure of the material. One key step of direct recycling materials like nickel manganese cobalt oxide (NMC) cathodes is relithiation, which includes replacing the depleted lithium inventory in the cathode and annealing the material to fix crystallographic degradation. This work uses multiple characterization techniques (synchrotron X-ray diffraction, Ni X-ray absorption near edge structure, scanning transmission electron microscopy) to understand the lithiation mechanism of degraded and chemically relithiated NMC 622. Despite the necessary reconstruction after relithiation being limited to the surface of the degraded NMC 622, a high annealing temperature of 720 °C is still necessary to restore the NMC 622 structure back to pristine condition after relithiation. This work also finds that treating degraded NMC 622 with an annealing step is sufficient to restore key electrochemical and structural properties, other essential features of pristine NMC 622 material such as particle porosity and morphology are largely unaffected. Understanding the effect of this annealing step has important implications on defining the degree of success of any given direct recycling strategy.

36 MATERIALS SCIENCE↗

Cell-Free Gene Expression: Methods and Applications

Cell-free gene expression (CFE) systems empower synthetic biologists to build biological molecules and processes outside of living intact cells. The foundational principle is that precise, complex biomolecular transformations can be conducted in purified enzyme or crude cell lysate systems. This concept circumvents mechanisms that have evolved to facilitate species survival, bypasses limitations on molecular transport across the cell wall, and provides a significant departure from traditional, cell-based processes that rely on microscopic cellular “reactors.” In addition, cell-free systems are inherently distributable through freeze-drying, which allows simple distribution before rehydration at the point-of-use. Furthermore, as cell-free systems are nonliving, they provide built-in safeguards for biocontainment without the constraints attendant on genetically modified organisms. These features have led to a significant increase in the development and use of CFE systems over the past two decades. Here, we discuss recent advances in CFE systems and highlight how they are transforming efforts to build cells, control genetic networks, and manufacture biobased products.

59 BASIC BIOLOGICAL SCIENCES↗

Metal–Organic Frameworks as Catalysts for (De)Hydrogenation: Progress, Challenges, and Perspectives

Storing hydrogen through chemical bonding in liquid-organic hydrogen carriers (LOHCs) offers a safer and more practical approach for hydrogen transportation compared to physical liquefaction, which is limited by low volumetric efficiency and gas release. The efficiency of LOHC systems is highly dependent on effective catalysts, which are typically composed of transition metals supported on metal oxides. However, these materials often rely upon costly noble metals, and their nonuniform nature limits mechanistic insights and structure–function relationships that could improve catalyst design. Metal–organic frameworks (MOFs) are promising alternatives to existing catalysts due to their crystalline, tunable, and porous nature. However, their use as catalysts for (de)hydrogenation reactions remains largely underexplored. Related to this, we identify two general classes of MOFs reported as catalysts for (de)hydrogenation reactions: MOFs as scaffolds for catalytically active species and MOFs that function as reactive materials themselves. MOF composites anchor reactive nanoparticles or homogeneous species, imparting reactivity to the framework. The confinement effects experienced by the affixed species, combined with favorable substrate adsorption interactions or acid sites provided by the MOF, enhance the stability, selectivity, and activity of these catalysts for (de)hydrogenation reactions. Additionally, catalytically active MOFs often feature open metal sites at the node or undergo postsynthetic modification at either node or linker to impart reactivity. Here, taking inspiration from these materials, we outline the current state and key challenges of utilizing MOFs as (de)hydrogenation catalysts and propose research pathways to advance materials in this field for energy applications.

Catalysts↗

Enhancing the Quantification of Critical Elements in WTE and Coal Ash via Alkaline Fusion: Superiority of Lithium Metaborate (LiBO 2 )

Ashes generated from coal combustion, as well as waste incineration, can be a potential source of critical elements necessary for the ongoing transition towards electrification and greener energy technologies. For the quantification of critical elements, traditional methods such as acid digestion are time-intensive and can fail to dissolve critical elements in refractory minerals. One potential solution is to adopt alkaline fusion for faster, total digestion. However, the role of flux choice and the subsequent digestion efficiency (DE) is unknown. Here, we report a systematic investigation on the feasibility of alkaline fusion with Lithium Metaborate (LiBO 2 ) and Lithium Tetraborate (Li 2 B 4 O 7 ) as fluxes for the digestion of two standard reference materials (BCR 176R and SRM 1633c). Our findings suggest that LiBO 2 yields higher DE values than Li 2 B 4 O 7 for several critical REEs and volatiles, such as Pb and Cd. Specifically, for REEs in SRM 1633c, the DE values with LiBO 2 are, on average, ~16 percent higher than those with Li 2 B 4 O 7 . Similarly, for Pb and Cd in BCR 176R, the DE values with LiBO 2 are ~20 percent higher than with Li 2 B 4 O 7 . These results suggest that LiBO 2 is a superior flux for rapid ash digestion.

01 COAL, LIGNITE, AND PEAT↗