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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Nitrate Radical Facilitates Indirect Benzyl Alcohol Oxidation on Bismuth(III) Vanadate Photoelectrodes

Bismuth(III) vanadate (BiVO 4 ) films show activity for direct benzyl alcohol (PhCH 2 OH) oxidation to benzaldehyde (PhCHO) in acetonitrile solvent. Introducing tetrabutylammonium nitrate (Bu 4 NNO 3 ) drastically reduces the overpotential required to generate the PhCHO product while maintaining a high faradaic efficiency (FE) >90%. BiVO 4 corrosion accompanies PhCH 2 OH oxidation. However, the presence of nitrate ions (NO 3 - ) results in significantly less bismuth- and vanadium-ion leaching (determined by ICP-MS analysis), as well as reduced surface roughening (determined by SEM imaging). In this reaction, it is proposed that rate-determining NO 3 - oxidation generates a highly reactive nitrate radical (NO 3 ∙) that reacts with PhCH 2 OH by hydrogen-atom abstraction (HAT). NO 3 - is stoichiometrically consumed by the irreversible formation of electrochemically inert HNO 3 , characterized by an EC i mechanism, rather than a catalytic EC' mechanism. In the presence of PhCH 2 OH, NO 3 - oxidation on BiVO 4 becomes more facile; every order of magnitude increase in PhCH 2 OH concentration shifts the NO 3 - / NO 3 ∙ equilibrium potential negatively by 200 mV. The shift results from the introduction of a consumption pathway for the nitrate radical intermediate via a coupled chemical step with benzyl alcohol. This report is the first example of photoelectrochemical NO 3 ∙ generation to initiate indirect PhCH 2 OH oxidation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Degradation Diagnostics from the Subsurface of Lithium-Ion Battery Electrodes

Despite the long-established rocking-chair theory of lithium-ion batteries (LIBs), developing novel characterization methodology with higher spatiotemporal resolution facilitates a better understanding of the solid electrolyte interphase studies to shape the reaction mechanisms. In this work, we develop a Xenon ion plasma focused ion beam (Xe + PFIB)-based characterization technique to probe the cross-sectional interface of both ternary cathode and graphite anode electrodes, with the focus on revealing the chemical composition and distribution underneath the electrode surface by in-depth analysis of secondary ions. Particularly, the lithium fluoride is detected in the pristine cathode prior to contact with the electrolyte, reflecting that the electrode degradation is in the form of the loss of lithium inventory during electrode preparation. This degradation is related to the hydrolysis of the cathode material and the decomposition of the PVDF binder. Here, through the quantitative analysis of the transition-metal degradation products, manganese is found to be the dominant element in the newly formed inactive fluoride deposition on the cathode, while no transition metal signal can be found inside the anode electrode. These insights at high resolution implemented via a PFIB-based characterization technique not only enrich the understanding of the degradation mechanism in the LIBs but also identify and enable a high-sensitivity methodology to obtain the chemical survey at the subsurface, which will help remove the capacity-fade observed in most LIBs.

25 ENERGY STORAGE↗
DOE OSTI2025

Electrocatalytic benchmarking of ruthenium-based bimetallic anodes for the electrocatalytic oxidation of biomass-derived wastewater

In this paper, we report on the synthesis, characterization, and use of ruthenium oxide (RuO 2 ) doped with a secondary metal (M2) to enhance electrochemical activity and stability for the electrocatalytic oxidation (ECO) of biomass-derived wastewaters. We used different electrochemical methods such as cyclic voltammetry (CV), electrochemical surface area (ECSA), and Tafel analysis as well as physical characterization such as grazing incidence X-ray diffraction, X-ray photoelectron spectroscopy, and scanning electron microscopy to understand how the introduction of M2 affects electrochemical performance. Our results show that including an M2 improves the ECO performance regardless of the composition of the electrolyte. Specifically, we saw increase in ECSA, which could be due to enhanced charge transfer for the pH ranges evaluated. Furthermore, the introduction of organic compounds in wastewater generated during the hydrothermal liquefaction of food waste affected the ECO performance differently, depending on M2, the electrolyte composition, and anodic half-cell potential, highlighting the need to properly control the reaction conditions when testing and characterizing the electrocatalysts under different reaction regimes. We developed an in situ electrocatalytic benchmarking protocol, Boruah – Lopez-Ruiz – Strange (BLoRS), to quickly assess if the presence of M2 improves the ECO performance; thus, saving time and resources in ex situ characterization, testing, and product analysis. This foundational work provides the basis for characterization and benchmarking of electrodes of the ECO of organic compounds.

Electrocatalysis↗
DOE OSTI2022

Partitioning behavior and mechanisms of rare earth elements during precipitation in acid mine drainage

Rare earth elements (REEs) are frequently found concentrated in acid mine drainage (AMD). The recovery of REEs from AMD has been successfully achieved using selective chemical precipitation. However, a portion of the REEs is often lost to the precipitates of the dominant metal contaminant ions. To better understand the REE partitioning behavior and mechanisms during the precipitation process, a systematic study was performed on both natural and synthetic AMD solutions. Precipitation test results show that REE removal was noticeably elevated at pH 4.0 after adding H 2 O 2 to convert ferrous to ferric ions, causing nearly complete precipitation of iron. Solution equilibrium calculations suggested that the REE removal increase was realized through adsorption onto the surfaces of the ferric precipitates. The presence of aluminum species in the solutions reduced the adsorption of REEs on the ferric precipitates. Based on electro-kinetic test results, it was concluded that aluminum species neutralize the negative surface charge of the ferric precipitates and compete with REEs for the adsorption active sites. The presence of ferrous ions in the solutions reduced REE adsorption on the aluminum precipitates at lower pH values (e.g., 5.0) due to competitive adsorption. However, at higher pH values (e.g., 6.0), REE removal to the precipitate product increased due to the precipitation of ferrous ions. Additionally, to the electro-kinetic tests and solution equilibrium calculations, mineralogy characterization, specific surface area measurement, particle size analysis, and morphology analysis were also conducted to investigate and identify the partitioning mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Liquid lithium wetting and percolation in a porous tungsten/liquid Li plasma facing component (PFC)

This work explores the concept of a hybrid material system designed to protect the plasma from high-Z material emission while also protecting an underlying high-Z wall material from erosion by integrating a low-Z component in the liquid phase. Plasma-surface interaction properties of a porous tungsten (W)-liquid metal hybrid system, having the favorable bulk thermomechanical properties of W while serving as a scaffold for a liquid metal with self-healing and radiative vapor shielding characteristics, are examined. W-substrates with 70% density of bulk W and 1–5 μm sized pores have been fabricated with 50-nm W powders using spark plasma sintering. Enhanced lithium (Li) wettability, driven by percolation through the porous W architecture, is demonstrated with in-situ liquid Li drop measurements. Finally, results show complete wetting of liquid Li at 250 °C in the porous W, 100 °C lower temperature than what has been observed on traditional W surfaces. In operando ion beam analysis of Li films deposited on porous W substrates provides microscopic evidence of Li percolation into the substrate and a first look at D retention up to a depth of 100 nm after plasma exposure at a flux of 10 20 m –2 s –1 , 250 eV/amu D + plasma to a fluence of 1.16 × 10 23 m –2 at a temperature of 200 °C.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Evaluating the Rheo-electric Performance of Aqueous Suspensions of Oxidized Carbon Black

Here, the macroscopic properties of carbon black suspensions are primarily determined by the agglomerate microstructure built of primary aggregates. Conferring colloidal stability in aqueous carbon black suspensions should thus have a drastic impact on their viscosity and conductivity. Carbon black was treated with strong acids following a wet oxidation procedure. An analysis of the resulting particle surface chemistry and electrophoretic mobility was performed in evaluating colloidal stability. Changes in suspension microstructure due to oxidation were observed using small-angle X-ray scattering. Utilizing rheo-electric measurements, the evolution of the viscosity and conductivity of the carbon black suspensions as a function of shear rate and carbon content was thoroughly studied. The carboxyl groups installed on the carbon black surface through oxidation increased the surface charge density and enhanced repulsive interactions. Electrostatic stability inhibited the formation of the large-scale agglomerates in favor of the stable primary aggregates in suspension. While shear thinning, suspension conductivities were found to be weakly dependent on the shear intensity regardless of the carbon content. Most importantly, aqueous carbon black suspensions formulated from electrostatically repulsive primary aggregates displayed a smaller rise in conductivity with carbon content compared to those formulated from attractive agglomerates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Degradation and recovery of solid oxide fuel cell performance by control of cathode surface acidity: Case study – Impact of Cr followed by Ca infiltration

Solid oxide fuel cells (SOFC) have attracted attention as clean and efficient energy conversion devices with low emissions. However, several degradation mechanisms limit the electrochemical performance of current SOFCs, with cathode degradation due to Cr-poisoning from metal interconnects particularly problematic. The acidity/basicity of binary additives has been found to be a sensitive descriptor of the oxygen exchange kinetics, indicating that acidic Cr-species/basic Ca-species can be expected to deactivate/activate the cathode surface, respectively. Inspired by recent advances, the feasibility of relative acidity as a tool for reviving degraded SOFCs is demonstrated by neutralizing Cr-poisoned SOFCs by subsequent serial infiltration of Ca-species. Furthermore, a model mixed ionic and electronic conducting oxide, Pr 0.1 Ce 0.9 O 2-δ (PCO), is selected as the cathode material. Area-specific resistances (ASR) of symmetric cells obtained by electrochemical impedance spectroscopy show that Cr-infiltration results in a seven-fold increase in ASR, while subsequent infiltration of Ca-species leads to complete recovery. Performance degradation and recovery are attributed to depressed/enhanced redox properties at the PCO surface, as supported by XPS analysis. Experiments using anode-supported fuel cells show a reduction in peak power density by 26% upon Cr-infiltration, reversed following Ca-infiltration, after which no degradation is observed during subsequent operation for 100 h.

(Pr,Ce)O2-δ↗
DOE OSTI2024

A Deep Learning-Driven Sampling Technique to Explore the Phase Space of an RNA Stem-Loop

The folding and unfolding of RNA stem-loops are critical biological processes; however, their computational studies are often hampered by the ruggedness of their folding landscape, necessitating long simulation times at the atomistic scale. Here, we adapted DeepDriveMD (DDMD), an advanced deep learning-driven sampling technique originally developed for protein folding, to address the challenges of RNA stem-loop folding. Although tempering- and order parameter-based techniques are commonly used for similar rare-event problems, the computational costs or the need for a priori knowledge about the system often present a challenge in their effective use. DDMD overcomes these challenges by adaptively learning from an ensemble of running MD simulations using generic contact maps as the raw input. DeepDriveMD enables on-the-fly learning of a low-dimensional latent representation and guides the simulation toward the undersampled regions while optimizing the resources to explore the relevant parts of the phase space. We showed that DDMD estimates the free energy landscape of the RNA stem-loop reasonably well at room temperature. Our simulation framework runs at a constant temperature without external biasing potential, hence preserving the information on transition rates, with a computational cost much lower than that of the simulations performed with external biasing potentials. Here, we also introduced a reweighting strategy for obtaining unbiased free energy surfaces and presented a qualitative analysis of the latent space. This analysis showed that the latent space captures the relevant slow degrees of freedom for the RNA folding problem of interest. Finally, throughout the manuscript, we outlined how different parameters are selected and optimized to adapt DDMD for this system. We believe this compendium of decision-making processes will help new users adapt this technique for the rare-event sampling problems of their interest.

Gupta, Ayush↗
DOE OSTI2022

Enabling Silicon Anodes with Novel Isosorbide-Based Electrolytes

Silicon is seen as one of the most promising anode candidates for next-generation lithium-ion batteries, due to its high theoretical capacity and energy density. However, many technical barriers remain to its implementation, due to its high chemical/electrochemical reactivities with standard electrolytes and incomplete passivation from large volume changes. Herein, we report an isosorbide dimethyl ether (IDE) based electrolyte, which exhibits greatly improved stability, as evidenced by long cycle life and calendar life. An analysis of the cycled silicon surface shows minimal decomposition of organic species from IDE solvent, confirming that the electrolyte maintains a limited chemical reactivity with nucleophilic lithiated silicon (Li x Si). Here, this research opens up new avenues for designing new electrolytes which could ultimately enable the practical application of silicon anodes.

25 ENERGY STORAGE↗
DOE OSTI2022

Developing a Chemical and Structural Understanding of the Surface Oxide in a Niobium Superconducting Qubit

We report superconducting thin films of niobium have been extensively employed in transmon qubit architectures. Although these architectures have demonstrated remarkable improvements in recent years, further improvements in performance through materials engineering will aid in large-scale deployment. Here, we use information retrieved from secondary ion mass spectrometry and electron microscopy to conduct a detailed assessment of the surface oxide that forms in ambient conditions for transmon test qubit devices patterned from a niobium film. We observe that this oxide exhibits a varying stoichiometry with NbO and NbO 2 found closer to the niobium film and Nb 2 O 5 found closer to the surface. In terms of structural analysis, we find that the Nb 2 O 5 region is semicrystalline in nature and exhibits randomly oriented grains on the order of 1-2 nm corresponding to monoclinic N-Nb 2 O 5 that are dispersed throughout an amorphous matrix. Using fluctuation electron microscopy, we are able to map the relative crystallinity in the Nb 2 O 5 region with nanometer spatial resolution. Through this correlative method, we observe that amorphous regions are more likely to contain oxygen vacancies and exhibit weaker bonds between the niobium and oxygen atoms. Based on these findings, we expect that oxygen vacancies likely serve as a decoherence mechanism in quantum systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A deep learning approach for semantic segmentation of unbalanced data in electron tomography of catalytic materials

In computed TEM tomography, image segmentation represents one of the most basic tasks with implications not only for 3D volume visualization, but more importantly for quantitative 3D analysis. In case of large and complex 3D data sets, segmentation can be an extremely difficult and laborious task, and thus has been one of the biggest hurdles for comprehensive 3D analysis. Heterogeneous catalysts have complex surface and bulk structures, and often sparse distribution of catalytic particles with relatively poor intrinsic contrast, which possess a unique challenge for image segmentation, including the current state-of-the-art deep learning methods. To tackle this problem, we apply a deep learning-based approach for the multi-class semantic segmentation of a γ-Alumina/Pt catalytic material in a class imbalance situation. Specifically, we used the weighted focal loss as a loss function and attached it to the U-Net’s fully convolutional network architecture. We assessed the accuracy of our results using Dice similarity coefficient (DSC), recall, precision, and Hausdorff distance (HD) metrics on the overlap between the ground-truth and predicted segmentations. Our adopted U-Net model with the weighted focal loss function achieved an average DSC score of 0.96 ± 0.003 in the γ-Alumina support material and 0.84 ± 0.03 in the Pt NPs segmentation tasks. We report an average boundary-overlap error of less than 2 nm at the 90th percentile of HD for γ-Alumina and Pt NPs segmentations. The complex surface morphology of γ-Alumina and its relation to the Pt NPs were visualized in 3D by the deep learning-assisted automatic segmentation of a large data set of high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) tomography reconstructions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Identification of the defect dominating high temperature reverse leakage current in vertical GaN power diodes through deep level transient spectroscopy

Deep level defects in wide bandgap semiconductors, whose response times are in the range of power converter switching times, can have a significant effect on converter efficiency. We use Deep Level Transient Spectroscopy (DLTS) to evaluate such defect levels in the n- drift layer of vertical GaN (v-GaN) power diodes with VBD ~ 1500 V. DLTS reveals three energy levels that are at ~0.6 eV (highest density), ~0.27 eV (lowest density) and ~ 45 meV (a dopant level) from the conduction band. Dopant extraction from Capacitance-Voltage measurement test (C-V) at multiple temperatures enables trap density evaluation, and the ~0.6 eV trap has a density of 1.2 × 10 15 cm -3 . Here, the 0.6 eV energy level and its density are similar to a defect that is known to cause current collapse in GaN based surface conducting devices (like HEMTs). Analysis of reverse bias currents over temperature in the v-GaN diodes indicates a predominant role of the same defect in determining reverse leakage current at high temperatures, reducing switching efficiency.

42 ENGINEERING↗
DOE OSTI2024

AuriDESI: mock catalogues for the DESI Milky Way Survey

The Dark Energy Spectroscopic Instrument Milky Way Survey (DESI MWS) will explore the assembly history of the Milky Way by characterizing remnants of ancient dwarf galaxy accretion events and improving constraints on the distribution of dark matter in the outer halo. We present mock catalogues that reproduce the selection criteria of MWS and the format of the final MWS data set. These catalogues can be used to test methods for quantifying the properties of stellar halo substructure and reconstructing the Milky Way’s accretion history with the MWS data, including the effects of halo-to-halo variance. The mock catalogues are based on a phase-space kernel expansion technique applied to star particles in the Auriga suite of six high-resolution lambda-cold dark matter magnetohydrodynamic zoom-in simulations. They include photometric properties (and associated errors) used in DESI target selection and the outputs of the MWS spectral analysis pipeline (radial velocity, metallicity, surface gravity, and temperature). They also include information from the underlying simulation, such as the total gravitational potential and information on the progenitors of accreted halo stars. We discuss how the subset of halo stars observable by MWS in these simulations corresponds to their true content and properties. These mock Milky Ways have rich accretion histories, resulting in a large number of substructures that span the whole stellar halo out to large distances and have substantial overlap in the space of orbital energy and angular momentum.

dynamics↗
DOE OSTI2025

Unified Picture of Superconductivity and Magnetism in CeRh 2 ⁢As 2

Here, we propose a theory for the microscopic origin of the multiple superconducting and magnetic phases observed in CeRh 2 ⁢As 2 based on the existence of Van Hove singularities near the Fermi energy. The nonsymmorphic symmetry of this material implies that these singularities are located away from high-symmetry momenta; i.e., they have so-called type-II character. This allows us to include the significant Rashba spin-orbit coupling in CeRh 2 ⁢As 2 in a parquet renormalization group approach. When Fermi-surface nesting is strong, our analysis reveals two closely competing superconducting states with opposite parities, as well as an instability toward spin-density wave states that support both of them, consistent with the phase diagram of CeRh 2 ⁢As 2 . Type-II Van Hove singularities are generic to nonsymmorphic space groups, and so our theory implies that many other compounds may support closely competing even- and odd-parity superconductivity.

Rashba coupling↗
DOE OSTI2024

Atmospheric Variability Drives Anomalies in the Bering Sea Air–Sea Heat Exchange

Abstract High latitudes, including the Bering Sea, are experiencing unprecedented rates of change. Long-term Bering Sea warming trends have been identified, and marine heatwaves (MHWs), event-scale elevated sea surface temperature (SST) extremes, have also increased in frequency and longevity in recent years. Recent work has shown that variability in air–sea coupling plays a dominant role in driving Bering Sea upper-ocean thermal variability and that surface forcing has driven an increase in the occurrence of positive ocean temperature anomalies since 2010. In this work, we characterize the drivers of the anomalous surface air–sea heat fluxes in the Bering Sea over the period 2010–22 using ERA5 fields. We show that the surface turbulent heat flux dominates the net surface heat flux variability from September to April and is primarily a result of near-surface air temperature and specific humidity anomalies. The airmass anomalies that account for the majority of the turbulent heat flux variability are a function of wind direction, with southerly (northerly) wind advecting anomalously warm (cool), moist (dry) air over the Bering Sea, resulting in positive (negative) surface turbulent flux anomalies. During the remaining months of the year, anomalies in the surface radiative fluxes account for the majority of the net surface heat flux variability and are a result of anomalous cloud coverage, anomalous lower-tropospheric virtual temperature, and sea ice coverage variability. Our results indicate that atmospheric variability drives much of the Bering Sea upper-ocean temperature variability through the mediation of the surface heat fluxes during the analysis period. Significance Statement A long-term ocean warming trend and a recent increase in marine heatwaves in the Bering Sea have been identified. Previous work showed that anomalies in the exchange of heat between the ocean and the atmosphere were the primary driver of Bering Sea temperature variability, but the processes responsible for the heat exchange anomalies were unknown. In this work, we show that the atmosphere is the primary driver of anomalies in the Bering Sea air–sea heat exchange and therefore plays an important role in altering the thermal state of the Bering Sea. Our results highlight the importance of understanding more about how the ocean and the atmosphere interact at high latitudes and how this relationship will be affected by future climate change.

Hayden, Emily E. [a College of Earth, Ocean, and A↗
DOE OSTI2020

Comparison of damage and ablation dynamics of multilayer dielectric films initiated by few-cycle pulses versus longer femtosecond pulses

The importance of high intensity few- to single-cycle laser pulses for applications such as intense isolated attosecond pulse generation is constantly growing, and with the breakdown of the monochromatic approximation in field ionization models, the few-cycle pulse (FCP) interaction with solids near the damage threshold has ushered a new paradigm of nonperturbative light–matter interaction. In this Letter, we systematically study and contrast how femtosecond laser-induced damage and ablation behaviors of SiO 2 /HfO 2 -based reflective multilayer dielectric thin film systems vary between FCP and 110 fs pulses. With time-resolved surface microscopy and ex situ analysis, we show that there are distinct differences in the interaction depending on the pulse duration, specifically in the “blister” morphology formation at lower fluences (damage) as well as in the dynamics of debris formation at higher fluences (ablation).

42 ENGINEERING↗
DOE OSTI2020

Charged Microdroplets in Air: Characterization and Use in Surface Functionalization and Nanomaterials Preparation (Final Technical Report)

The major theme of this project is the exploration of ions and charged droplets in the open air. The specific goals are (1) focusing ions in the open air, (2) separating and measuring the sizes of charged droplets, (3) examining chemical reactions occurring within droplets, (4) examining chemical reactions occurring between charged droplets and chemical vapors, and (5) characterizing surfaces post droplet deposition. The analysis of ions in the open air greatly simplifies instrumentation as it removes the need for large, costly vacuum pumps. Major strides in this project include the sizing of electrospray droplets using structured illumination microscopy, 3D printed drift tube ion mobility (both standalone and coupled with mass spectrometry), and accelerated Suzuki reactions in Leidenfrost droplets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Particle scale impacts on deconstruction energy of pine residues

The goal of this Case Study was to quantify the impacts of variable moisture and ash on hammer mill throughput and energy consumption and on generation of fines that are not able to be fed to conversion, as compared to a status quo Base Case system. Also considered was convertible carbon content (minimum carbon specification) and maximum ash content and the delivered feedstock cost impacts of not being able to feed residue not meeting both specifications to the conversion reactor. Laboratory data on the impacts of input particle size and moisture content on the exit particle size were received from FCIC Subtask 5.2 from their single particle impact population balance modeling study. Additional throughput and energy consumption data were obtained from FCIC Subtask 5.2 for the same grinder with a 6 mm screen in place. These data were utilized to develop the necessary response surface equations to perform throughput analysis using discrete event simulation. Because the ash contents in the separated fines had not been analyzed in the laboratory at the time of the model runs, we chose to assume that the ash distributed proportionally with total mass into the overs and unders in the disk screen following grinding. Key takeaways from this Case Study are that it is significantly more cost effective to hammer mill the residue prior to drying, even though the grinder throughput is lower and energy consumption is higher versus drying first before grinding. An effect of dry grinding versus high moisture grinding is the production of higher amounts of fines during dry grinding, leading to significantly more of the ground feedstock being rejected by conversion for being below a minimum particle size. With wet grinding the system is still able to produce more preprocessed feedstock meeting the minimum particle size specification even though the instantaneous throughput is lower than for the case of grinding dry feedstock. Additionally, even without the higher fines production from dry grinding, the status quo would still be more costly than wet grinding because the material is rejected after the drying energy has already been input for the dry grinding case. Finally, significant reductions in drying energy are obtained by drying after grinding, and those reductions are of far greater magnitude than the grinding energy increase.

09 BIOMASS FUELS↗