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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Nitrogen Vacancy Centers in Diamond for Stress Sensing Applications: Theory and Experiments

Sensing of stress under high elevated environmental conditions with high resolution has critical importance for range of applications including earth’s subsurface scanning and geological CO2 storage monitoring. Using first principles density functional theory (DFT) approach combined with the theoretical modelling of low energy Hamiltonian, here we investigate a novel approach to detect unprecedented level of pressure by taking advantage of solid-state electron’s spin of Nitrogen vacancy (NV) centers in nanodiamond. We computationally explore the effect of strain on the defect band edges and band gaps by varying the lattice parameters of diamond supercell hosting a single NV center. A low energy Hamiltonian is developed that includes effect of stress on the energy level of ±1 spin manifold at the ground state. By quantifying the energy level shift and split, we predict the pressure sensing of up to 0.3 MPa/√Hz. We show superiority of the quantum sensing over traditional optical sensing techniques by discussing our results from DFT and theoretical modelling for the frequency shift per unit pressure. The proposed quantum stress sensing could be useful to measure earth’s subsurface vibrations. Our results open avenues for development of sensing technology with a high sensitivity and resolution under extreme pressure conditions that potentially has a wider applicability than existing pressure sensing technologies.

Paudel, Hari P.↗
DOE OSTI2026

3D TRISO particle-explicit compact meshing

The TRI-structural ISOtropic (TRISO) layered fuel particle is a robust nuclear fuel form offering enhanced safety and performance for advanced reactor concepts, including high-temperature gas-cooled reactors and other Generation IV designs. These poppy-seed-sized particles are embedded in a graphite matrix to form fuel elements that must withstand elevated temperatures and high burn-up levels. The heterogeneous nature of these fuel elements — comprising thousands of randomly distributed TRISO particles — produces complex stress fields and thermal gradients that one- and two-dimensional models cannot accurately capture. While three-dimensional modeling has improved predictions of dimensional changes, internal pressure buildup, and fission product transport under irradiation, current approaches rely on homogenized material properties that are known to have considerable divergence from experimental observations. This work presents a methodology for optimized random packing of TRISO fuel compacts and full three-dimensional mesh generation within the BISON fuel performance code, with each particle coating layer individually discretized. The resulting mesh was demonstrated through heat conduction simulations under representative in-reactor operating conditions, showing strong agreement with expected behavior. This capability enables detailed analysis of particle-to-particle interactions, matrix cracking mechanisms, and the statistical distribution of coating layer failures — all of which directly govern fuel performance and safety margins.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Improving MicroBooNE's Inclusive Single-Photon Search with Low-Energy Hadronic Identification

This analysis aims to further investigate MicroBooNE’s inclusive single-photon search results, which reported a 2.2$\sigma$ excess below 600 MeV in shower energy for events with no reconstructed protons using roughly half of MicroBooNE's dataset. Taken together with MiniBooNE’s long-standing low-energy excess and MicroBooNE’s recent electron-like search results showing no observable excess with respect to Standard Model predictions, this result provides strong impetus for expanded exploration of the single-photon channel in Fermilab’s short-baseline liquid-argon time projection chamber (LArTPC) experiments. By identifying and classifying isolated MeV-scale energy depositions, or blips, in the vicinity of single-photon events selected by the Wire-Cell reconstruction framework, we establish a more comprehensive labeling scheme for nearby hadronic content. In particular, blips found backwards along the shower axis indicate the presence of previously-unidentified final-state protons, while elevated blip counts at wide angles signal the presence of final-state neutrons. By applying this new technique to its full dataset, MicroBooNE will perform a purer and higher-statistics test of the truly isolated nature of its modest photon-like excess, furthering its hunt for the presence of unexpected new physics beyond the Standard Model.

Andrade Aldana, Diego [Los Alamos; IIT, Chicago (m↗
DOE OSTI2022

Anthropogenic sulfate aerosol pollution in South and East Asia induces increased summer precipitation over arid Central Asia

Precipitation has increased across the arid Central Asia region over recent decades. However, the underlying mechanisms of this trend are poorly understood. Here, we analyze multi-model simulations from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP) to investigate potential drivers of the observed precipitation trend. We find that anthropogenic sulfate aerosols over remote polluted regions in South and East Asia lead to increased summer precipitation, especially convective and extreme precipitation, in arid Central Asia. Elevated concentrations of sulfate aerosols over remote polluted Asia cause an equatorward shift of the Asian Westerly Jet Stream through a fast response to cooling of the local atmosphere at mid-latitudes. This shift favours moisture supply from low-latitudes and moisture flux convergence over arid Central Asia, which is confirmed by a moisture budget analysis. High levels of absorbing black carbon lead to opposing changes in the Asian Westerly Jet Stream and reduced local precipitation, which can mask the impact of sulfate aerosols. This teleconnection between arid Central Asia precipitation and anthropogenic aerosols in remote Asian polluted regions highlights long-range impacts of anthropogenic aerosols on atmospheric circulations and the hydrological cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Denudation, solute export, landscape evolution modeling, and geographic information system data for the East River watershed, Colorado, USA (2020-2024)

This data package contains geographic information system (GIS) layers and tabular datasets associated with the study of lithologic controls on denudation, solute export, carbon-scaling relationships, and transient landscape evolution in the East River watershed near Crested Butte, Colorado, USA. The package includes GIS layers used to produce the Figure 2 map, including drainage, hillshade, lithology, sample locations, and basin polygons, together with comma-separated value (CSV) tables and matching CSV data dictionaries. One group of tables reports sample-level and catchment-level information for river-sediment samples analyzed for in situ-produced cosmogenic beryllium-10 (10Be), including sample names, outlet elevations, geographic coordinates, upstream drainage area, rock-type classes, production-rate scaling scheme, analyzed nuclide, catchment-averaged denudation rates, and associated lower and upper analytical uncertainties. Sample and catchment attributes provide the basis for comparing denudation rates across intrusive, shale, sedimentary, and mixed-lithology settings. A second group of tables reports supporting information for landscape-evolution modeling and the mapped geologic framework of the study area. Included files list parameter values and definitions for the two-phase landscape-evolution simulations, summarize full-domain model erosion fluxes and topographic metrics for different simulation configurations, provide a fixed-area carbon-model scaling table, and summarize mapped geologic units within the East River study domain, including geologic code, formation name, lithologic description, mapped area, and lithologic class grouping. Model outputs and geologic summaries support interpretation of transient landscape behavior and its relation to the mapped distribution of shale, intrusive, sedimentary, and surficial units. A third group of tables reports hydrologic and hydrochemical information used to quantify dissolved export from the watershed. Included files provide site-level values for drainage area, mean annual solute export, standard error of annual export, area-normalized solute yield, and equivalent weathering rate for five East River monitoring sites, along with metadata describing the number, sampling cadence, and date range of discharge records and partial and full total dissolved solids observations used in the solute-yield analyses. The package also contains a supplementary daily ion-load time series with daily mean discharge, discharge observation counts, dissolved concentrations, and daily loads for calcium, magnesium, sodium, potassium, chloride, sulfate, nitrate, fluoride, dissolved silica, charge-balance bicarbonate, and total dissolved solids. The package contains GIS files, comma-separated value files (.csv), CSV data dictionaries, a file-level metadata table, a package-tree text file, and a readme text file.

10Be↗
DOE OSTI2021

Multi-cyclone analysis and machine learning model implications of cyclone effects on forests

Past studies of cyclones (hurricanes, typhoons, tropical cyclones) disturbance showed that meteorological, topographical, and biological factors affect the patterns of forest disturbance intensity but left open the extent to which these findings were representative across different global cyclone regions. Using remote sensing data and machine learning models, we examined how these factors change over spatial scales and assessed their consistency across four major cyclones: Katrina (August 2005), Rita (September 2005), Yasi (February 2011), and María (September 2017). Our results revealed that the factors which best explained forest disturbance intensity pattern varied across these regions. Wind speed and precipitation were the dominant factors contributing to the variation in impacts of Katrina; terrain features, especially elevation, explained most of the variation in disturbance intensity of Rita; pre-disturbance vegetation condition was significant predictors of effects of Yasi; these factors played equal roles in explaining the disturbance intensity variation of María. A 40 m/s (144 km/h) wind speed threshold was proposed to split low- and high-level forest disturbance intensity. Other than wind speed, few generalizations can be made on features across multiple regions. We built several generalized hurricane impact models, which worked well with the test data from cyclones used for model development (R 2 = 0.89). However, these models did not have good predictions on other cyclones, such as Michael (October 2018) and Laura (August 2020). This study showed that each cyclone interacted with the landscape in a unique way and the challenges remained in building a generalized cyclone impact model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Divergent selection and climate adaptation fuel genomic differentiation between sister species of Sphagnum (peat moss)

Abstract Background and Aims New plant species can evolve through the reinforcement of reproductive isolation via local adaptation along habitat gradients. Peat mosses (Sphagnaceae) are an emerging model system for the study of evolutionary genomics and have well-documented niche differentiation among species. Recent molecular studies have demonstrated that the globally distributed species Sphagnum magellanicum is a complex of morphologically cryptic lineages that are phylogenetically and ecologically distinct. Here, we describe the architecture of genomic differentiation between two sister species in this complex known from eastern North America: the northern S. diabolicum and the largely southern S. magniae. Methods We sampled plant populations from across a latitudinal gradient in eastern North America and performed whole genome and restriction-site associated DNA sequencing. These sequencing data were then analyzed computationally. Key Results Using sliding-window population genetic analyses we find that differentiation is concentrated within ‘islands’ of the genome spanning up to 400 kb that are characterized by elevated genetic divergence, suppressed recombination, reduced nucleotide diversity and increased rates of non-synonymous substitution. Sequence variants that are significantly associated with genetic structure and bioclimatic variables occur within genes that have functional enrichment for biological processes including abiotic stress response, photoperiodism and hormone-mediated signalling. Demographic modelling demonstrates that these two species diverged no more than 225 000 generations ago with secondary contact occurring where their ranges overlap. Conclusions We suggest that this heterogeneity of genomic differentiation is a result of linked selection and reflects the role of local adaptation to contrasting climatic zones in driving speciation. This research provides insight into the process of speciation in a group of ecologically important plants and strengthens our predictive understanding of how plant populations will respond as Earth’s climate rapidly changes.

58 GEOSCIENCES↗
DOE OSTI2021

ACBD3 is up-regulated in gastric cancer and promotes cell cycle G1-to-S transition in an AKT-dependent manner

Highlights: • ACBD3 is up-regulated in gastric cancer. • ACBD3 regulates cell-cycle of gastric cancer in an AKT-dependent manner. It has been reported that ACBD3 is closely related to the malignant process of cells, but its role in gastric cancer has not been elucidated. This study aims to investigate the expression and function of ACBD3 in human gastric cancer. The Cancer Genome Atlas (TCGA) database were selected to analyze mRNA levels of ACBD3 in gastric cancer tissues and normal gastric epithelial tissues. qPCR and Western blot were conducted to detect the expression of ACBD3 in two normal gastric epithelial cell lines and five gastric cancer cell lines which were cultured in our laboratory. To exclude differences in individual background between different patients, we further detected the expression of ACBD3 in 8 pairs of malignant/non-malignant clinical gastric tissues. Through the establishment of stable cells, in vitro cell experiments and in vivo xenotransplantation models in mice, the role of ACBD3 in the proliferation of gastric cancer cells has been further explored. AKT inhibitors were used to deeply explore the molecular regulation mechanism of ACBD3. The results showed that the elevated ACBD3 in gastric cancer tissue were positively correlated with the clinical grade and prognosis of gastric cancer. In terms of molecular function, we found that ACBD3 can enhance the production and growth of gastric cancer cells. At the same time, the activation of AKT kinase played an important role in ACBD3's promotion of G1-to-S transition. The experiments generally indicate that ACBD3 is expected to become a potential diagnostic molecule or therapeutic target for gastric cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Quantum Chemistry-Driven Machine Learning Approach for the Prediction of the Surface Tension and Speed of Sound in Ionic Liquids

Ionic liquids (ILs) have unique solvent properties and have thus garnered significant interest. However, exhaustive experimental determination of the physicochemical properties of ILs is unrealistic due to the large structural diversity of anions and cations, their high cost, the requirements of elevated temperature and pressure, and the time required. To circumvent these experimental costs, computational approaches to accurately calculate these properties have emerged. Here in the present study, we present a demonstration of two machine learning (ML) models for the prediction of two critical IL physical properties, the surface tension and the speed of sound, across a wide range of temperatures and pressures. The models make use of molecular descriptors derived from the COSMO-RS, a quantum chemical-based model. The ML models show excellent agreement with experimental observations, with an R2 value of 0.96–0.99 and RMSE of 1.71 mN/m and 16.12 m/s for the surface tension and speed of sound, respectively. This work paves the way for the development of COSMO-RS-informed ML models for the prediction of IL properties which can help to further optimize and accelerate technology development for ILs.

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

Climate-Driven Limits to Future Carbon Storage in California's Wildland Ecosystems

Enhanced ecosystem carbon storage is a key component of many climate mitigation pathways. The State of California has set an ambitious goal of carbon neutrality by 2045, relying in part on enhanced carbon sequestration in natural and working lands. We used statistical modeling, including random forest and climate analog approaches, to explore the climate-driven challenges and uncertainties associated with the goal of long-term carbon sequestration in forests and shrublands. We found that seasonal patterns of temperature and precipitation are strong controllers of the spatial distribution of aboveground live carbon. RCP8.5 projections of temperature and precipitation are estimated to drive decreases of 16.1% ± 7.5% in aboveground live carbon by the end of the century, with coastal areas of central and northern California and low/mid-elevation mountain areas being most vulnerable. With RCP4.5 projections, declines are less severe, with 8.8% ± 5.3% carbon loss. In either scenario, increases in temperature systematically cause biomass declines, and the spread of projected precipitation across 32 CMIP5 models contributes to substantial uncertainty in the magnitude of that decline. Projected changes in the environmental niche for the 20 most biomass-dominant tree species revealed widespread replacement of conifers by oak species in low elevation regions of central and northern California, with a corresponding decline in carbon storage depending on expected migration rates. The spatial patterns of vulnerability we identify may allow policymakers to assess where carbon sequestration in aboveground biomass is an appropriate part of a climate mitigation portfolio, and where future climate-driven carbon losses may be a liability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Mesoscale Convective Systems Modulated by Convectively Coupled Equatorial Waves

Mesoscale convective systems (MCSs) produce over 50% of tropical precipitation and account for the majority of extreme rainfall and flooding events. MCSs are considered the building blocks of larger-scale convectively coupled equatorial waves (CCEWs). While CCEWs can provide favorable environments for convection, how CCEWs can systematically impact organized convection and thereby MCS characteristics is less clear. We examine this question by analyzing a global MCS tracking data set. During the active phase of CCEWs, MCS frequency increases and MCSs rain harder, produce more lifetime total rain, and grow larger in size. The probability of extreme MCSs also elevates. These changes are most pronounced when MCSs are associated with Kelvin waves and tropical depression-type waves while less so with the Madden-Julian Oscillation. Furthermore, these results can be benchmarks to improve model representation of MCS interactions with large-scale circulations and can be leveraged for operational forecasts of high-impact MCSs at extended lead times.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Value-added catalog of physical properties for more than 1.3 million galaxies from the DESI survey

We present an extensive catalog of the physical properties of more than a million galaxies investigated with the Dark Energy Spectroscopic Instrument (DESI), one of the largest spectroscopic surveys to date. Spanning a full range of target types, including emission-line galaxies, luminous red galaxies, and quasars, our survey encompasses an unprecedented range of spectroscopic redshifts, all the way from 0 to 6. The physical properties, such as stellar masses and star formation rates, were derived via the CIGALE spectral energy distribution (SED) fitting code accounting for the contribution coming from active galactic nuclei (AGNs). Based on the modeling of the optical-mid-infrared (grz supplemented with WISE photometry) SEDs, we studied the galaxy properties with respect to their location on the main sequence. We have revised the dependence of stellar mass estimates on model choices and on the availability of WISE photometry. Indeed, the WISE data are required to minimize the misclassification of star-forming galaxies as AGNs. The lack of WISE bands in SED fits leads to elevated AGN fractions for 68% of star-forming galaxies identified using emission line diagnostic diagrams, but this does not significantly affect their stellar mass or star formation estimates.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Deciphering yield modification of hadron-triggered semi-inclusive recoil jets in heavy-ion collisions

Jet quenching is recognized as critical evidence for the existence of the quark-gluon plasma (QGP) and serves as an essential probe to study its transport properties. Measurements of hadron-triggered semi-inclusive recoil jets have gained popularity due to its capability to probe jets over an extended phase space at low transverse momenta (p T ) and large radii. Recent ALICE measurements showed that the I AA , yield ratio of recoil jets between heavy-ion and p+p collisions, rises with jet p T and exceeds unity at high p T , contradicting conventional expectations that jet quenching should result in I AA values less than one. In this contribution, we re-examine the surface bias and study the effects of energy losses for both trigger hadrons and recoil jets on I AA , employing the Linear Boltzmann Transport (LBT) model to simulate jet-medium interactions. Our findings suggest that a large portion of hadrons used for the triggers undergoes substantial energy loss, despite surface bias. In particular, the energy loss of the trigger hadrons elevates the I AA baseline, corresponding to the case of no energy loss for recoil jets, to be greatly larger than unity. This enhancement of the baseline implies that the measured I AA values being larger than unity could still signal jet quenching.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Upland forest retreat lags behind sea‐level rise in the mid‐Atlantic coast

Abstract Ghost forests consisting of dead trees adjacent to marshes are striking indicators of climate change, and marsh migration into retreating coastal forests is a primary mechanism for marsh survival in the face of global sea‐level rise. Models of coastal transgression typically assume inundation of a static topography and instantaneous conversion of forest to marsh with rising seas. In contrast, here we use four decades of satellite observations to show that many low‐elevation forests along the US mid‐Atlantic coast have survived despite undergoing relative sea‐level rise rates (RSLRR) that are among the fastest on Earth. Lateral forest retreat rates were strongly mediated by topography and seawater salinity, but not directly explained by spatial variability in RSLRR, climate, or disturbance. The elevation of coastal tree lines shifted upslope at rates correlated with, but far less than, contemporary RSLRR. Together, these findings suggest a multi‐decadal lag between RSLRR and land conversion that implies coastal ecosystem resistance. Predictions based on instantaneous conversion of uplands to wetlands may therefore overestimate future land conversion in ways that challenge the timing of greenhouse gas fluxes and marsh creation, but also imply that the full effects of historical sea‐level rise have yet to be realized.

Biodiversity & Conservation↗
DOE OSTI2020

A Phenomenological Model for Cavitation

A phenomenological model of cavitation is presented, based on observations that both large relative negative pressures and large negative time derivatives of pressure are required for cavitation onset. We simulated two cavitation experiments to generate cavitation scaling parameters for relative pressure drop and rate of pressure drop. Our results show the model, while simple, is effective at reproducing results from laboratory experiments of cavitation. The parameters were then used in conjunction with a human surrogate computational model to predict, at any position within the head, the probability of intracranial cavitation caused by exposure to a blast event. The results suggest that the magnitude of blast overpressure observed in field data is sufficient to cause intracranial cavitation. Our analysis indicates that the helmeted head, when compared to the unhelmeted head configuration, results in a decrease but not elimination of cavitation exposure. When density functions of cavitation probability versus cumulative brain volume are combined with an injury severity model, the results show helmet efficacy at low and moderate risk levels. However, the convergence of unhelmeted and helmeted probability density functions at high-to-excessive risk thresholds indicates the helmet offers diminishing protection at elevated exposure levels, relative to the unhelmeted baseline. Future investigation and collaboration with neuroscience subject matter experts are needed to contextualize the current computational results. While the present work contributes specific and quantified predictions of intracranial cavitation location and severity, more research is required to apply our results to clinical settings with population-based brain injury subjects and controls. The relationship between our intracranial cavitation predictions with their anticipated clinical sequelae remains a topic in need of exploration.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Impact of Mixed Sources on the Atmospheric Aerosols of Urbanized Areas in the Philippines

Southeast Asia (SEA) holds approximately 10% of the global population, who are constantly exposed to severe local and transboundary air pollution. Here, we characterized the physiochemical characteristics of atmospheric aerosols in urbanized areas (Valenzuela, Manila, and Boracay) in the Philippines. The variability of coarse and fine aerosols, black carbon (BC), and trace elements of particulate matter (PM) were analyzed between June 2017 and April 2019. The average fine (coarse) aerosols of Valenzuela, Manila, and Boracay were 26.7 (80.4), 27.9 (86.6), and 20.9 (124.6) µg m –3 , respectively, which all exceeded the recent annual limits of the World Health Organization. The average BC level was 6.6 µg m –3 across three sampling sites, ranging between 4 to 83% of the fine PM mass. Vehicular emission predominated at the extreme urban sites as reflected by the high BC levels attributed to transport activities. The conventional receptor modeling procedure was implemented and improved by integrating BC speciation, which distinguished vehicle emission and biomass burning. The new method revealed eight and seven sources influencing the atmospheric conditions of Valenzuela and Boracay. In particular, the elevated zinc and lead highlighted the substantial impact of industrial sources in Valenzuela, attributing more than 9% of PM 2.5 . For Boracay, construction activities evidently enhanced PM based on the mass burden of calcium. Overall, the results uncovered the origin of PM 2.5 in urbanized locations in the Philippines, which will be valuable in reducing the exposure of a significant portion of the global population to harmful pollutants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A radar view of ice microphysics and turbulence in Arctic cloud systems

Ice microphysical processes are inherently complex because of their sensitivity to temperature and humidity, the diversity of ice crystal habits, and their interaction with supercooled liquid water (SCL) and turbulence. Long-term surface-based radar observations have been systematically used to unravel the different processes that affect ice particle growth. In this study, we present a statistical analysis of 6.5 years of Ka-band radar observations in Arctic cloud systems, combined with thermodynamic profiles derived from radiosonde measurements. For the first time, ice particle growth and sublimation – diagnosed from vertical gradients of radar reflectivity and mean Doppler velocity – are systematically mapped across a broad range of temperature and moisture conditions. These vertical gradients correspond closely to saturation levels relative to ice and exhibit a strong temperature dependence in supersaturated regions. Notably, distinct signatures near −15 °C are indicative of dendritic growth. Turbulence, quantified via the eddy dissipation rate (EDR), is most frequently observed in regions containing SCL. The co-occurrence of SCL and elevated turbulence results in significantly enhanced ice particle growth compared to conditions in which either is present alone. This work provides new observational constraints that are critical for improving the representation of ice microphysics in atmospheric models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Air Classification of Forestry Residues for Fast Pyrolysis

Understanding critical biomass attributes through efficient fractionation is crucial for advancing sustainable pyrolysis for renewable energy and chemical production. This study investigates the intricate relationship between biomass preprocessing and pyrolysis product yields, employing the air classification technique for the treatment of loblolly pine residues with varying moisture content. A comprehensive exploration of the physicochemical properties of air-classified loblolly pine informs a sophisticated pyrolysis simulation model. Given the complex and multifaceted nature of biomass pyrolysis, operating across diverse temporal and spatial scales, a pyrolysis kinetics-based CFD–DEM simulation method is employed to predict product yields. Results showed that the elevated moisture content amplifies particle adhesiveness, necessitating augmented air velocities for effective separation, thereby influencing the efficiency of the separation process. While carbon and hydrogen contents exhibit relative stability across diverse moisture contents and blower frequencies, the oxygen content undergoes noticeable changes. For example, the oxygen contents were measured as 29.2 and 38.6 wt% in the light fraction of 30% moisture content sample at blower frequencies of 10 and 20 Hz, respectively. An intriguing finding emerges from pyrolysis simulation, indicating that a lower blower frequency in air classification moderately enhances bio-oil yield and significantly improves its quality, particularly in terms of water content. For instance, the water content in the bio-oil was about 1.5% and 10% in the heavy and light fractions, respectively from 10% moisture sample under 15 Hz blower frequency.

09 - BIOMASS FUELS↗