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At least 487 records · Page 27

Application of an Empirical Density Law via Python for Aqueous Plutonium Chloride Systems for MCNP6

Criticality safety models for aqueous plutonium chloride systems often contain a significant bias due to assumptions in material compositions. These systems are currently modeled as a fictitious metal-water mixture because little is known about the true solution density. Furthermore, no predictive density tools or capabilities for modeling aqueous plutonium chloride systems are approved for use at Los Alamos National Laboratory. Recent density measurements of this ternary system (PuCl 3 -HCl-H 2 O) have allowed for the development of a more realistic density law, which is applied in this work via an empirical method based in Python. This tool, entitled PuCS (Plutonium Chloride Solution tool) may be used to determine solution density and composition based on the plutonium content, acid content, and temperature for MCNP6 inputs. PuCS has been found to predict density within 2% of experimental data. In conclusion, MCNP6 calculations have found that crediting minimal amounts of free acid (0.5 M) may correspond to a ~12% decrease in peak reactivity in comparison to current modeling methods.

42 ENGINEERING↗

National Energy Water Treatment and Speciation (NEWTS) Database & Dashboard

The Department of Energy's Office of Fossil Energy & Carbon Management (DOE/FECM) through the National Energy Technology Laboratory (NETL) has launched a free online tool, the National Energy Water Treatment and Speciation (NEWTS) Database and Dashboard, which can be utilized by community leaders and water researchers to better understand the composition of energy-related wastewater streams. The NEWTS Database and Dashboard provide public access to difficult-to-access datasets, including the original data sources and the processed data forms for input into aqueous chemistry modeling software. The data provided by the tool will help mitigate environmental risks and identify possible sources of valuable critical minerals (CM). The goal of this ASME Power presentation is to highlight the data and capabilities of this free online-tool for obtaining high quality water datasets in formats that are easy for modeling the treatment and recovery of valuable resources from effluent waste stream associated with energy operations.

Siefert, Nicholas↗

SPARTAN and IMPROVE Comparison Experiment (SPICE) Interim Campaign Report

SPICE (the SPARTAN and IMPROVE Comparison Experiment) aims to obtain and quantify comparisons between aerosol PM 2.5 mass concentration measurements from the University of Oklahoma (OU) Surface Particulate Matter Network (SPARTAN) station and the U.S. Environmental Protection Agency (EPA) Interagency Monitoring of Protected Visual Environments (IMPROVE) station hosted by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility at ARM’s Southern Great Plains (SGP) observatory in Oklahoma. Aerosols—both natural and anthropogenic—affect human populations in multiple ways. Much of ARM’s research focuses on how aerosols influence weather and climate through their optical and radiative effects, as well as their impacts on clouds and precipitation. However, aerosols also pose direct risks to humans and other organisms through inhalation, with the severity of health impacts depending on particle size, chemical composition, and duration of exposure. The IMPROVE network was established by the U.S. EPA to monitor air quality, including visible clarity as well as total and chemically speciated aerosol mass concentrations. The ARM SGP site hosts the IMPROVE SOGP station. Separately, the SPARTAN network operates a globally distributed set of stations similar to IMPROVE but with an emphasis on remote deployment and semi-autonomous operation for use beyond the borders of the United States (IMPROVE only operates within the U.S.). The University of Oklahoma operates a SPARTAN station. To establish confidence in the OU SPARTAN instrumentation and measurement protocol relative to the EPA-certified IMPROVE station, the OU SPARTAN station is currently deployed at SGP in close proximity to the IMPROVE SOGP station. The SPICE campaign was envisioned as a contiguous calendar-year effort for 2025 to capture seasonal variation in mass loading as well as composition. However, independent of the SPICE campaign, the SPARTAN network adopted a new filter construction part-way through the year, interrupting our contiguous data set. Thus, to obtain a contiguous data set with a uniform consistent configuration, SPICE desires an extension through 2026.

54 ENVIRONMENTAL SCIENCES↗

The Optical and Infrared Are Connected

Galaxies are often modeled as composites of separable components with distinct spectral signatures, implying that different wavelength ranges are only weakly correlated. They are not. We present a data-driven model that exploits subtle correlations between physical processes to accurately predict infrared (IR) Wide-field Infrared Survey Explorer (WISE) photometry from a neural summary of optical Sloan Digital Sky Survey spectra. The model achieves accuracies of $χ^{2}_{N} ≈ 1$ for all photometric bands in WISE, as well as good colors. We are able to tightly constrain typically IR-derived properties, e.g., the bolometric luminosities of active galactic nuclei (AGN) and dust parameters such as q PAH . We also test whether current spectral energy distribution (SED) fitting methods reproduce such panchromatic relations, but find their predictions biased and overconfident, likely due to model misspecification, with correlated biases in star-formation rates (SFRs) and AGN luminosities being most evident. To help improve SED models, we determine which features of the optical spectrum are responsible for our improved predictions, and identify several lines (Ca II , Sr II , Fe I , [O II ], and Hα), which point to the complex chronology of star formation and chemical enrichment being incorrectly modeled.

Jespersen, Christian Kragh [Princeton Univ., NJ (U↗

Rare Earth Carbide (Nd-C and Ce-C) Synthesis and Characterization to Inform Phase Equilibrium in Advanced Nuclear Fuels

As advances are being made regarding the performance of nuclear fuels, uranium carbides, and composites, such as (U,Zr)C and UO2 + UCx, have recently gained significant interest for deployment in nuclear space propulsion and high temperature gas-cooled reactors, respectively. However, the phase equilibria of several fission products in carbide systems remain unknown and may impact the overall fuel performance, specifically for particle nuclear fuels that are designed for commercial nuclear energy. Furthermore, comprehensive thermodynamic data on Rare Earth (RE) carbides, such as the Nd-C and Ce-C binary systems, remain limited. Presented in this study are the synthesis methods and characterizations of several Nd-C and Ce-C compositions. The findings from this research provide insights on the stability of RE-C binaries that form in irradiated nuclear fuels and address a critical knowledge gap in the current state of thermodynamics for two key RE-C systems.

Cavazos, Steven J. (ORCID:0009000130329363)↗

Mixture-of-Experts for Multi-Domain Defect Identification in Non-Destructive Inspection

Composite materials are widely used in aircraft structures because of their superior mechanical properties. However, their complex failure modes require sophisticated inspection methods to ensure structural integrity. Ultrasonic testing (UT) is a common non-destructive inspection (NDI) technique for aircraft composites that can detect internal and external defects with high resolution and accuracy. Despite their effectiveness, traditional UT methods rely on the manual interpretation of ultrasonic signals, which is time-consuming, labor-intensive, and subjective. Furthermore, processing such large-scale data, particularly across materials of varying thicknesses, significantly increases the computational demands of deep learning model optimization. To overcome these challenges, we propose an efficient sparse mixture-of-experts (MoE) model with a multi-level loss function and introduce four novel training objectives to improve computational efficiency and accuracy in identifying surface defects in composite aircraft materials. Here, we evaluated our approach on material with multiple thicknesses or domains comprising various defects. Our experimental results demonstrate higher accuracy and F1-Score, with only 10% training epochs compared to baseline MoE.

composite materials↗

Apatite geochemistry as a tool for understanding the petrogenesis of layered mafic-ultramafic rocks in the Bushveld Complex, South Africa

The sources of the magmas that formed the Rustenburg Layered Suite of the Bushveld Complex in South Africa remain debated, despite decades of research. Vertical and lateral variation in bulk rock and mineral separate Sr-Nd isotopic compositions, which generally indicate enriched sources, demonstrate that the layered sequence was formed by the emplacement of multiple batches of magma, crucially resulting in episodes of PGE-Cr-V mineralisation. The Lu-Hf isotope compositions of zircon are, however, at odds with the bulk rock Sr-Nd isotopic heterogeneity as they show near homogeneous compositions throughout the layered sequence (εHf (2.06 Ga) =−8). This lack of variation in Hf isotope composition has been attributed to deep, continental lithospheric mantle-related and/or crustal contamination of plume-derived Bushveld magmas. In this study, we analysed the major, trace element and Sr-Nd isotope geochemistry of apatite in the Rustenburg Layered Suite. Apatite occurs as an intercumulus mineral in the lowermost regions and a cumulus mineral in the uppermost regions of the layered sequence and can therefore be used to test existing models for the isotopic disequilibrium between bulk rock Sr-Nd and zircon Hf isotopic compositions. Apatite is largely chlorapatite in the lowermost regions and fluorapatite in the uppermost regions of the layered sequence. The Merensky Reef is unusual in that it comprises both chlorapatite and fluorapatite. Apatite throughout the layered sequence is generally unzoned and shows no evidence of late-stage alteration. Trace element data show that apatite is enriched in L/HREE, with common negative Eu-Sr anomalies. These trace element signatures are consistent with a magmatic origin for the apatite grains, with prior, or concurrent, plagioclase crystallization from the same melt. Variability in in situ Sr and Nd isotope compositions of apatite is recorded throughout the layered sequence with εNd (2.06 Ga) compositions varying between −2.5 and − 10.2 and initial 87 Sr/ 86 Sr compositions varying between 0.7079 and 0.7103 (for the Marikana dikes only). The variability in Sr-Nd isotope compositions of apatite is consistent with the bulk rock (and mineral separate) variation in Sr-Nd isotope compositions, suggesting apatite preserves primary magmatic compositions in the Rustenburg Layered Suite.

Apatite↗

Completing the Ba–As Compositional Space: Synthesis and Characterization of Three New Binary Zintl Arsenides, Ba3As4, Ba5As4, and Ba16As11

Three novel binary barium arsenides, Ba3As4, Ba5As4, and Ba16As11, were synthesized and their crystal and electronic structures were investigated. Structural data collected via the single-crystal X-ray diffraction method indicate that the anionic substructures of all three novel compounds are composed of structural motifs based on the homoatomic As–As contacts, with [As2]4− dimers found in Ba5As4 and Ba16As11, and an [As4]6− tetramer found in Ba3As4. Ba3As4 and Ba5As4 crystallize in the orthorhombic crystal system—with the non-centrosymmetric space group Fdd2 (a = 15.3680(20) Å, b = 18.7550(30) Å, c = 6.2816(10) Å) for the former, and the centrosymmetric space group Cmce (a = 16.8820(30) Å, b = 8.5391(16) Å, and c = 8.6127(16) Å) for the latter—adopting Eu3As4 and Eu5As4 structure types, respectively. The heavily disordered Ba16As11 structure was solved in the tetragonal crystal system with the space group P4¯21m (a = 12.8944(12) Å and c = 11.8141(17) Å). The Zintl concept can be applied to each of these materials as follows: Ba3As4 = (Ba2+)3[As4]6−, Ba5As4 = (Ba2+)5(As3−)2[As2]4−, and 2 × Ba16As11 = (Ba2+)32(As3−) ≈ 20[As2]4− ≈ 1, pointing to the charge-balanced nature of these compounds. Electronic structure calculations indicate narrow bandgap semiconducting behavior, with calculated bandgaps of 0.47 eV for Ba3As4, 0.34 eV for Ba5As4, and 0.33 eV for Ba16As11.

Crystallography↗

New NOvA Results with 10 Years of Data

NOvA is a two-detector accelerator neutrino oscillation experiment. Using Fermilab's newly Megawatt-capable NuMI neutrino beam, NOvA measures the disappearance of muon (anti)neutrinos and the appearance of electron (anti)neutrinos at the far detector, 810 km from the source. These oscillations are observed relative to the unoscillated beam composition measured at the functionally equivalent near detector, also located at Fermilab, which enables significant cancellation of systematic uncertainties. From these, we obtain precision measurements of the larger neutrino mass splitting and the largest neutrino mixing angle, as well as constraints on the octant of that angle, the neutrino mass ordering, and neutrino CP violation. In this talk I will present new measurements of these parameters using 10 years of NOvA data collected between 2013 and 2023, which includes twice the neutrino-mode exposure of our previous results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Life cycle assessment of coir fiber-reinforced composites for automotive applications

Past decades have seen an increasing prevalence of natural fiber-reinforced composites (NFRCs) due to growing conscientiousness around sustainability and a push towards vehicle lightweighting. The environmentally friendly and sustainable claims of NFRCs need to be validated due to their large variability and variety, particularly where material substitutions are concerned, such as in substituting glass fiber with natural fiber. Additionally, the objective of this work is to determine the cumulative energy demand (CED) and greenhouse gas emissions (GHG) associated with an automotive part (of volume 0.001 m3) made from 40 wt% coir fiber-reinforced polypropylene (PP) and compared with a similar part made from 40 wt% glass fiber reinforced PP. SimaPro v. 9.0.0.49 was used for the analysis, whereas inventory data were collected from databases, such as Ecoinvent 3, Transportation Energy Databook, Greet model 2022, and published papers. The results showed that CED and GHG associated with the coir fiber-reinforced composite part were lower than the glass fiber-reinforced composite part for both cradle-to-gate (~34–40%) and cradle-to-grave (excluding end-of-life) (~24%) analysis.

36 MATERIALS SCIENCE↗

SPRUCE FT-ICR MS, Bulk Chemistry, and Mass Loss from Litter Decomposition Study in Experimental Plots, Marcell Experimental Forest, Minnesota, 2015-2017

This dataset contains molecular, bulk chemical, and mass loss measurements from a litter decomposition study at the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site within the Marcell Experimental Forest in northern Minnesota, USA. This site is in a Sphagnum spp. ombrotrophic bog forest. Litterbags were deployed into the peat in September 2015 across three warming levels (+0, +4.5, and +9°C) under ambient and elevated carbon dioxide (CO₂ - +500 ppm) and retrieved after roughly 0.5, 1, and 2 years of field incubation (2015-09-23 to 2017-08-02). Litterbags containing six peatland litter types: black spruce needles (Picea mariana - SPL), spruce fine roots (SPR), Sphagnum angustifolium (ANG), Sphagnum magellanicum (MAG), Labrador tea leaves (Rhododendron groenlandicum - LTL), and Labrador tea roots (LTR). Molecular composition of water-soluble organic matter extracts was characterized using Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS) at 9.4 Tesla, operated in negative ion mode with electrospray ionization, providing molecular formula assignments and compound-class distributions across the decomposition time series. Bulk chemical characterization included elemental analysis (percent carbon, nitrogen, and phosphorus) and Fourier Transform Infrared Spectroscopy (FTIR) to quantify functional group composition. Litter mass loss was tracked gravimetrically at each retrieval interval, expressed as percent mass remaining relative to initial dry mass for each litter type and treatment combination. These data are valuable for understanding how vegetation shifts driven by increased atmospheric CO2 and temperature in peatlands alter litter inputs and organic matter stabilization trajectories, with implications for projecting and modeling peatland carbon cycling. This dataset contains two data files in comma-separated value (.csv) format. Additional metadata are provided: two data dictionaries and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.

decomposition↗

KCl-UCl 3 molten salts investigated by Ab Initio Molecular Dynamics (AIMD) simulations

Ab Initio Molecular Dynamics (AIMD) simulations are performed on molten KCl-UCl3 salt mixtures to determine energies, heat capacities, and densities. The density-dependent energy correction (DFT-dDsC), Grimme et al.'s DFT-D3, and Langreth & Lundqvist (vdW-cx) models are used for dispersion forces and combined with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation potential with a Hubbard U parameter for the 5f electrons of uranium. After validating predictions for the end-member systems to literature data, KCl-UCl 3 mixtures are studied at select temperatures. Densities and energies both deviate from ideal solution behavior, with the maximum deviation occurring around 36% UCl 3 for mixing energies and slightly lower (29% UCl3) for densities. Compared to the NaCl-UCl 3 system, which was previously investigated using the same simulation methodologies, the KCl-UCl 3 density and mixing energy deviations from ideal solution behavior are larger by almost a factor of two. No deviation from ideal solution behavior for heat capacity was observed. The AIMD predictions for mixing energies and densities agree qualitatively with experimental data, though the spread in data obtained from the various dispersion force models utilized, measurements, and empirical estimates makes strong conclusions difficult. The dependence of thermodynamic and thermophysical properties on composition is correlated with the local chemistry of the solution phase, in particular, the tendency of UCl 3 to form network structures.

36 MATERIALS SCIENCE↗

Toluene Adsorption and TPD

Raw data for toluene adsorption and TPD experiments on two different adsorbents using a custom flow-through, bench-top reactor capable of controlling gas compositions and temperature.

36 MATERIALS SCIENCE↗

KCl-UCl 3 molten salts investigated by Ab Initio Molecular Dynamics (AIMD) simulations: A comparative study with three dispersion models

Ab Initio Molecular Dynamics (AIMD) simulations are performed on molten KCl-UCl 3 salt mixtures to determine energies, heat capacities, and densities. The density-dependent energy correction (DFT-dDsC), Grimme et al.’s DFT-D3, and Langreth & Lundqvist (vdW-cx) models are used for dispersion forces and combined with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation potential with a Hubbard U param eter for the 5$f$ electrons of uranium. After validating predictions for the end-member systems to literature data, KCl-UCl 3 mixtures are studied at select temperatures. Densities and energies both deviate from ideal solution behavior, with the maximum deviation occurring around 36% UCl 3 for mixing energies and slightly lower (29% UCl 3 ) for densities. Compared to the NaCl-UCl 3 system, which was previously investigated using the same simulation methodologies, the KCl-UCl 3 density and mixing energy deviations from ideal solution behavior are larger by almost a factor of two. No deviation from ideal solution behavior for heat capacity was observed. The AIMD predictions for mixing energies and densities agree qualitatively with experimental data, though the spread in data obtained from the various dispersion force models utilized, measurements, and empirical estimates makes strong conclusions difficult. The dependence of thermodynamic and thermophysical properties on composition is correlated with the local chemistry of the solution phase, in particular, the tendency of UCl 3 to form network structures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Evaluation of PBR Spent Fuel Criticality and Dose Rate Compliance for Storage and Transportation

Spent tri-structural isotropic (TRISO)–based fuels have a strong track record in storage and transportation without documented incidents. This work seeks to reduce uncertainty to aid in more informed spent fuel management of TRISO-based fuels by modeling both fresh and spent pebble bed reactor (PBR) fuel and comparing the results to the regulatory standards from 10 CFR 71. SCALE was used for all modeling due to it having fast and accurate methods for handling PBR fuel modeling, as well as having an efficient method for shielding calculations in monaco with automated variance reduction using importance calculations (MAVRIC), which utilizes the consistent adjoint-driven importance sampling (CADIS) and the forward-weighted consistent adjoint-driven importance sampling (FW-CADIS) methods. KENO-VI was used for all criticality calculations, TSUNAMI was used for uncertainty quantification on k-effective, TRITON and the Oak Ridge isotope generation code (ORIGEN) were both used for depletion of the fuel, and MAVRIC was used for shielding calculations. For criticality assessments, this study focused on the requirement that the value of the neutron multiplication factor, k-effective (k-eff), would not exceed a peak value of 0.95, including uncertainty, with 95% confidence. Criticality was initially examined by modeling fresh fuel from three different designs—HTR-10 fuel, PBMR-400 fuel, and demonstration fuel representative of a TRISO-fueled modern high-temperature gas reactor (HTGR) design, henceforth referred to as Demo HTGR—and placing them into various sized containers with conditions described in 10 CFR 71 to quantify the peak k-eff state. When the peak value of 0.95 k-eff was exceeded, mitigation methods were examined in those scenarios. Burnup credit, pebble displacement in areas of strong neutron multiplication, and random pebble replacement using pebbles of various compositions and replacement fractions were examined. In summary, the criticality of PBR fuels can be well accounted for by restricting container size, taking credit for burnup, or by displacing/replacing pebbles. Uncertainty of the k-eff due to nuclear data uncertainties was recorded at ~0.6644%Δk/k, or roughly 664% mil (pcm). The nuclear data–induced uncertainty was relatively small and should not require significant modification in the design to be accounted for. Revisions to the evaluated nuclear data file values have been shown to have a larger impact than nuclear data–induced uncertainty. For dose rate aspects, U.S. Nuclear Regulatory Commission regulations require a maximum dose rate of 10 millirem per hour (mrem/h) at 2 meters. In examining the dose rate behavior of spent PBR fuel, the representative Demo HTGR fuel was modeled exclusively due to it possessing the highest target burnup of the examined fuels. Equilibrium cycle modeling methods were used to produce a higher-fidelity discharge isotopic composition than simple assumptions, such as reflected pebbles. The discharge composition was used as a source term in the fixed-source transport shielding calculations, and dose rates were calculated at 2 m for the shortest possible cooling time. The low concentration of fuel material led to dose rates that were in line with regulatory limits, despite the high burnup when compared to traditional light water reactor fuels. In conclusion, the methods employed in this study would require more work to further verify and validate and are limited to the criticality and dose rate analyses performed.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The System for Classification of Low-Pressure Systems (SyCLoPS): An All-In-One Objective Framework for Large-Scale Data Sets

We propose the first unified objective framework (SyCLoPS) for detecting and classifying all types of low-pressure systems (LPSs) in a given data set. We use the state-of-the-art automated feature tracking software TempestExtremes (TE) to detect and track LPS features globally in ERA5 and compute 16 parameters from commonly found atmospheric variables for classification. A Python classifier is implemented to classify all LPSs at once. The framework assigns 16 different labels (classes) to each LPS data point and designates four different types of high-impact LPS tracks, including tracks of tropical cyclone (TC), monsoonal system, subtropical storm and polar low. The classification process involves disentangling high-altitude and drier LPSs, differentiating tropical and non-tropical LPSs using novel criteria, and optimizing for the detection of the four types of high-impact LPS. A comparison of our labels with those in the International Best Track Archive for Climate Stewardship (IBTrACS) revealed an overall accuracy of 95% in distinguishing between tropical systems, extratropical cyclones, and disturbances. SyCLoPS produces a better TC detection skill compared to the previous algorithms, highlighted by an approximately 6% reduction in the false alarm rate compared to the previous TE algorithm. The vertical cross section composite of the four types of high-impact LPS we detect each shows distinct structural characteristics. Finally, we demonstrate that SyCLoPS is valuable for investigating various aspects of LPSs in climate data, such as the evolution of a single LPS track, patterns of LPS frequencies, and precipitation or wind influence associated with a particular LPS class.

54 ENVIRONMENTAL SCIENCES↗

AutoEMX v1.

The invention consists in the full automation of compositional analysis of inorganic powder samples by scanning electron microscopy (SEM) with energy-dispersive X-ray spectroscopy (EDS). The measurements and analysis are controlled via python-based software, Auto-SEMEDS. Auto-SEMEDS fully automates the SEM-EDS measurements, and analyses the collected data via the use of machine-learning (ML) algorithms, which have never been used before for such scope. Auto-SEMEDS enables the identification in fully-automated fashion of the individual material phases present in a powder sample. Similar technologies, such as commercial SEM-EDS software, can automatically classify particles based on their composition, but they have significant limitations. These solutions typically provide inaccurate composition measurements and struggle to identify single phases in lab samples, where phases are often closely intermixed. In contrast, Auto-SEMEDS achieves unprecedented accuracy in composition measurements of powder samples, and furthermore leverages machine learning algorithms to effectively discern intermixed phases. Notably, while previous studies have demonstrated accurate measurements on individual particles, Auto-SEMEDS stands out by successfully analyzing mixture of different phases, a capability that has not been reported in the literature until now.

Giunto, Andrea [Lawrence Berkeley National Laborat↗

Waste management strategies for military-generated waste in the United States

Sustainable and energy efficient municipal solid waste (MSW) management is vital for the health and performance of deployed soldiers, as they play an important role in the safety and dignity of a country. As the United States targets net-zero carbon-free emission goals, research and development are essential to surpassing current practices for management of MSW at military installations, both at home and abroad. To achieve this, it is important to act upon and implement the policies and instructions set by government agencies such as the Environmental Protection Agency (EPA), the Department of Energy (DOE), and the Department of Defense (DoD). Understanding the composition of waste and disposal methods that are in use at military installations is a crucial step to success. Here, the authors show this through analyzed data from trusted sources, such as government agencies, reports, magazines, journals, and other publications on MSW management techniques. By defining these challenges, possible solutions can be better understood for improved management of MSW at military installations in the United States. Finally, an integrated approach with deployable units capable of waste-to-energy technology using waste reduction, diversion, and recycling strategies shows to be an effective pathway for MSW conversion into energy and other useful products.

09 BIOMASS FUELS↗