Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “raw materials”

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.

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

At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Data Processing Workflow for Fixed-wing Drone Based Radiation Mapping in the Chornobyl Exclusion Zone (CEZ) - 20119

April 2020 marks the 34. anniversary of the high-profile radiological release from the Chornobyl Nuclear Power Plant (ChNPP). The release of radioactive material from reactor number four began on the 26 April 1986 and continued over a period of about 10 days, releasing approximately 1700 PBq of radioactive material (including 85 PBq of 137-Cs) into the environment. To this day, the accident remains the most significant release of radioactive material since civil nuclear power generation began. In the years since the accident, automated and remote radiation monitoring technologies have advanced significantly in their capabilities. One such example of this is the use of unmanned aerial vehicles (UAVs) in radiation mapping investigations. In April 2019, a team of scientists from the University of Bristol showcased a novel radiation mapping system within the CEZ, specifically aiming to map radiation over a large portion of the area immediately surrounding the ChNPP. Over six days of data collection, the system flew a total distance of 583.8 km, covering an area of 14.6 sq.km with an exceptional spatial resolution (sub 20 m/pixel). The work presented herein outlines and explains the data processing procedure to convert the raw data into 137-Cs activity (kBq/sq.m) and cesium-equivalent dose-rate (CED) at 1 m above ground level (μSv/hr). A demonstration of the validity of the method is demonstrated through the successful reduction of the raw data into a single linear relationship between the measured {sup 137}Cs net peak intensity and the {sup 137}Cs activity. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Corrosion characteristics of Mo and TZM alloy for plasma facing components in molten lithium at 623 K

Here, in this study, the corrosion behaviours of molybdenum (Mo) and a Mo-based alloy (TZM) were investigated using a static immersion corrosion technique. Weight loss, surface microstructure, and corrosion depth of Mo and the TZM alloy were correlated with elements. The compatibility of Mo and the TZM alloy in static liquid Li was suitable. Mo demonstrated uniform corrosion with a homogenous dissolution of free C and Mo, and TZM alloy exhibited a nonuniform corrosion behaviour with a preferential grain boundary attack caused by the selective dissolution of free C, Ti, and Zr. When the surface oxidation layer of the samples was consumed, free C from Mo and TZM diffused into molten Li to form Li 2 C 2 and then was captured by Zr, Ti, and Mo to form thermodynamically stable carbides, which resulted in the enrichment of the C layer near the sample surfaces. In addition, Ti and Zr acted as N-trappers in liquid Li; the formation of Zr and Ti nitrides resulted in the enrichment of N, Ti, and Zr elements on the surface and led to TZM corrosion increase. Thus, Zr and Ti depletion, pitting, and grain boundary corrosion were problematic for TZM under long-term exposure to liquid Li. Reducing the content of free C and nonmetallic N and increasing the amount of Ti and Zr carbides on the surface of and inside the raw TZM alloy helped improve the corrosion resistance of TZM in liquid Li.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Dataset for manuscript "Equipartition and the temperature of maximum density of TIP4P/2005 water"

We simulate TIP4P/2005 water in the temperature range of 257 K to 318 K with time-steps 0.25, 0.50, 1.00, 2.00, and 4.00 fs. The density-temperature behavior obtained using 0.25 or 0.50 fs are in excellent agreement with each other but differ from those obtained using time-steps that have been shown earlier to lead to a breakdown of equipartition. The temperature of maximum density (TMD) is 277.15 K with time-step 0.25 or 0.50 fs, but is shifted to progressively lower values for longer time-steps, a trend that holds for different thermostat/barostat combinations. Enhancing the water-water dispersion interaction, as has been recommended for simulating disordered proteins in TIP4P/2005, degrades the description of the liquid-vapor phase envelope. We present a simple physically transparent reasoning to highlight the separation of the time-scales between translational and rotational motion. We also develop a metric, Chi, that we term the equipartition anomaly, to detect equipartition violations in simulations that include molecules that are treated as rigid objects. Calculating Chi is shown to be straightforward and sensitive to equipartition violations. A key takeaway from this study is that using sufficiently short time-steps (less than or equal to 0.5 fs) to preserve equipartition is essential for obtaining meaningful liquid water properties and for producing reliable simulation data, as correct-ensemble sampling is fundamental to ensure reproducibility across codes and simulation alogrithms. The included dataset provides the raw data used in the preparation of the graphs noted in the manuscript.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Recycled Paper as a Source of Renewable Jet Fuel in the United States

Converting biomass into jet fuel involves more than the core chemical process. The overall process includes the logistics of harvesting and transporting the biomass, handling and preparing the material for processing, and processing and disposal of waste. All of these activities contribute to cost. Controlling cost involves more than developing efficient process chemistry. Choice of feedstock also has a significant impact on process economics. We consider chemical conversion of paper from municipal solid waste as a feedstock for the production of jet fuel and diesel. Paper has a significantly higher cellulose content than raw lignocellulosic biomass such as corn stover, so it requires less pretreatment to convert it into hydrocarbons than lignocellulosic biomass. Our techno-economic analysis showed that the cost of converting paper waste into jet fuel is about $1.00/gal less than jet fuel produced from corn stover. Although the cost of recycling paper into jet fuel is less than producing it from corn stover, the process is not competitive with petroleum. We estimated a minimum selling price of $3.97/gal for paper-derived jet fuel. Our sensitivity studies indicated that the biggest economic obstacle is the cost of cellulose hydrolysis. Direct hydrogenation of paper to sugar alcohols combined with increased economy of scale could make recycling paper jet fuel competitive.

09 BIOMASS FUELS↗
DOE OSTI2020

Characterization of vacuum conductance in commercially available (sintered) and additively manufactured porous structures

This report documents the work performed in characterizing the vacuum conductance of porous structures made by conventional sintering (purchased as commercially available products from Mott Corporation ranging from 20 to 100 media grade) and additive manufacturing (powder bed fusion). The additively manufactured structures described in this report were originally intended to be the first iteration of several in an effort to produce desirable conductance characteristics. While resources were not available to link the experimental results to a modeling effort to better understand why certain characteristics were observed, the author hopes that this report may provide a useful set of data for future use, especially as sintered porous structures are not uncommonly procured from Mott corporation for research and development purposes. For that reason, all of the raw data is tabulated in the Appendix: it is possible to reproduce all of the figures shown in this report independently. For a quick order-of magnitude scan of the conductances, refer to Figures 5, 6, 8 and 9.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Deployment of ADTimePix3 areaDetector Driver at Neutron and X-ray User Facilities

TimePix3 is a 65k hybrid pixel readout chip with simultaneous Time-of-Arrival (ToA) and Time-over-Threshold (ToT) recording in each pixel*. The chip operates without a trigger signal with a sparse readout where only pixels containing events are read out. The flexible architecture allows 40 MHits/s/cm² readout throughput, using simultaneous readout and acquisition by sharing readout logic with transport logic of superpixel matrix formed using 2x4 structure. The chip ToA records 1.5625 ns time resolution. The X-ray and charged particle events are counted directly. However, indirect neutron counts use 6Li fission in a scintillator matrix, such as ZnS(Ag). The fission space-charge region is limited to 5-9 um. A photon from scintillator material excites a photocathode electron, which is further multiplied in dual-stack MCP. The neutron count event is a cluster of electron events at the chip. We report on the EPICS areaDetector** ADTimePix3 driver that controls Serval*** using json commands. The driver directs data to storage and to a real-time processing pipeline and configures the chip. The time-stamped data are stored in raw .tpx3 file format and passed through a socket where the clustering software identifies individual neutron events. The conventional 2D images are available as images for each exposure frame, and a preview is useful for sample alignment. The areaDetector driver allows integration of time-enhanced capabilities of this detector into SNS beamlines controls and unprecedented time resolution.

Gofron, Kaz↗
DOE OSTI2022

Root image collection from a genotype by environment (GxE) root architecture study of the bioenergy species, Populus trichocarpa

Here we present a curated dataset; raw images of fresh roots collected from a genotype by environment (growth matrix) greenhouse root architecture study of the bioenergy species, Populus trichocarpa. Five separate experiments were performed to generate the dataset. Biological replicates (ramets, vegetative propagants) of Populus trichocarpa genotypes BESC 24 and BESC 375 were used for all experiments. The first two experiments were an eight-week and a six-week pot experiment where plants with grown in 4" X 14" sized pots were filled with Farfard 3B potting soil (Fafard Sungro #3B), and watered twice daily. Average greenhouse humidity and growth temperature were around 50-60% and 23°C, respectively. Ramets of P. trichocarpa genotypes BESC 24 and BESC 375 were used in various experiments. The source of this material was dormant field cuttings grown in greenhouse. The second experiment was a Microcosm root architecture experiment. This was done in a microcosm built with double-decker tissue culture Magenta box. Tissue culture plants with new root initials were transferred to microcosm with pro choice rapid dry growth matrix with 1x Hoagland’s solution pH5.7 and grown for six weeks until harvest. Temperature was held at ~22°C. The closed container trapped moisture. The source material was tissue culture stock plants established from shoot tips of greenhouse stock plants (obtained from same set of dormant field cuttings as rest of the study). For the remaining two experiments, greenwood stem cuttings from greenhouse grown plants were grown in six-week rhizotron and two-week hydroponics experiments in the greenhouse. For rhizotron experiments, plants were grown in 2-D rhizotron with black panels on both sides (31cm H x 30cm L x 1.2cm W) and watered daily. For hydroponics experiment, plants were grown in a 15ml falcon tube with distilled water and covered in foil and shaken a few times a day. Greenhouse temperature was held at ~ 23°C and humidity was between 50-60%. Stems were cut off and the root system was separated, gently washed to rid of matrix, immersed in a water tray and scanned for obtaining raw root images reported here. All scans of roots floating in a water tray were performed using an Epson Perfection V850 Pro Photo Scanner. Additional meta data is embedded in the raw image files.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Enhancing biomass flowability for entrained flow Gasification: The role of densification and torrefaction

Gasification presents a key strategy in addressing future energy demands while minimizing environmental impact. This has been recognized as a promising method to convert biomass to higher value products such as biofuels or hydrogen. Among gasification technologies, high-temperature and high-pressure reactors, particularly the R-GAS® system, emerge as an advanced option boasting superior conversion efficiency. However, akin to conventional high-temperature and high-pressure gasifiers, R-GAS® necessitates small particle sizes for optimal carbon conversion, a requirement yet to be fully explored for biomass. Hence, this study investigated the effectiveness of combined mechanical and thermal preprocessing techniques in modifying the physicochemical properties of biomass to suit gasification systems. Mechanical techniques including densification and pulverization, alongside thermal techniques such as torrefaction and steam explosion, were examined. The results demonstrate that torrefaction fosters producing of uniform granular material, enhancing flowability and reducing energy requirements for pulverization compared to steam explosion. Notably, torrefied corn stover exhibited lower internal friction angles and effective cohesion (40.09 ± 0.22° and 0.56 ± 0.01 kPa, respectively) compared to steam exploded corn stover (41.87 ± 0.65° and 0.83 ± 0.06 kPa, respectively), indicative of improved flowability. Additionally, pulverization of torrefied corn stover required approximately 16 % less energy than steam exploded corn stover and 91 % less energy than raw corn stover. Furthermore, the torrefaction-induced alterations in particle size, shape, and packing densities emphasize its potential to optimize flow and handling processes for gasification. These findings underline that densification followed by torrefaction effectively addresses biomass variability, leading to more efficient and sustainable energy conversion.

09 - BIOMASS FUELS↗
DOE OSTI2023

Automated Energy-Dispersive X-ray Spectroscopy Analysis for Multi-Modal Few-Shot Learning

Scanning transmission electron microscopy (STEM) is a powerful tool that allows for the atomic-scale analysis of a materials’ structure, chemistry, and defect domains (Akers et al. 2021). The current generation of microscopes generate vast amounts of data, surpassing the limits of effective manual analysis traditionally performed by domain experts (Spurgeon et al. 2021). While recent strides in machine learning have significantly enhanced the processing of large and intricate datasets acquired through electron microscopy, the prevalent use of proprietary software packages for initial data collection poses a challenge. In many cases, these software packages act as a ‘black box’, constraining user functionality and hindering the output of data in a format that is conducive to seamless integration into machine learning models. This work addresses these challenges by adapting HyperSpy, an open-source Python library, for the analysis and quantification of raw energy dispersive spectroscopy (EDS) data acquired through STEM. The modified HyperSpy code successfully facilitates user-defined segmentation of the data, enabling the integration of atomic %, weight %, and raw EDS spectra for each segmented region into an existing few-shot machine learning model. While initial results reveal discrepancies in quantified atomic and weight percentages when compared to proprietary software, ongoing efforts aim to rectify this issue by refining the fit of the HyperSpy model to the EDS spectra. Overall, this research underscores the potential of open-source tools like HyperSpy to enhance the accessibility of analytical tools, fostering a transparent and user-friendly environment for seamlessly incorporating electron microscopy data into machine learning models.

36 MATERIALS SCIENCE↗
DOE OSTI2022

ORNL_AISD_NiNb

This dataset describes the nickel-niobium solid solution binary alloy, where the two constituent elements nickel (Ni) and niobium (Nb) are randomly placed on an underlying crystal lattice. This dataset for nickel-niobium (Ni-Nb) alloys available includes the formation energy and bulk modulus for each crystal structure. Each atomic sample has a disordered phase which is obtained starting from an initial regular crystal structure of type body-centered cubic (BCC), face-centered cubic (FCC), or hexagonal compact packed (HCP). The geometry optimization ensures that all the alloy samples reached the equilibrium with negative formation energy. We perform geometry optimizations using the LAMMPS simulation package [1], a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. We utilized the embedded atom model (EAM) potential for Ni and Nb developed in a previous study [2]. The potential could describe behaviors of the liquid and solid phases of Ni-Nb alloy. The structural factors and angular distributions of three atoms are well-matched with X-ray and ab initio-based molecular dynamics data. We prepared the three different crystals with different initial lattice parameters (3.52 Ã… for FCC, 3.32 Ã… for BCC, and 3.5 Ã… for HCP). We performed energy minimization in two steps. Firstly, we minimized the structures with an isotropic unit cell to minimize the side effects from our arbitrary lattice parameters for all other compositions. Then, we applied geometry optimization with a triclinic (non-orthogonal) unit cell to fully minimize the stress components to calculate the elastic constants. In this procedure, we chose 10,000 as the maximum number of allowable steps aimed at obtaining fully relaxed atomic geometries. The dataset consists of three sets of crystal structures. The first set contains 46,086 irregular crystal structures, each of them with 54 atoms, obtained through optimization starting from a regular BCC crystal structure. The second set contains 24,543 irregular crystal structures, each of them with 32 atoms, obtained through optimization starting from a regular FCC crystal structure. The third set contains 39,303 irregular crystal structures, each of them with 48 atoms, obtained through optimization starting from a regular HCP crystal structure. The atomic configurations within each set span the possible compositional range. The three sets have been unified in a global dataset, which is extremely heterogeneous in terms of crystal structures, lattice volumes, and atomic configurations. Organization of files inside the dataset: the dataset contains three subdirectories called • BCC_opt • FCC_opt • HCP_opt based on the type of initial regular structure used to start the geometry optimization. Inside each of these folders, every atomic structure is identified by a string “A_B_Câ€, where A denotes the number of Nb in the system, B denotes index of structure with a given Nb number, and C denotes the total number of structures generated with a given Nb number. For each optimized crystal structure identified by the unique string of characters “A_B_Câ€, three files are provided: • A_B_C_opt.xyz: The optimized geometries in xyz format • A_B_C_opt.cfg: The optimized geometries in cfg format. It includes cell information and atomic energy, and forces calculated from LAMMPS. • A_B_C.elastic: Raw data of 21 elastic constants from LAMMPS output. • A_B_C.bulk: Calculated upper and lower bounds of bulk modulus and averaged one based on Voigt-Reuss-Hill approach from *.elastic. References: [1] A. P. Thompson, H. M. Aktulga, R. Berger, D. S. Bolintineanu, W. M. Brown, P. S. Crozier, P. J. in 't Veld, A. Kohlmeyer, S. G. Moore, T. D. Nguyen, R. Shan, M. J. Stevens, J. Tranchida, C. Trott, and S. J. Plimpton. LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. Comp. Phys. Comm., 271:108171, 2022. [2] Y Zhang, R Ashcraft, MI Mendelev, CZ Wang, and KF Kelton. Experimental and molecular dynamics simulation study of structure of liquid and amorphous ni62nb38 alloy. The Journal of chemical physics, 145(20):204505, 2016.

36 MATERIALS SCIENCE↗
DOE OSTI2026

pyRMG: A framework for high-throughput, large-cell DFT calculations on supercomputers

Exascale computing delivers the raw power to simulate ever larger and more chemically realistic systems, but realizing this potential requires codes that can efficiently use thousands of processors. Our real-space multigrid (RMG) density functional theory (DFT) code’s grid-decomposition approach scales nearly linearly with the number of graphics processing units (GPUs), even for simulations exceeding thousands of atoms. This scalability makes RMG a compelling tool for high-throughput DFT studies of materials that would otherwise be bottlenecked in other codes (for example, by global fast Fourier transforms in plane-wave DFT). However, the limited workflow infrastructure for RMG has thus far constrained its adoption to a small user community. In this work, we present pyRMG, a Python package designed to streamline the setup and execution of RMG DFT calculations. Built on the pymatgen and ASE (Atomic Simulation Environment) computational materials science Python packages, pyRMG automates input generation and convergence checking, and it integrates with modern job schedulers (e.g., Flux) on leadership-class platforms such as Frontier and Perlmutter. Here, we demonstrate pyRMG for a high-throughput study of strain effects in 2D 2L-Bi 2 Se 3 /2L-NbSe 2 heterostructures, which offers chemical insights into this system and shows that RMG-based workflows can converge with limited user intervention.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Raw data for KCoAsO4 powder

Contains neutron powder data on nuclear and magnetic diffraction as well as low and high energy inelastic neutron scattering for KCoAsO4

36 MATERIALS SCIENCE↗
DOE OSTI2022

Rare Earth Element (REE) and Critical Mineral Fractions of Central Appalachian Coal-Related Strata Determined by 7-Step Sequential Extraction

Rare earth elements (REEs) and critical minerals (CMs) are used in many modern industries, including the automotive sector, generation and storage, clean energy, and defense. The demand for REEs is increasing, and the REE supply chain is unpredictable. The US has driven to assess non-conventional sources of REE (such as coal underclay) to identify domestic resources to stabilize this uncertainty in supply. Knowledge of the minerology, distribution, and modes of occurrence of REEs is integral to the assessment of non-conventional sources. Additionally, extraction techniques can be optimized and targeted when REE distribution in different solid fractions from source material is understood. In this study, four bituminous coal-related samples associated with the Lower and Middle Kittanning coal seams in the Appalachian Basin (US) underwent a seven-step sequential extraction procedure, primarily targeting the water-soluble, exchangeable, acid soluble, mildly reducible, moderately reducible, strongly reducible, and oxidizable fractions. The REE and other elements of interest from each extraction step were analyzed, and the percentages of element extracted from raw solids were calculated. REEs extracted from the total seven steps were reported as the extractable fraction, whereas the fractions in the residual solids were reported as the non-extractable fraction. Less than 6% of REE were extracted from three samples. Twenty-one percent of REE was extracted from the fourth sample, mainly from the steps targeting oxidizable and exchangeable phases. Co-extraction of critical metals (Co, Ni, Cu, and Zn) occurred during the oxidizable, exchangeable, acid soluble, and water-soluble steps for the four samples. In the extracted fractions, the four samples all exhibited a middle and heavy REE enrichment relative to light REE. The mobility of major cation (e.g., Ca, Fe, and P) and REE is associated with exchangeable, oxidizable, and acid soluble fractions. Non-extractable REE is likely held in refractory apatitic phases, and/or primary REE-phosphates (e.g., monazite and xenotime).

58 GEOSCIENCES↗
DOE OSTI2025

A Data-Driven Framework for Predicting the Sorting and Screening Performance of an Integrated Biomass Feedstock Preprocessing System

The characteristics of mechanically sorted and screened lignocellulosic biomass, such as the mass contents of corn stover anatomical fractions (leaves, husks, stalks, cobs, etc.), can be used to calculate the intermediate feedstock quality attributes “yield” and “purity” that indicate the conversion efficiency of biocrude. No prior study has investigated the correlations from the characteristics of raw biomass and preprocessing unit operation parameters to those intermediate feedstock quality attributes. This work presents a data-driven framework for assessing and predicting the intermediate feedstock quality attributes in an integrated biomass feedstock preprocessing system. Our study used corn stover as a typical type of herbaceous biomass because of its abundance in the U.S. It began with data acquisition of moisture content, particle size distribution, and anatomical fractions of the materials after each unit operation in the system. The objective of this preprocessing system is to minimize husks and leaves and maximizing cobs and stalks by mechanically separating the materials into three streams via disc screen and air separator. Prototype neural network models were then developed to evaluate the feasibility of predicting process outcomes based on measurable parameters. It is found that incorporating physical constraints into these prediction models significantly enhances the accuracy of the predicted yield and purity against the ground truth data. The experimental data and model predictions indicate that decreasing throughput increases purity, while higher throughput results in lower purity. Finally, an optimization problem was introduced to search optimal combinations of feed material properties and preprocessing unit operation parameters, as the intermediate feedstock quality attributes – yield and purity, appeared to be competing factors. The study also suggests the continual need to improve the data-driven framework’s predictability by incorporating more accurate physical models to describe the dynamics in the preprocessing units such as the air separator.

09 - BIOMASS FUELS↗
DOE OSTI2020

Improving PCM Waste Management Through New Approaches to Screening for LLW Treatment and Disposal - 20145

A major step forward in the management of Plutonium Contaminated Material (PCM) Waste has been taken at the Sellafield site with the introduction of new capabilities to enable wastes previously conservatively designated as PCM Intermediate Level Waste (ILW) to be re-classified for treatment as Low Level Waste (LLW). The Sellafield site, located in the North West of England, within the United Kingdom (UK), has operated plutonium processing plants and waste facilities for almost 70 years. During this time management of the raw PCM waste produced has presented a variety of challenges. The waste is currently processed by high force waste compaction in the Waste Treatment Complex (WTC). The WTC converts 200 litre drums of raw PCM waste into a compacted, grout encapsulated monolith form within stainless steel containment, ready for emplacement within the UK's Geological Disposal Facility (GDF) when it becomes available. To help progress some of the wastes waiting for treatment, recent improvements have been made with the introduction of new waste assay instrumentation which enables the identification of a 'candidate' waste potentially suitable for disposal via the LLW treatment route. Opening a new LLW route for previously designated PCM has been a major advance in PCM waste management policy. It has required a range of technical assessment arrangements to be developed, tested and commissioned and involved the engagement of a wide range of stakeholders. In particular, very detailed technical analysis methods have been developed to ensure that there is a robust and conservative approach to the final sentencing of waste. Following completion of commissioning tests, the first 86 m{sup 3} of previously designated PCM waste was successfully treated through the LLW route and consigned to LLW disposal in June 2019. The direct benefit of sentencing waste to the correct waste route (LLW) is the significant cost savings across the complete range of waste management activities. This work is also strategically important for demonstrating to a range of stakeholders including workforce and regulators, that waste previously designated as PCM can be re-classified in a systematic and justifiable way without increasing risk to personnel or the wider environment. By ensuring that waste is being managed appropriately it will be possible to carry out more remediation work safely, in less time, and at a lower cost. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Life-Cycle Greenhouse Gas Emissions and Human Health Trade-Offs of Organic Waste Management Strategies

Waste-to-energy systems can play an important role in diverting organic waste from landfills. However, real-world waste management can differ from idealized practices, and emissions driven by microbial communities and complex chemical processes are poorly understood. This study presents a comprehensive life-cycle assessment, using reported and measured data, of competing management alternatives for organic municipal solid waste including landfilling, composting, dry anaerobic digestion (AD) for the production of renewable natural gas (RNG), and dry AD with electricity generation. Landfilling is the most greenhouse gas (GHG)-intensive option, emitting nearly 400 kg CO 2e per tonne of organic waste. Composting raw organics resulted in the lowest GHG emissions, at -41 kg CO 2e per tonne of waste, while upgrading biogas to RNG after dry AD resulted in -36 to -2 kg CO 2e per tonne. Monetizing the results based on social costs of carbon and other air pollutant emissions highlights the importance of ground-level NH3 emissions from composting nitrogen-rich organic waste or post-AD solids. However, better characterization of material-specific NH 3 emissions from landfills and land-application of digestate is essential to fully understand the trade-offs between alternatives.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Totally chlorine-free peracetic acid pulping for nanocellulose isolation from hemp and poplar

Nanocellulose is a promising and sustainable feedstock for developing advanced and functional materials. However, the characteristics of nanocellulose, such as crystallinity, surface energy, and aspect ratio, can vary depending on biomass source and pretreatment methods, leading to variable performance of the nanocellu-lose-based materials. In this study, cellulose nanocrystals (CNCs) were isolated from hemp and poplar using totally chlorine free (TCF) peracetic acid and sodium chlorite delignification and bleaching pretreatments to probe the influences of biomass source and treatment methods on the isolation and characteristics of CNCs. Our results showed that hemp and poplar were almost completely delignified by peracetic acid treatment, whereas sodium chlorite treatment left 5%–6% lignin in the pulp. The yields of CNCs from raw hemp and poplar biomass ranged from 9.8% to 21.9% and 10.9% to 28.3%, respectively, depending on the treatment methods. The dimensions of CNCs from TCF-treated biomass generally maintained a larger width and aspect ratio than those from sodium chlorite-treated biomass. The poplar-derived CNCs exhibited slightly higher crystallinity of 53%–58% than hemp-derived CNCs of 49%–54%. The zeta potential of the CNCs, ranging from -20.1 mV to -31.1 mV, ensured a well-dispersed aqueous solution. The surface energy (dispersive energy of 40–80 mJ/m2 and specific energy of 2–10 mJ/m2), water interaction, and thermal stability of the CNCs were comparable, regardless of the biomass source and pretreatment methods. Our finding suggests that the TCF technique with peracetic acid treatment is a promising delignification and bleaching approach to obtain cellulose-rich pulps from herbaceous and hardwood biomass for nanocellulose isolation.

09 BIOMASS FUELS↗