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At least 721 records · Page 40

Kinetics Modeling for Design of Continuous Enzymatic Hydrolysis

Enzymatic hydrolysis of cellulose to monomeric sugars continues to be a limiting step in cost-effectively producing sugar and fermentation-based biofuels from biomass. In particular, the high cost of enzymes coupled with the long time-scale of reaction pose challenges to economic viability. Performing enzymatic hydrolysis in a continuous mode with enzyme recycle may provide a path towards substantially reduced costs for sugar production, but design and analysis are complicated by a lack of suitable kinetics models. Computationally attainable models, such as fractal-based models, require knowledge of the reaction-history of the biomass, and are thus only suitable for describing the batch reactions from which they are derived. Fundamental models, while potentially more generalizable, are often too computationally intensive to use in process or reactor modeling. In this work, a phenomenological rate model is proposed based on a two-phase substrate representation. Good agreement is seen between batch and continuous enzymatic hydrolysis (CEH) experiment data, which validates the model and enables us to solve for reactor design parameters, such as CEH reactor size and stream flow rates, based on process variables like yield. This model is integrated with techno-economic analysis software to explore economic sensitivities. Important design optimizations and tradeoffs are identified and quantified, including the relative cost imposed by rate slowdown from sugar inhibition versus the cost to remove and concentrate sugars at a lower concentration. It also identifies, high-leverage avenues for further exploration, such as increasing the maximum feasible solids concentration, and sustaining high membrane flux and reliability.

09 BIOMASS FUELS↗

Prediction of microalgae hydrothermal liquefaction products from feedstock biochemical composition

Hydrothermal liquefaction (HTL) uses water under elevated temperatures and pressures (200–350 °C, 5–20 MPa) to convert biomass into liquid “biocrude” oil. Despite extensive reports on factors influencing microalgae cell composition during cultivation and separate reports on HTL products linked to cell composition, the field still lacks a quantitative model to predict HTL conversion product yield and qualities from feedstock biochemical composition; the tailoring of microalgae feedstock for downstream conversion is a unique and critical aspect of microalgae biofuels that must be leveraged upon for optimization of the whole process. This study developed predictive relationships for HTL biocrude yield and other conversion product characteristics based on HTL of Nannochloropsis oculata batches harvested with a wide range of compositions (23–59% dw lipids, 58–17% dw proteins, 12–22% dw carbohydrates) and a defatted batch (0% dw lipids, 75% dw proteins, 19% dw carbohydrates). HTL biocrude yield (33–68% dw) and carbon distribution (49–83%) increased in proportion to the fatty acid (FA) content. A component additivity model (predicting biocrude yield from lipid, protein, and carbohydrates) was more accurate predicting literature yields for diverse microalgae species than previous additivity models derived from model compounds. FA profiling of the biocrude product showed strong links to the initial feedstock FA profile of the lipid component, demonstrating that HTL acts as a water-based extraction process for FAs; the remainder non-FA structural components could be represented using the defatted batch. These findings were used to introduce a new FA-based model that predicts biocrude oil yields along with other critical parameters, and is capable of adjusting for the wide variations in HTL methodology and microalgae species through the defatted batch. Lastly, the FA model was linked to an upstream cultivation model (Phototrophic Process Model), providing for the first time an integrated modeling framework to overcome a critical barrier to microalgae-derived HTL biofuels and enable predictive analysis of the overall microalgal-to-biofuel process.

09 BIOMASS FUELS↗

Putting ROSE to Work: A Proposed Application of a Request-Oriented Scheduling Engine for Space Station Operations

Scheduling engines are found at the core of software systems that plan and schedule activities and resources. A Request-Oriented Scheduling Engine (ROSE) is one that processes a single request (adding a task to a timeline) and then waits for another request. For the International Space Station, a robust ROSE-based system would support multiple, simultaneous users, each formulating requests (defining scheduling requirements), submitting these requests via the internet to a single scheduling engine operating on a single timeline, and immediately viewing the resulting timeline. ROSE is significantly different from the engine currently used to schedule Space Station operations. The current engine supports essentially one person at a time, with a pre-defined set of requirements from many payloads, working in either a "batch" scheduling mode or an interactive/manual scheduling mode. A planning and scheduling process that takes advantage of the features of ROSE could produce greater customer satisfaction at reduced cost and reduced flow time. This paper describes a possible ROSE-based scheduling process and identifies the additional software component required to support it. Resulting changes to the management and control of the process are also discussed.

Jaap, John↗

Schema Elements for Granta Annual Report: FY2024

Granta: Materials Intelligence (Granta: MI) is a commercial database software distributed by Ansys, Inc. that is utilized by the Nuclear Security Enterprise (NSE) to organize and store relevant materials data. Lack of standard and well-documented database schema is the primary obstacle to an NSE materials data management solution, so the objective of this project is to create and document such a schema. In FY21, an approach for designing, documenting, and managing a standard database schema was described based on the creation of schema elements (collections of attributes used to describe particular aspects of the data) to be used as building blocks for creating various database tables without duplication. In FY22, these methods were applied through a multi-site collaboration to create and document the schema elements necessary to build a thermogravimetric analysis (TGA) testing table. In FY23 the schema was expanded to include elements for a differential scanning calorimetry (DSC) table, along with schema for supporting metadata tables including Instruments, Projects, Documents, and Testing Series. In FY24 the following progress was made, again through multi-site collaboration: • The existing schema elements were modified to accommodate thermomechanical analysis (TMA) data, and a table, Test Data: TMA, was created for managing TMA data. • The elements necessary for the following additive manufacturing (AM) data tables (directed at data specific to selective laser sintering AM technology) were created: • AM Builds • AM Processes • AM Part Designs • Built AM Parts • AM Feedstock Materials • AM Feedstock Material Batches • The elements necessary for creating a Calibrated Material Models table were created, and the Calibrated Material Models table was created. In FY25 the existing schema will be deployed on the production enterprise Granta instance on the enterprise secure network. Schema elements will be appended, and new elements created as necessary, to allow the creation of tables specifically to support materials testing, AM process development, and design and analysis for modernization programs.

36 MATERIALS SCIENCE↗

Deconvoluting sources of variability in aerosol jet printing using light scattering measurements

Aerosol jet printing (AJP) is a digital additive manufacturing technique for hybrid and conformal electronics, where its contactless deposition readily enables patterning over 3D surface topography. However, the complexity of aerosol transport physics makes deposition rate sensitive to process variability, hindering widespread industry adoption. Light scattering measurements have recently been demonstrated as a capable tool for measuring deposition rate in real time, enabling closed-loop control and in-situ qualification frameworks. These inline optical measurements present further opportunity as a diagnostic tool to understand the effects of secondary process parameters affecting vapor–liquid equilibrium and heat and mass transport during deposition. Downstream of the optical measurement cell, changing the sheath gas flow rate, increasing temperature via an inline heater, and adding solvent vapor via a sheath gas bubbler were observed to alter drying physics during sheath-collimation, and thereby impaction efficiency. Further upstream, the introduction of solvent vapor via a carrier gas bubbler and liquid build-up in the printhead were seen to affect the quantitative relationship between the light scattering data and the true deposition rate. Using this information, tightened controls of meaningful secondary parameters were implemented to improve the batch-to-batch consistency for printing a dielectric ink. In addition to advancing AJP process reliability for production, this work demonstrates the capability of inline optical measurements to provide insight into process physics and deconvolute competing mechanisms that underly variability.

additive manufacturing↗

Technical Evaluation of Accelerated Basin De-Inventory Material Addition to Sludge Batch 11

Savannah River Nuclear Solutions has a need to discard spent nuclear fuel (SNF), currently stored in L Basin, to the Defense Waste Processing Facility (DWPF) for vitrification. The Department of Energy (DOE) has approved the Accelerated Basin De-inventory (ABD) Program for discarding SNF via transfers from H-Canyon to the Savannah River Site (SRS) Liquid Waste (LW) system. The first ABD discards will occur during the preparation of Sludge Batch (SB) 11. An initial impact evaluation of the LW flowsheet was performed by the Savannah River National Laboratory (SRNL) prior to the approval of the ABD Program. This evaluation addressed the LW downstream facilities based on the current H-Canyon flowsheet sequence for the average ABD discard. The flowsheet evaluation only included aluminum-clad SNF, specifically Materials Test Reactor (MTR) fuel and High Flux Isotope Reactor (HFIR) fuel similar to the planned SB11 discard. Following this evaluation, the flowsheet has been slightly altered to address (i) new nuclear criticality safety controls for DWPF that credit a higher amount of gadolinium as a neutron poison for all of the enriched uranium contained in a SB and (ii) potential additions of the H-Canyon neutralized fuel stream prior to the Low Temperature Aluminum Dissolution (LTAD) process in Tank 51. The early introduction of ABD material into the SB assembly process is being investigated to provide flexibility regarding transfer opportunities for H-Canyon to Tank 51 for SB11 and future sludge batches.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Open Specy 1.0: Automated (Hyper)spectroscopy for Microplastics

Microplastic spectral analysis is one of the most time-consuming processes in studying microplastic pollution, often requiring days per sample. Researchers are transitioning to automated batch and hyperspectral image analysis techniques to enhance efficiency. Open Specy, initially aimed at manual single-spectrum analysis, has now integrated automated methods. This updated version, Open Specy 1.0, introduces several new features, including two algorithms for automated processing (smoothing and particle compression), an extensive library containing over 40,000 open-source Raman and FTIR spectra, and two machine learning classifiers (logistic regression and k medoids) developed from this library. Furthermore, it includes a revamped user interface, an R package, and a benchmark data set for testing future advancements in automated techniques. Researchers evaluated various configurations for hyperspectral smoothing, particle identification, compression, and splitting, to achieve combined recovery rates between 50 and 150% particle counts, identities, and sizes with a coefficient of variation (CV) of less than 40% (the accredited standard). Mean absorbance times the standard deviation provided a consistent particle identification. Hyperspectral smoothing led to a 96% combined recovery rate and reduced variability (CV = 38%) compared to the 86% recovery (CV = 83%) of nonsmoothed controls. Additionally, compressing spectra for particles was significantly faster (>3x) and showed similar accuracy but with reduced variability than processing each pixel individually. Key challenges persist in automating spectral analysis, particularly in refining particle splitting algorithms, and improving identification routines to minimize false positives and negatives. In conclusion, new methods in sample preparation for better stabilization and dispersion of particles could overcome some of these issues.

13 HYDRO ENERGY↗

Ceramics in gas turbines - Powder and process characterization

The role of powder and process characterization in producing high quality silicon nitride and silicon carbide components, for gas turbine applications, is described. Some of the intrinsic properties of various forms of Si3N4 and SiC are listed and limitations of such materials' availability have been pointed out. The essential features/parameters to characterize a batch of powder have been discussed including the standard techniques for such characterization. In process characterization, parameters in sintering, reaction sintering, and hot pressing processes are discussed including the factors responsible for strength limitations in ceramic bodies. It is inevitable that significant improvements in material properties can be achieved by reducing or eliminating the strength limiting factors with consistent powder and process characterization along with process control.

Dutta, S.↗

Amine Functionalized Electrospun Cellulose Nanofibers for Fluoride Adsorption from Drinking Water

In this study, we synthesized amine functionalized cellulose nanofiber based adsorbent for effective removal of dissolved fluoride ions from groundwater samples. Cellulose acetate was electrospun into nanofibers followed by deacetylation to yield cellulose nanofibers which were then treated with ethylenediamine to prepare amine functionalized cellulose fabric to be used as an adsorbent. As- synthesized adsorbent was first characterized by scanning electron microscopy and Fourier transform infrared spectroscopy for physiochemical characteristics. Fluoride adsorption studies were then carried out under batch mode to study the influence of various parameters on adsorption process. Amine functionalized cellulose nanofibrous mat was found to be effective with high adsorption efficiency for removal of fluoride ions from aqueous solution, even at low fluoride concentrations (< 5 mg L{sup −1}). Adsorption mechanism of fluoride onto prepared cellulose nanofibers based adsorbent was explained from the studies of isotherms, kinetic and thermodynamic parameters. Field studies conducted using this amine functionalized cellulose nanofibrous mat revealed the suitability and effectiveness of adsorbent for fluoride removal from contaminated groundwater.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Characterization of Nonmetallic Inclusions in 18CrNiMo7-6

The detrimental effect of nonmetallic inclusions (NMIs) in steels on, e.g., fatigue lifetime is well known. In order to increase the durability and safety of materials and components, inclusion control and a deep understanding of inclusion formation are essential. The present study examines the formation of inclusions as well as their content, type, morphology, and size distribution for different batches of the steel alloy 18CrNiMo7-6 (AISI 4317), which was processed with various refractory crucible materials. To this end, extensive metallographic investigations were carried out including fracture surface analyses, metallographic sections, and the chemical extraction of inclusions. Scanning electron microscopy supported by energy-dispersive X-ray spectroscopy was used alongside electron backscatter diffraction for the qualitative and quantitative analysis of the NMIs. Oxide contents were found to have a significant effect on sulfide precipitation behavior, and had a strong impact on the resulting sizes and numbers of inclusions. The formation and growth of sulfides and oxide-sulfides featuring different morphologies is discussed on the basis of these experimental results.

36 MATERIALS SCIENCE↗

High-level co-production of 3-hydroxypropionic acid and 1,3-propanediol from glycerol: Metabolic engineering and process optimization

3-Hydroxypropionic acid (3-HP) and 1,3-propanediol (1,3-PDO) are value-added chemicals with versatile applications in the chemical, pharmaceutical, and food industries. Nevertheless, sustainable production of 3-HP and 1,3-PDO is often limited by the lack of efficient strains and suitable fermentation configurations. We report attempts have been made to improve the co-production of both metabolites through metabolic engineering of Escherichia coli and process optimization. First, the 3-HP and 1,3-PDO co-biosynthetic pathways were recruited and optimized in E. coli, followed by coupling the pathways to the transhydrogenase-mediated cofactor regeneration systems that increased cofactor availability and product synthesis. Next, pathway rebalancing and block of by-product formation significantly improved 3-HP and 1,3-PDO net titer. Subsequently, glycerol flux toward 3-HP and 1,3-PDO synthesis was maximized by removing metabolic repression and fine-tuning the glycerol oxidation pathway. Lastly, the combined fermentation process optimization and two-stage pH-controlled fed-batch fermentation co-produced 140.50 g/L 3-HP and 1,3-PDO, with 0.85 mol/mol net yield.

1,3-propanediol↗

pCAM precursor produced from electroextraction technology and its application in synthesis of NMC 811 cathode material

The synthesis and characterization of LiNi 0.8 Co 0.1 Mn 0.1 O 2 (LNMC811) cathodes produced from recycled hydroxide precursors obtained from spent lithium-ion batteries is evaluated. Two precursor batches (Sample 1 and Sample 2) are prepared using modified recycling processes to examine how residual impurities and processing conditions influence the properties of the regenerated materials. Structural and compositional characterization by X-ray diffraction, ICP and SEM shows that the recycled precursors exhibit layered hydroxide structures containing both α Ni(OH) 2 and β Ni(OH) 2 phases. Trace impurities including sodium, boron, and aluminum are detected and partially mitigated during processing, with boron found to play a beneficial role in electrochemical behavior. Following lithiation with lithium carbonate and lithium hydroxide at 800 °C under an oxygen rich atmosphere, the resulting LNMC811 materials show electrochemical performance comparable to conventionally synthesized cathodes. Sample 2, which contains higher boron levels and improved cation ordering, delivers an initial discharge capacity of 174 mAh g -1 and retains more than 93 percent of its capacity after 50 cycles. The stable cycling behavior and structural integrity of these materials demonstrate that recycled precursors can be converted into high performance layered cathodes and support recycling as a practical and sustainable route for lithium-ion battery manufacturing.

25 ENERGY STORAGE↗

Compression molding of anisotropic NdFeB bonded magnets in a polycarbonate matrix

Anisotropic bonded Nd 2 Fe 14 B (NdFeB) magnets in a polycarbonate (PC) binder matrix are fabricated using a compression molding process. The weight fractions (w.f.) of NdFeB in PC on the batch mixer are 20, 50, 75, 85 and 95% compared to the twin screw extruder with 20, 50 and 75% respectively. The density of the 95% batch mixed magnets fabricated was 5.34 g/cm 3 and the magnetic properties are, intrinsic coercivity H ci = 942.99 kA/m, remanence B r = 0.86 T, and energy product (BH) max = 120.96 kJ/m 3 . Furthermore, the measured tensile properties are in the range of 27-59 MPa, comparable to that of polyamide (PA), polyphenylene sulfide (PPS) bonded magnets and demonstrating potential for bonded magnet applications. Scanning electron microscopy showed that the onset of failure occurs in the magnetic particle- matrix interface. This study demonstrates that compression additive molding technique can be used to fabricate high performance NdFeB polycarbonate composite magnets with improved mechanical properties.

36 MATERIALS SCIENCE↗

Size tunable elemental copper nanoparticles: extracellular synthesis by thermoanaerobic bacteria and capping molecules

Bimodal sized elemental copper (Cu) nanoparticles (NPs) were synthesized from inexpensive oxidized copper salts by an extracellular metal-reduction process using anaerobic Thermoanaerobacter sp. X513 bacteria in aqueous solution. The bacteria nucleate NPs outside of the cell, and they control the Cu2+ reduction rate to form uniform crystallites with an average diameter of 1.75 0.46 m after 3-day incubation. To control the size and enhance air stability of Cu NPs, the reaction mixtures were supplemented with nitrilotriacetic acid as a chelator, and the surfactant capping agents oleic acid, oleylamine, ascorbic acid, or L-cysteine. Time-dependent UV-visible absorption measurements and XPS studies indicated well-suspended, bimodal colloidal Cu NPs (70 150 and 5 10 nm) with extended air-stability up to 300 min and stable Cu NP films surfaces with 14% oxidation after 20 days. FTIR spectroscopy suggested that these capping agents were effectively adsorbed on the NP surface providing oxidation resistance in aqueous and dry conditions. Compared to previously reported Cu NP syntheses, this biological process substantially reduced the requirement for hazardous organic solvents and chemical reducing agents, while reducing the levels of Cu oxide impurities in the product. This process was highly reproducible and scalable from 0.01 to 1-L batches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sequencing and analysis of 131 SARS-CoV-2 isolates in previously sampled and unsampled regions of Jordan from 2020 to 2023

The Hashemite Kingdom of Jordan remains an understudied country for next generation sequencing analysis of SARS-CoV-2 genomes collected during the 2019 pandemic. Here we provide 131 additional reference genomes collected between 2020–2023 from SARS-CoV-2-positive patients across Jordan. Phylogenetic analysis supports existing pandemic narratives of changing clade dominance over time and adds genomes in novel Jordanian locations and timepoints to make Jordan SARS-CoV-2 databases more comprehensive. Samples from the less-sequenced cities of Ajloun, Jaresh, Karak, and Madaba identified previously unreported lineages while Amman, Irbid, and Zarqa have existing sequencing efforts bolstered. Despite many incomplete patient records and a relatively small sample size, we observe interesting symptom patterns that support existing global and Jordanian pandemic narratives. We note how in-country COVID-19 pandemic genomic studies showcase Jordan’s efforts to expand next generation sequencing capabilities, especially through the leveraging of EDGE COVID-19, a bioinformatics platform for performing rapid, batched analysis of SARS-CoV-2 sequencing that streamlines sample processing prepared from a network of hospital locations.

60 APPLIED LIFE SCIENCES↗

GLEAM: Galaxy Line Emission & Absorption Modeling

We present Galaxy Line Emission & Absorption Modeling (gleam), a Python tool for fitting Gaussian models to emission and absorption lines in large samples of 1D extragalactic spectra. gleam is tailored to work well in batch mode without much human interaction. With gleam, users can uniformly process a variety of spectra, including galaxies and active galactic nuclei, in a wide range of instrument setups and signal-to-noise regimes. gleam also takes advantage of multiprocessing capabilities to process spectra in parallel. With the goal of enabling reproducible workflows for its users, gleam employs a small number of input files, including a central, user-friendly configuration in which fitting constraints can be defined for groups of spectra and overrides can be specified for edge cases. For each spectrum, gleam produces a table containing measurements and error bars for the detected spectral lines and continuum and upper limits for nondetections. For visual inspection and publishing, gleam can also produce plots of the data with fitted lines overlaid. In the present paper, we describe gleam’s main features, the necessary inputs, expected outputs, and some example applications, including thorough tests on a large sample of optical/infrared multi-object spectroscopic observations and integral field spectroscopic data. gleam is developed as an open-source project hosted at https://github.com/multiwavelength/gleam and welcomes community contributions.

79 ASTRONOMY AND ASTROPHYSICS↗

Selecting optimum algorithms for image processing

Collection of registration, compression, and classification algorithms allows users to evaluate approaches and select best one for particular application. Program includes six registration algorithms, six compression algorithms, and two classification algorithms. Package also includes routines for evaluating effects of processing on image data. Collection is written in FORTRAN IV for batch execution.

Jaroe, R. R.↗