Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “batch sampling”

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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

ETF Grout Expansion: Effects of Different Slags and Struvite Precipitation Protocols (Stirring Time)

The ETF ammonia tolerant grout waste form was developed by the Vitreous State Laboratory (VSL) to stabilize ammonium and thereby prevent emission of ammonia vapor during solidification of an ammonium-rich, concentrated sodium sulfate aqueous waste stream generated at the Hanford Effluent Treatment Facility (ETF). VSL personnel did not observe expansion in samples prepared during the waste form development work. However, Savannah River National Laboratory (SRNL) personnel detected expansion, in a few ETF grout samples, up to ~ 20 percent vertical expansion, while preforming work scope to evaluate the effect of ETF brine compositional ranges on the precipitation and solidification processes. The initial work requests can be found in Washington River Protection Services (WRPS) Statement of Work (SOW, Requisitions #: 339922 Revisions 0 and 1, March 11, 2021, and November 2021, respectively. As a result of the waste form expansion observed by SRNL, additional evaluation was requested by WRPS SOW Requisitions #: 356730 Revision 0 and Revision 1, February 1, 2022, and July 11, 2022, respectively. The goal of these requests was to determine whether differences in the slags and / or in sample preparation protocols used by VSL and SRNL were the cause of the expansion observed in the SRNL samples. G. Chen, WRPS, arranged a materials exchange between VSL and SRNL and coordinated the VSL protocol(s) for grouting and curing 1L batches of Base Case ETF base case simulant. Materials were exchanged between VSL and SRNL. Both laboratories performed the VSL struvite precipitation-solidification protocol and cured samples for at least 28 days. Differences in VSL and SRNL slag compositions, mineralogy and particle size results in themselves or combined were determined to not be the cause of the expansion because all samples expanded regardless of whether the VSL or SRNL slags were used. The fundamental cause of the observed expansion could not be attributed to minor variations in the following: 1) chemistry of the slag and other reagents, 2) container wall thickness, 3) ambient bench top curing conditions at VSL and SRNL, 4) pH adjustments to 7 ± a few tenths of unit, nor 5) stirring time between the precipitation and solidification process steps. Additional observations include: grout samples prepared with VSL slag expanded less than those prepared with the SRNL slag and, based on a very limited sample set, some samples stirred for longer times expanded less than those stirred for 20 minutes.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRSDate not supplied

The Effect of Temperature on the Preservation of Volatile-Rich Lunar Samples

Introduction. The Moon’s south pole is a high-priority target for human exploration and scientific study. This interest is, in part, due to the presence of Permanently Shadowed Regions (PSRs), which could contain high concentrations of unique volatiles at cryogenic temperatures [1]. Returned samples from PSRs may include a unique combination of rocks, regolith, and volatile species, providing unprecedented insights into the history of the Solar System and the potential for resource utilization on the Moon. However, because PSR samples are cryogenic up-on collection, lunar polar sample return will eventually require cold stowage for the journey from the Moon to Earth. Without cold stowage, PSR sample return will likely result in phase changes and chemical reactions within the volatile component of the sample, which would negatively impact the resulting scientific studies of those samples. This abstract summarizes the initial results from an ongoing characterization of analog PSR samples at a range of temperatures, with the goal of defining the temperatures needed for a flight cold stowage freezer. Background. Based on remote sensing observations of the Moon [2], south polar PSRs range in temperature from ~120K for small and/or shallow PSRs to ~20K at the most extreme locations in large, deep PSRs. A range of volatiles have been hypothesized to exist at the surface or subsurface of the lunar poles [3-5 and others]. This hypothesis was verified when the LCROSS mission impacted the <50-K PSR in the crater Cabeus, detecting a range of volatiles from water to low condensation temperature species such as H2S and methane [6]. Species such as H2S and ammonia (also detected by LCROSS) are also highly reactive, and increase the likelihood of chemical reactions at elevated (non-cryogenic) temperatures. At the Johnson Space Center’s Planetary Exploration and Astromaterials Research Laboratory (JSC-PEARL), we have developed a volatile-bearing lunar simulant that incorporates several of the species detected by LCROSS [Table 1] mixed cryogenically with the USGS Lunar Highlands Type (LHT) regolith simulant. The new volatile-regolith simulant will be used to assess the degree of sample alteration at room temperature, -20°C, -80°C, and -196°C (liquid nitro-gen), over a two-week period. Room temperature samples represent those likely to be returned during initial missions without cold stowage, -20°C provides an analog to Apollo cold curated samples, -80°C is the temperature of multiple flight payload freezers (e.g., MELFI), and -196°C is analogous to lunar PSRs. Two weeks is an approximation of the time between sample collection and Earth return for initial Artemis missions. Over this period of time, sample head-space gases will be analyzed using a Universal Gas Analyzer (UGA, a type of mass spectrometer) coupled with a Baratron pressure sensor. After testing, the regolith component of the simulant will be purged of volatiles and preserved for future electron beam and/or FTIR analysis. Experimental Procedure. Volatile-regolith simulants will be produced as an initial homogenous batch; this batch will then be distributed into aliquots (gas chromatography/GC vials or cryo vials), ensuring that each sample has the same starting composition and conditions [Fig. 1]. In addition to the “full” simulant shown in Table 1, less complex simulant compositions will be used as baseline and control samples [Table 2]. Aliquots will be produced in triplicate for each simulant composition, storage temperature, and date of sampling. Headspace gases in all Day 0 samples will be analyzed by the UGA immediately. Cold storage samples for future analytical days will be placed in freezers appropriate to their target temperatures (-20°C, -80°C, -196°C). For ambient-temperature samples, regolith and regolith-water samples will be stored in a fume hood, while the full simulant will be stored in a sealed Parr vessel for safety; no other simulants (RWCM/ RWCM+) will be stored at ambient temperature for this test. Samples will be analyzed by UGA in this manner on each Analysis Day outlined in Table 2. Analytical Data. The UGA measures the partial pressures in a single sample aliquot over a set mass range of 0-105 atomic mass units (AMU) [Figure 2]; this set range was selected to slightly exceed the mass of the highest-mass expected reaction product (H2SO4). The Baratron complements the UGA by measuring the total pressure in the headspace of a sample vial. Coupled together, the quantitative abundances of gases will be monitored throughout the test. UGA analyses of the triplicate samples for each storage temperature, day, and simulant composition will be averaged, and standard deviations for each will be calculated. The compositions of starting species (shown in Table 1) will be characterized as a function of time, and the presence of any new compounds (reaction products) will be monitored as well. Total pressures will be recorded for each sample analysis, and any samples that show signs of leakage (e.g., a significant reduction in pressure or simulant volatiles) will be discarded. Anticipated Results. Testing is planned to begin in January 2022. The resulting data will allow compositional and phase changes in the volatile component of the simulants to be determined. Both the reduction in initial compounds and the addition of reaction products are expected to be observed. In addition, the relative efficacy of the different temperatures at pre-serving the initial composition of the simulants will be quantified. Finally, the regolith component of each sample will be argon-purged and stored in a controlled environment for future laboratory analysis. Compositional and morphological changes in the regolith are expected for samples above 0°C. This test will be repeated three times over the course of 2022. Understanding the effect of temperature on both the volatile and regolith components of analog lunar materials will allow requirements for a cold stowage freezer to be developed. The implementation of cold stowage for lunar polar missions will maximize the preservation of returned samples, enabling ground-breaking lunar and Solar System volatiles science for decades to come.

J L Mitchell↗
DOE OSTI2026

ML-based Micro-CT SOFC Microstructure Models (from Kent 2026 Microstructural Augmentation paper)

Overview -------------------------- This repository contains datasets from the manuscript **"Enhanced Generalizability to Deep-Learning Quantification of 3D Microstructural Characteristics through Microstructurally Aware Augmentation of Scarce Data"** (*William F. Kent, Rochan Bajpai, Rachel C. Kurchin, William K. Epting, Harry W. Abernathy, Paul A. Salvador. Submitted 2026*). The methods are also described in the dissertation **Data Intensive Analysis of Solid Oxide Cell Microstructures** (*Doctoral dissertation, Carnegie Mellon University, 2025*). The datasets here are trained convolutional neural network (CNN) models for predicting key microstructural properties of solid oxide cell (SOC) electrodes from low-res, 2-channel 3D images, as well as some helpful code. The parameters for input images are provided in the paper. Sample data is provided in the file `Combined_anode_aug_dual_1k_examples` - that particular data was used to train `anode_all_aug.pth` and will work most accurately with that model. Please familiarize yourself with all caveats on accuracy and applicability, as detailed in the associated paper. Usage -------------------------- The basic usage is as follows, assuming `model_fn` is the path to the .pth file, and `X` is 2-channel input image(s) of the proper dimensions (either one image of shape `[2,12,24,24]`, or a batch of N input images of shape `[N,2,12,24,24]`): from CNN_inferencer import load_model_for_inference model = load_model_for_inference(model_fn) y_predicted = model(X) The model object automatically handles input scaling and output de-scaling based on the way the models were trained - in other words, pass in a 2-channel micro-CT image, and it will output microstructural property values in real units. ## Other model object attributes Note that model has useful attributes other than its forward pass model(X). * `model.output_descaler` - returns the output descaler object. Model does the de-scaling when generating inferences, but you may want to re-use this de-scaler on other values to e.g. compare predictions to ground truth from already-scaled training data. * `model.prop_names` - Gives the property names of the predicted y values, in order. Only exists if there's an output scaler as part of the model object, which there will be in the models provided here. ## Usage with sample data Here is a short script to use with the included sample data. from CNN_inferencer import display_predictions, load_model_for_inference, calculate_mape, parity_plot import h5py import numpy as np model_fn = 'anode_all_aug.pth' data_fn = 'Combined_anode_aug_dual_1k_examples.h5' N_samples = 200 figure_outdir = '.' model = load_model_for_inference(model_fn) with h5py.File(data_fn,'r') as f: XX = f['X'] #These are the 2-channel 3D images yy = f['y'] #These are the ground-truth microstructural properties, but they have been scaled for training - need to de-scale below N = XX.shape[0] #How many images total in the input data file #Run inferences on N_samples random samples from XX. #Run in a batch, much more efficient than one at a time. ii = np.random.choice(N,N_samples,replace=False) ii.sort() y_pred = model(XX[ii]) #Get the original/true (but normalized/scaled) values from the training dataset... #Because they were normalized, they are not in real units yet. So let's also de-scale them using model.output_scaler. y_true = model.output_scaler.transform(yy[ii]) #Let's display actual values for just 5 random ones for i in np.random.choice(N_samples,5,replace=False): display_predictions(y_true[i], y_pred[i], model.prop_names) #Make parity plots for each property (ground truth vs predicted values) #Also label each plot with the mean abs. percent error (MAPE) of the predicted values for i,key in enumerate(model.prop_names): mape = calculate_mape(y_true[:,i], y_pred[:,i]) parity_plot(y_true[:,i], y_pred[:,i], figure_outdir, key, extra_title=f' ({mape:.2f}% MAPE)')

3D microstructure↗
DOE OSTI2020

Sample Dependence of Magnetism in the Next-Generation Cathode Material LiNi 0.8 Mn 0.1 Co 0.1 O 2

We present a structural and magnetic study of two batches of polycrystalline LiNi 0.8 Mn 0.1 Co 0.1 O 2 (commonly known as Li NMC 811), a Ni-rich Li ion battery cathode material, using elemental analysis, X-ray and neutron diffraction, magnetometry, and polarized neutron scattering measurements. We find that the samples, labeled S1 and S2, have the composition Li 1–x Ni 0.9+x–y Mn y Co 0.1 O 2 , with x = 0.025(2), y = 0.120(2) for S1 and x = 0.002(2), y = 0.094(2) for S2, corresponding to different concentrations of magnetic ions and excess Ni 2+ in the Li + layers. Both samples show a peak in the zero-field-cooled (ZFC) dc susceptibility at 8.0(2) K, but the temperature at which the ZFC and FC (field-cooled) curves deviate is substantially different: 64(2) K for S1 and 122(2) K for S2. The ac susceptibility measurements show that the transition for S1 shifts with frequency whereas no such shift is observed for S2 within the resolution of our measurements. Our results demonstrate the sample dependence of magnetic properties in Li NMC 811, consistent with previous reports on the parent material LiNiO 2 . Here, we further establish that a combination of experimental techniques is necessary to accurately determine the chemical composition of next-generation battery materials with multiple cations.

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

Pore connectivity influences mass transport in natural rocks: Pore structure, gas diffusion and batch sorption studies

For this work, six rocks (one granodiorite, one limestone, two chalks, one mudstone, and one dolostone) with different extents of heterogeneity at six different particle sizes (from 75 to 8000 μm) were studied to describe the effects of pore connectivity on mass transport. The methods applied were (i) porosity measurement of granular rocks, (ii) analyses of gas-phase diffusive transport in a bed of packed particles, along with a solid quartz method at these six particle sizes being developed to identify the contribution of intraparticle diffusion, and (iii) batch sorption tests of multiple ions (anions and cations) with subsequent analyses of inductively coupled plasma-mass spectrometry. Granular porosity measurement results reveal that with decreasing particle sizes, the effective porosities for the “heterogenous” group of rocks (Grimsel granodiorite and Edwards limestone) increase, whereas the porosities of another “homogeneous” group (two Israel chalk samples, Japan mudstone, and Wyoming dolostone) remain constant. Gas diffusion results show that the intraparticle gas diffusion coefficient among these two sample groups, varying in the magnitude of 10 -8 to 10 -6 m 2 /s, are not directly correlated to the porosity differences. Moreover, the batch sorption work displays a different affinity of rocks for various tracers. For Grimsel granodiorite, Japan mudstone, and Wyoming dolostone, the adsorption capacity of Sm 3+ and Eu 3+ increases as the particle size decreases. In general, this integrated research of grain size distribution, granular rock porosity, intraparticle diffusivity, and ionic sorption capacity gives insights into the pore connectivity effect on both physical and chemical transport behaviors for different lithologies and/or different particle sizes.

58 GEOSCIENCES↗
DOE OSTI2024

Effects of Interactions Between Produced Formation Fluid and Rock Matrix on Pore Structure of Caney Shale, Southern Oklahoma

ABSTRACT: Rock-fluid interactions change properties of shales during exploitation. To investigate effects of rock-fluid interactions on pore structure of shales matrix after hydraulic fracturing, powder samples from two late Mississippian Caney Shale cores in the Ardmore Basin, southern Oklahoma, were used to react with formation produced fluid from the field in the batch reactor analysis. X-ray diffraction for mineralogy and Low-pressure nitrogen adsorption isotherms for pore structure were measured for original, after-7days, and after-30days samples. Results show that the samples consist mainly of quartz, followed by clay minerals, carbonates, and feldspar. The pore sizes of micropore (<2 nm) and mesopore (2-50 nm) increase 14%-233% due to dissolution of pyrite, feldspar, and carbonates after 7 days. Due to the transformation from smectite to illite and the increase of pore size, the specific surface area (SSA) decreases after 7-days interactions. After 30-days interactions, the micropore volume slightly increases and the mesopore and macropore volume decreases. Due to the decrease of pore size, the SSA of 30-days reacted samples increases correspondingly and is lower (for the clay-rich sample) or higher (for the calcareous sample) than that of the unreacted samples. Findings improve our understanding of dynamic alteration of shale properties during production. 1. INTRODUCTION Energy demand will continuously grow owing to the increasing global population as well as energy consumption (EIA, 2023). On the other hand, shale gas and oil reshaped the energy market in the United States, enabling the United States to become a net-export of natural gas country in 2017 (EIA, 2023). However, shale reservoirs are challenging tight formations that are still poorly understood in the extraction and production of hydrocarbons (Ross and Bustin, 2009; Curtis et al., 2012; Xiong et al., 2015, 2021a; Li Y. et al., 2016; Gong et al., 2019a; Benge et al., 2021; Awejori et al., 2022; Huang et al., 2022). One of the most challenging topics is the rock-fluid interactions post hydraulic fracturing and its subsequent impacts on the pore structures of fractured formation matrix.

Xiong, Fengyang↗
DOE OSTI2026

Accelerated 133 Xe Quantification in Samples Containing Significant 133 mXe

The quantification of 133 Xe in the presence of its mother radionuclide 133 mXe requires the full quantification of both to perform the ingrowth correction for 133 Xe. Due to the nature of both of these radionuclides, the 133 mXe requires significantly more time to quantify by High Purity Germanium (HPGe) detectors due to lower production yields, lower gamma emission probabilities, and lower detection efficiencies. This work shows that 133 Xe and 133 mXe quantification can be accelerated by measuring the 133m:133 activity ratio for a large batch of material and applying this activity ratio to assays of lower activity subsamples of the same batch of material. Included in this report are derivations of the required decay correction equations, and experiments using actual samples to validate the performance of these equations. A detector calibration method is also shown that leverages this method as an alternative to existing calibration methods for 133 mXe quantification.

133mXe↗
DOE OSTI2022

Automated Defect Identification For Triso Fuels

The developed code is to be used to identify manufacturing defects of nuclear fuel kernels using image processing methods. Past batches of TRi-structural ISOtropic particle (TRISO) fuel kernels have on occasion contained fissures that result in the fuel batch not meeting specifications. The developed code automates the inspection process of these kernels. The code analyzes micrographs of TRISO fuel kernels and outputs a count of total kernels in the sample, a count of the number of defective particles in the sample, as well as processed images for more effective manual inspection. This information output will be used to help identify if defective kernels are present in a fuel batch and quantify the countable fissure fraction.

Oncken, JosephE.↗
DOE OSTI2023

Simultaneous isotopic analysis of fission product Sr, Mo, and Ru in spent nuclear fuel particles by resonance ionization mass spectrometry

Abstract Fission product Sr, Mo, and Ru isotopes in six 10-μm particles of spent fuel from a pressurized water reactor were analyzed by resonance ionization mass spectrometry (RIMS) and evaluated for utility in nuclear material characterization. Previous measurements on these same samples showed widely varying U, Pu, and Am isotopic compositions owing to the samples’ differing irradiation environments within the reactor. This is also seen in Mo and Ru isotopes, which have the added complication of exsolution from the UO 2 fuel matrix. This variability is a hindrance to interpreting data from a collection of particles with incomplete provenance since it is not always possible to assign particles to the same batch of fuel based on isotopic analyses alone. In contrast, the measured 90 Sr/ 88 Sr ratios were indistinguishable across all samples. Strontium isotopic analysis can therefore be used to connect samples with otherwise disparate isotopic compositions, allowing them to be grouped appropriately for interpretation. Strontium isotopic analysis also provides a robust chronometer for determining the time since fuel irradiation. Because of the very high sensitivity of RIMS, only a small fraction of material in each of the 10 μm samples was consumed, leaving the vast majority still available for other analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

MONet/1000 Soils metagenome pathway modelling narrative w/ auto batch import

This narrative performs metabolic modeling and flux balance analysis (FBA) using metagenome-assembled genomes (MAGs) from the 1000 Soils samples, as described by Song et al. (2026, accepted). The set of MAGs (in FASTA format) is converted into a set of assembly objects compatible with functional annotation via RASTtk, yielding a set of genome objects that undergo metabolic modeling via OMEGGA. These genome objects are then used to conduct FBA, generating tables of metabolite uptake rates across the MAGs under investigation.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2020

JSC-Rocknest: A Large-Scale Mojave Mars Simulant (MMS) Based Soil Simulant for In-Situ Resource Utilization Water-Extraction Studies

The Johnson Space Center-Rocknest (JSC-RN) simulant was developed in response to a need by NASA's Advanced Exploration Systems (AES) In-Situ Resource Utilization (ISRU) project for a simulant to be used in component and system testing for water extraction from Mars regolith. JSC-RN was designed to be chemically and mineralogically similar to material from the aeolian sand shadow named Rocknest in Gale Crater, particularly the 1-3 wt.% low temperature (<450 ºC) water release as measured by the Sample Analysis at Mars (SAM) instrument on the Curiosity rover. Sodium perchlorate, goethite, pyrite, ferric sulfate, regular and high capacity granular ferric oxide, and forsterite were added to a Mojave Mars Simulant (MMS) base in order to match the mineralogy, evolved gases, and elemental chemistry of Rocknest. Mineral and rock components were sent to the United States Geological Survey (USGS) in Denver for mixing. Approximately 800 kg of JSC-RN was sent back to NASA in 5 gallon buckets, which were subsampled and characterized. All samples of the USGS-produced simulants had similar evolved gas profiles as a small prototype batch of JSC-RN made in JSC laboratories, with the exception of HCl, and were similar in terms of mineralogy and total chemistry. Also, all JSC-RN subsamples were homogenous and had similar mineralogy, total chemistry, and low-temperature evolved gas profiles as the Rocknest aeolian sand shadow examined with Curiosity’s instrument suite on Mars. In particular, the low temperature water releases were similar and the amount of water evolved from JSC-RN at <450 ºC was similar to the water content of Rocknest based on SAM water peak integrations. Overall, JSC-RN is ideally suited for ISRU studies of water extraction of global martian soil due to its excellent agreement with measured properties of martian soils and its proven feasibility for large-scale production.

Simulant↗
DOE OSTI2022

Melt Processing Pretreatment Effects on Enzymatic Depolymerization of Poly(ethylene terephthalate)

Poly(ethylene terephthalate) (PET) is a common thermoplastic material, used in a wide variety of applications (i.e., bottles, fabrics, packaging, electronics, and automotive components). Increasing demand for PET has precipitated a need for improved recycling technology, especially for single-use PET waste. Recently, enzymatic depolymerization has shown promise as an environmentally responsible alternative for PET chemical recycling that yields economically useful products (e.g., terephthalic acid, adipic acid, and ethylene glycol). However, the depolymerization system still suffers from low rates on crystalline PET substrates, and effects of realistic waste streams are not known. In our work, PET waste is pretreated using an ultra-high-speed twin-screw extruder system. PET substrates were modified by various processing pretreatments to allow enzymes better access to depolymerize substrate materials. The effect of varying throughput and mechanical shear on structural properties of the PET waste was analyzed using molecular weight and thermal characterizations. These pretreated samples exhibit modifications in molecular weight, glass transition temperature, crystallinity, and specific surface area. The unpurified leaf-branch compost cutinase enzyme produced from the fed-batch fermentation of Escherichia coli BL21(DE3) was used in enzymatic depolymerization, where a faster reaction was observed as crystallinity was decreased and the specific surface area was increased. The rate of terephthalic acid production was also significantly higher for samples processed at lower mechanical shear with higher throughputs. As a result, this work demonstrates the potential for tailoring pretreatments in pursuit of faster and more energy efficient PET recycling using enzymes, with facile adaptation to the industrial scale for the circular economy.

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

Preliminary Characterization and Evaluation on FFF Manufactured 316H and ODS Steels

The Advanced Materials and Manufacturing Technology (AMMT) program develops cross-cutting technologies in support of a broad range of nuclear reactor technologies and maintains U.S. leadership in materials and manufacturing technologies for nuclear energy applications. The overarching vision of AMMT is to accelerate the development, qualification, demonstration, and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy. Solid-state advanced manufacturing techniques can overcome some of the challenges in liquid-based additive manufacturing (AM) processes and should therefore be considered in material design and manufacturing as well. The work presented in this report forms part of a study on solid-state AM techniques of 316 stainless steels (SS) and oxide dispersion strengthened (ODS) steel components and supports the vision and goals of the AMMT program relevant to accelerate the development and deployment of advanced manufacturing processes. Achieving this can provide a safety improvement through larger safety margins, economic benefit for higher efficiency during operation, and a cost reduction through more effective manufacturing processes and less waste. This study provides preliminary information on development of the fused-filament fabrication (FFF) process using different powder types to demonstrate the sensitivity, and therefore the characterization of these sample components. The full solid-state manufacturing feasibility study will be completed and reported in a final feasibility evaluation during 2025. The study investigation used two 14YWT ODS powder batches, which provided information and the effect of different powder morphologies on manufacturability. The two 316SS powders demonstrated the effect of powder size on the manufacturability using FFF. Two product forms, namely a honeycomb structure and flat samples, were manufactured to demonstrate the flexibility of product form.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Drying of strawberries with airborne ultrasound and other integrated dehydration mechanisms

This article presents a comprehensive investigation into the drying of strawberries using multiple dehydration methods with an emphasis on energy efficiency and sustainability. Initially, an airborne ultrasonic transducer with a frequency of 21 kHz was employed in batch operations to examine the effects of controlling parameters, including applied power, distance from the transducer plate, sample thickness, and sample holder type. The Energy Ratio, defined as the ratio of thermal energy required to evaporate moisture to ultrasonic energy, was observed to reach up to 2.2, particularly during the initial stages of drying. Subsequently, the Smart Dryer integrated airborne ultrasound (US) dehydration, slot jet reattachment (SJR) nozzle convective drying, infrared (IR) drying, and their combinations, enabling a systematic exploration of various drying conditions on the drying time and quality of strawberries. The integration of airborne US with SJR nozzles and IR drying demonstrates a promising approach for optimizing drying processes. This method not only preserves the quality of dried strawberries but also improves the energy factor to 0.88, reducing drying time by 89% compared with other conditions. Key quality attributes of the dried strawberries, such as color and water activity, were evaluated to understand the influence of each drying method. The findings highlight the potential of these integrated drying techniques as sustainable solutions for efficient and high-quality strawberry dehydration.

42 ENGINEERING↗
DOE OSTI2021

A high solids field-to-fuel research pipeline to identify interactions between feedstocks and biofuel production

Abstract Background Environmental factors, such as weather extremes, have the potential to cause adverse effects on plant biomass quality and quantity. Beyond adversely affecting feedstock yield and composition, which have been extensively studied, environmental factors can have detrimental effects on saccharification and fermentation processes in biofuel production. Only a few studies have evaluated the effect of these factors on biomass deconstruction into biofuel and resulting fuel yields. This field-to-fuel evaluation of various feedstocks requires rigorous coordination of pretreatment, enzymatic hydrolysis, and fermentation experiments. A large number of biomass samples, often in limited quantity, are needed to thoroughly understand the effect of environmental conditions on biofuel production. This requires greater processing and analytical throughput of industrially relevant, high solids loading hydrolysates for fermentation, and led to the need for a laboratory-scale high solids experimentation platform. Results A field-to-fuel platform was developed to provide sufficient volumes of high solids loading enzymatic hydrolysate for fermentation. AFEX pretreatment was conducted in custom pretreatment reactors, followed by high solids enzymatic hydrolysis. To accommodate enzymatic hydrolysis of multiple samples, roller bottles were used to overcome the bottlenecks of mixing and reduced sugar yields at high solids loading, while allowing greater sample throughput than possible in bioreactors. The roller bottle method provided 42–47% greater liquefaction compared to the batch shake flask method for the same solids loading. In fermentation experiments, hydrolysates from roller bottles were fermented more rapidly, with greater xylose consumption, but lower final ethanol yields and CO 2 production than hydrolysates generated with shake flasks. The entire platform was tested and was able to replicate patterns of fermentation inhibition previously observed for experiments conducted in larger-scale reactors and bioreactors, showing divergent fermentation patterns for drought and normal year switchgrass hydrolysates. Conclusion A pipeline of small-scale AFEX pretreatment and roller bottle enzymatic hydrolysis was able to provide adequate quantities of hydrolysate for respirometer fermentation experiments and was able to overcome hydrolysis bottlenecks at high solids loading by obtaining greater liquefaction compared to batch shake flask hydrolysis. Thus, the roller bottle method can be effectively utilized to compare divergent feedstocks and diverse process conditions.

09 BIOMASS FUELS↗
DOE OSTI2024

Continued Evaluation of the Use of a Raman Spectrometer for H-Canyon Dissolver Monitoring

Remote monitoring of dissolver activities in H-Canyon can help operators avoid delays associated with excessive levels of fuel fragments remaining after a run. SRNL has proposed that effective monitoring can be achieved by using a Raman spectrometer to measure NO 2 concentrations in the offgas stream sampled from the facility stack. Prior work (SRNL-STI-2021-00451) measuring the offgas from one dissolution batch of High Flux Isotope Reactor (HFIR) fuel suggested a relationship between %NO 2 levels and fragment height. Herein, we report the results of monitoring and analysis of the dissolution of four batches of Material Test Reactor (MTR) fuel. A rigorous quantitative relationship between %NO 2 measurements and fragment heights could not be established, due to high uncertainties associated with both measurements. Uncertainties with gas measurements are associated with the %NO 2 levels in the offgas being close to the detection limit for the analyzer. Alternative gas measurement strategies are discussed which could improve sensitivity and reduce uncertainty. Limitations to the precision of the probe measurements are also discussed. It is also noted that the offgas is an average of the products from simultaneous dissolution of elements in multiple wells. Detection of a high fragment height level in an individual well may be hindered by low levels in other wells.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2003

Protein crystals and their growth

Recent results on the associations between protein molecules in crystal lattices, crystal-solution surface energy, elastic properties, strength, and spontaneous crystal cracking are reviewed and discussed. In addition, some basic approaches to understanding the solubility of proteins are followed by an overview of crystal nucleation and growth. It is argued that variability of mixing in batch crystallization may be a source of the variation in the number of crystals ultimately appearing in the sample. The frequency at which new molecules join a crystal lattice is measured by the kinetic coefficient and is related to the observed crystal growth rate. Numerical criteria used to discriminate diffusion- and kinetic-limited growth are discussed on this basis. Finally, the creation of defects is discussed with an emphasis on the role of impurities and convection on macromolecular crystal perfection.

Review↗