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At least 559 records · Page 31

Application of an orcinol-ferric chloride colorimetric assay in barley and wheat accessions for water-extractable and total arabinoxylan

Arabinoxylan is an important hemicellulose potentially affecting wheat baking qualities, barley malt quality, and may impart prebiotic benefits. Water-extractable (WEAX) and total arabinoxylan (TOAX) were characterized in 204 wheat and barley accessions, respectively, using an orcinol-ferric chloride assay. WEAX measurement accuracy was optimum when glucose concentration was greater than 12–13 times pentose concentration. The modified method removed enough excess glucose spectral absorbance to make the corrected and uncorrected lines different, but still significantly correlated (p = 0.009, R = 0.94). Mean WEAX (expressed as percentage WEAX of TOAX) for the wheat accessions was 15.90%, ranging from 8.82% to 24.87%, and for barley accessions WEAX the mean was 7.10%, and ranged from 2.98% to 13.86%. Conclusions are 1) the assay is useful for a breeding program because of its semi-high throughput design for the simultaneous analysis of 16 (WEAX) to 40 (TOAX) barley lines or 24 (WEAX) to 40 (TOAX) wheat lines, 2) the trichromatic measurement reduces the impact of glucose, and 3) the broad range of WEAX measured showed that barley and wheat accessions vary in their extractable and unextractable components.

59 BASIC BIOLOGICAL SCIENCES↗

Critical review of functionalized silica sorbent strategies for selective extraction of rare earth elements from acid mine drainage

We report the ubiquitous and growing global reliance on rare earth elements (REEs) for modern technology and the need for reliable domestic sources underscore the rising trend in REE-related research. Adsorption-based methods for REE recovery from liquid waste sources are well-positioned to compete with those of solvent extraction, both because of their expected lower negative environmental impact and simpler process operations. Functionalized silica represents a rising category of low cost and stable sorbents for heavy metal and REE recovery. These materials have collectively achieved high capacity and/or high selective removal of REEs from ideal solutions and synthetic or real coal wastewater and other leachate source. These sorbents are competitive with conventional materials, such as ion exchange resins, activated carbon; and novel polymeric materials like ion-imprinted particles and metal organic frameworks (MOFs). This critical review first presents a data mining analysis for rare earth element recovery publications indexed in Web of science, highlighting changes in REE recovery research foci and confirming the sharply growing interest in functionalized silica sorbents. A detailed examination of sorbent formulation and operation strategies to selectively separate heavy (HREE), middle (MREE), and light (LREE) REEs from the aqueous sources is presented. Selectivity values for sorbents were largely calculated from available figure data and gauged the success of the associated strategies, primarily: (1) silane-grafted ligands, (2) impregnated ligands, and (3) bottom-up ligand/silica hybrids. These were often accompanied by successful co-strategies, especially bite angle control, site saturation, and selective REE elution. Recognizing the need to remove competing fouling metals to achieve purified REE “baskets,” we highlight techniques for eliminating these species from acid mine drainage (AMD) and suggest a novel adsorption-based process for purified REE extraction that could be adapted to different water systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Automatic information extraction from neutron radiography imaging to estimate axial fuel expansion in $\mathrm{EBR-II}$

Approximately 130,000 metal fuel pins were irradiated in the Experimental Breeder Reactor II (EBR-II) during its 30 years of operation to develop and characterize existing and prospective fuels. For many of the metal fuel irradiation experiments, neutron radiography imaging was performed to characterize fuel behavior, like fuel swelling. However, due to the lack of technology or resources, many of the images have not been processed or were processed manually through visual examination. This paper represents first-attempt to develop an image processing algorithm capable of automatically extracting information regarding the degree of fuel swelling from neutron radiography imaging. The algorithm was applied to 120 images of three different metallic fuel pin compositions—U-10Zr, U-8Pu-10Zr, and U-19Pu-10Zr. The algorithm performs operations of image intensity adjustment, image binarization, region finding, and labeling to extract information about fuel swelling. The average growth for U-10Zr was found to be 8.49% with 95% Confidence Interval (CI) [8.33 –8.66%], for U-8Pu-10Zr — 7.50% with 95% CI [7.23 – 7.78%], and for U-19Pu-10Zr — 3.15%, with 95% CI [2.40 – 3.91%]. The results obtained by applying this automatic image processing algorithm are consistent with previously reported studies of the same types of fuels. The automatic image processing algorithm will be expanded to include thousands of available neutron radiography images and different types of fuels to investigate empirical dependencies of fuel swelling, which can be subsequently applied to advanced fuel modeling. Results from this study can later be compared to BISON simulations to further benchmark modeling efforts and develop assessment cases.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Radiation induced amorphization of carbides in additively manufactured and conventional ferritic-martensitic steels: In-situ experiments on extraction replicas

In-situ irradiations using 1 MeV Kr 2+ ions in a transmission electron microscope were performed on extraction replica samples containing M 23 C 6 carbides and MX carbonitrides from two ferritic-martensitic (FM) steels: (i) 9%Cr-1%W-TaV based Eurofer97 and (ii) 9%Cr-1%Mo-VNb (all in wt.%) based additively manufactured (AM) Grade91 steel. The irradiations were performed between 100 and 773 K up to a maximum dose of ~2.4 displacements per atom (dpa). The M 23 C 6 carbides are highly susceptible to radiation induced amorphization (RIA), while the MX type nanoprecipitates are highly amorphization resistant across the entire irradiation temperature range. Between 100 and 423 K, RIA of M 23 C 6 carbides occurs very rapidly with critical amorphization doses ranging between ~0.35 and 0.9 dpa, increasing to higher doses at 573 K. Complete amorphization of the M 23 C 6 carbides up to doses of ~2.4 dpa is not possible at 773 K under the present irradiation conditions. The critical amorphization dose of M 23 C 6 carbides increases nearly exponentially with irradiation temperature. The critical temperature for the crystalline-to-amorphous phase transformation (T c→a ) of M 23 C 6 carbides irradiated as replica samples, i.e. without the surrounding metal matrix, was estimated to be ~812 K. Comparing the present results with neutron irradiation data on bulk samples reveals a decrease in the critical amorphization dose for M 23 C 6 and an increase of T c→a , highlighting the effect of dose rate on the amorphization behavior that is qualitatively consistent with literature on other non-metals. Changes in the minor chemistry of M 23 C 6 , such as presence or absence of W, V, Nb, Mo, seems to have little effect on the amorphization behavior. Here, in-situ irradiations on extraction replica samples provide a novel pathway to explore radiation tolerance of nanoprecipitates in nuclear structural materials

36 MATERIALS SCIENCE↗

Structural characterization of sugarcane lignins extracted from different protic ionic liquid pretreatments

Previous studies based on protic ionic liquids have shown them to be effective for extracting lignins from biomass. Moreover, ILs synthesized with amine cations can promote the insertion of nitrogen into lignin, favoring its valorization for industrial applications. Here, lignins extracted from sugarcane bagasse by eight different PILs were analyzed. Several techniques of characterization were employed (2D HSQC NMR, 31P NMR, GPC, Py-GC/MS, TGA, FTIR, and elemental analysis), seeking a deeper understanding of lignin structure post-PILS treatment. In particular, lignin obtained with acetate and lactate anions with monoethanolamonium cations showed similar structural compositions. Lignins obtained from ethylenediamonium cation combined anions acetate and lactate exhibited relatively higher molecular weights compared to the other lignins studied. The elemental analysis of these lignins further revealed the presence of nitrogen in their structures, suggesting that amination occurred. In this work we used PILs not yet reported in the literature for this purpose, and consequently obtained lignins with specific structures. Overall, our results demonstrated that depending on the PILs used, lignins with distinct properties could be obtained which might be used for value-added applications. This work covered new advances in elucidation of lignin chemical structure and opened a new path for lignin valorization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

U.S. lithium resources from geothermal and extraction feasibility

As the demand for electric vehicles (EVs) increases, demand for lithium (Li) is expected to grow over the coming decade. To satisfy the demand for rechargeable batteries, it is imperative to devise solutions for sufficient Li production. Additionally, even though commercial Li currently comes from conventional saline salar brine and spodumene ore extractions, efforts to retrieve Li from geothermal brines are increasing in popularity. In this paper, we evaluate the United States’ potential to supply Li from geothermal brines using Systems Dynamics modeling. The main goals are to assess (1) the viability of US Li supply from geothermal brines and (2) the potential supply chain impact of extracting Li from this source. Results show that Li supply from geothermal brines could (1) reach around 4% to 8% of total US Li supply and (2) be economically viable.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor

Mutational signature analysis is commonly performed in cancer genomic studies. Here, we present SigProfilerExtractor, an automated tool for de novo extraction of mutational signatures, and benchmark it against another 13 bioinformatics tools by using 34 scenarios encompassing 2,500 simulated signatures found in 60,000 synthetic genomes and 20,000 synthetic exomes. For simulations with 5% noise, reflecting high-quality datasets, SigProfilerExtractor outperforms other approaches by elucidating between 20% and 50% more true-positive signatures while yielding 5-fold less false-positive signatures. Applying SigProfilerExtractor to 4,643 whole-genome- and 19,184 whole-exome-sequenced cancers reveals four novel signatures. Two of the signatures are confirmed in independent cohorts, and one of these signatures is associated with tobacco smoking. In summary, this report provides a reference tool for analysis of mutational signatures, a comprehensive benchmarking of bioinformatics tools for extracting signatures, and several novel mutational signatures, including one putatively attributed to direct tobacco smoking mutagenesis in bladder tissues.

59 BASIC BIOLOGICAL SCIENCES↗

mzapy : An Open-Source Python Library Enabling Efficient Extraction and Processing of Ion Mobility Spectrometry-Mass Spectrometry Data in the MZA File Format

We have recently reported MZA, a new and simple mass spectrometry data structure based on the broadly supported HDF5 format and created to facilitate software development. While this format is inherently supportive of application development, the availability of a core library with standard mass spectrometry utilities greatly facilitates fast software development. Here, we present a Python library, mzapy, for efficient extraction and processing of mass spectrometry data in the MZA format. In addition to raw data extraction, mzapy contains supporting utilities enabling tasks including calibration, signal processing, peak finding, and generating plots. Being implemented in pure Python with minimal and largely standardized dependencies makes mzapy uniquely suited to application development in the multi-omics domain. The free and open source mzapy is built with extensibility in mind, and future development will support cloud computing and artificial intelligence/machine learning applications. The software source code is freely available at https://github.com/PNNL-m-q/mzapy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Robust Neural Network for Extracting Dynamics from Electrostatic Force Microscopy Data

Advances in scanning probe microscopy (SPM) methods such as time-resolved electrostatic force microscopy (trEFM) now permit the mapping of fast local dynamic processes with high resolution in both space and time, but such methods can be time-consuming to analyze and calibrate. Here, we design and train a regression neural network (NN) that accelerates and simplifies the extraction of local dynamics from SPM data directly in a cantilever-independent manner, allowing the network to process data taken with different cantilevers. We validate the NN’s ability to recover local dynamics with a fidelity equal to or surpassing conventional, more time-consuming, calibrations using both simulated and real microscopy data. We apply this method to extract accurate photoinduced carrier dynamics on n = 1 butylammonium lead iodide, a halide perovskite semiconductor film that is of interest for applications in both solar photovoltaics and quantum light sources. Lastly, we use SHapley Additive exPlanations to evaluate the robustness of the trained model, confirm its cantilever-independence, and explore which parts of the trEFM signal are important to the network.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multioutput Convolutional Neural Network for Improved Parameter Extraction in Time-Resolved Electrostatic Force Microscopy Data

Time-resolved scanning probe microscopy methods, like time-resolved electrostatic force microscopy (trEFM), enable imaging of dynamic processes ranging from ion motion in batteries to electronic dynamics in microstructured thin film semiconductors for solar cells. Reconstructing the underlying physical dynamics from these techniques can be challenging due to the interplay of cantilever physics with the actual transient kinetics of interest in the resulting signal. Previously, quantitative trEFM used empirical calibration of the cantilever or feed-forward neural networks trained on simulated data to extract the physical dynamics of interest. Both these approaches are limited by interpreting the underlying signal as a single exponential function, which serves as an approximation but does not adequately reflect many realistic systems. Here, we present a multi-branched, multi-output convolutional neural network (CNN) that uses the trEFM signal in addition to the physical cantilever parameters as input. The trained CNN accurately extracts parameters describing both single-exponential and bi-exponential underlying functions, and more accurately reconstructs real experimental data in the presence of noise. This article demonstrates an application of physics-informed machine learning to complex signal processing tasks, enabling more efficient and accurate analysis of trEFM.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Toward Sustainable Lithium Recovery: A Universal Hydrothermal Approach for Lithium Extraction

The rapid growth of lithium-ion battery (LIB) deployment presents critical challenges in sustainable end-of-life management and raw material recovery. Conventional pyrometallurgical and hydrometallurgical methods suffer from high energy demand, lithium loss, and complex wastewater treatment. This study established a universal, highly efficient, and sustainable hydrothermal route for lithium extraction and material recovery from various spent lithium-ion battery cathodes using 1,2,4,5-benzenetetracarboxylic acid (BTCA). The optimized process achieved over 99% lithium leaching efficiency for lithium iron phosphate (LFP) and LiNi x Mn y Co 1–x–y O 2 (NMC), with transition metal coleaching below 1%. It was also broadly applicable to lithium manganese oxide, lithium cobalt oxide, and black mass, achieving 98.5%, 98.95%, and 94.06% leaching efficiencies, respectively. The extracted lithium was directly converted into battery-grade lithium sources, while transition metals were recovered as oxides. Unreacted BTCA was efficiently regenerated and reused without degradation. Electrochemical evaluation confirmed that cathode materials synthesized with recovered lithium exhibit comparable performance to commercial products. Compared to conventional hydrometallurgy, the BTCA-based process increased revenue by over 40% and reduced greenhouse gas emissions by up to 39%. This closed-loop, chemistry-agnostic strategy offered a scalable and economically viable solution for industrial LIB recycling, enabling resource circularity and reducing dependency on primary critical materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Capacitive Deionization for the Extraction and Recovery of Butyrate

Separation processes underpin chemical manufacturing, energy and fuel production, resource recovery, and water purification. Capacitive deionization (CDI) is an electrochemical separation technique based on electrosorption of charged species from an aqueous solution. This work reports the development and application of CDI for the extraction and recovery of butyrate, a carboxylate anion that is key to bioenergy production, among other applications. Electrosorption of sodium butyrate was evaluated using a bench-scale CDI system with activated carbon cloth electrodes. Applying an external potential (1.2 V) enhanced the adsorption capacity of activated carbon for butyrate by 250%. Reversible electrosorption was also demonstrated by extracting and recovering butyrate at 1.2 and 0 V, respectively. Performance metrics including butyrate adsorption and desorption capacities, adsorption and desorption rates, charge efficiency, energy consumption, and recovery are reported. Furthermore, this study also investigates the long-term operational stability of the system by cycling the cell more than 1000 times using 1.2 and 0 V for charging and discharging, respectively. Subsequent physicochemical characterization indicates increased oxygen content (from similar to 2% to >8%), decreased specific surface area (by similar to 20%), and decreased pore volume (by similar to 20%), attributed to carbon oxidation. Overall, this work informs the design of CDI for organic anion separation and recovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Composition-Preserving Extraction and Characterization of Biomass Extrinsic and Intrinsic Inorganic Compounds

The inorganic content of biomass impairs size reduction tool life and the conversion process. Conventional ash extraction relies on furnace combustion that inevitably alters the inorganic compounds due to oxidation and decomposition. This study developed composition-preserving methods for extracting and analyzing extrinsic and intrinsic inorganic compounds. Comprehensive characterization was carried out on selected biomass feedstocks, including corn stover, pine residue, and pine anatomical fractions, to reveal their inorganic species and morphology. The extrinsic inorganic compounds were found to be dominated by quartz, along with other minor minerals, such as albite, microcline, and gehlenite, and have particle sizes ranging from tens to hundreds of micrometers. Among the pine anatomical fractions, the needles contain the highest intrinsic silicon content while the bark trapped the most extrinsic minerals. By correlation of the total ash and extrinsic inorganic contents to the wear behavior, both the extrinsic and intrinsic inorganic compounds were concluded to have made significant contributions to the wear process. Finally, the results here validated a new approach to characterize inorganic compounds in biomass and provided fundamental insights for their potential impact on preprocessing tool wear.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mitigating Injection‐Induced Seismicity Along Basement Faults by Extraction: Application to 2016–2018 Pohang Earthquakes

Abstract The risk of induced earthquake is considered as the major obstacle for sustainable subsurface energy activities. As a mitigation approach, mechanistic risk assessment can be essential to minimize the potential of seismic hazard. Coupled hydro‐mechanical modeling approach is integrated with geomechanical analysis to better assess the occurrence of seismicity induced by injection and/or extraction, which will provide a basis to update operational conditions (e.g., number and location of mitigating wells, rate and duration of operations) for mitigating earthquake nucleation. The Coulomb stability analysis and seismicity rate estimates from this generic study indicate that simultaneous extraction can relieve injection‐induced pore‐pressure buildup, but also transfer and accumulate elastic energy along the faults. Field‐scale simulation with variation in well design for the Pohang EGS site, South Korea, show that multiple wells aligned across a preexisting fault form gradients of pressure and stress fields normal to the fault, which can enhance the direct impact of diffusion process and poroelastic stressing on the fault stability perturbation. Our mechanistic study suggests multiphysics‐oriented mitigation strategies that consider (1) possible mechanical deformation, caused by hydro‐mechanical coupling effects, and (2) proper configuration of well operations based on site‐specific geological characteristics.

Chang, K. W.↗

Optical emissivity dataset of multi-material heterogeneous designs generated with automated figure extraction

Optical device design is typically an iterative optimization process based on a good initial guess from prior reports. Optical properties databases are useful in this process but difficult to compile because their parsing requires finding relevant papers and manually converting graphical emissivity curves to data tables. Here, we present two contributions: one is a dataset of thermal emissivity records with design-related parameters, and the other is a software tool for automated colored curve data extraction from scientific plots. We manually collected 64 papers with 176 figures reporting thermal emissivity and automatically retrieved 153 colored curve data records. The automated figure analysis software pipeline uses Faster R-CNN for axes and legend object detection, EasyOCR for axes numbering recognition, and k-means clustering for colored curve retrieval. Additionally, we manually extracted geometry, materials, and method information from the text to add necessary metadata to each emissivity curve. Finally, we analyzed the dataset to determine the dominant classes of emissivity curves and determine the underlying design parameters leading to a type of emissivity profile.

47 OTHER INSTRUMENTATION↗

Extracting band edge profiles at semiconductor heterostructures from hard-x-ray core-level photoelectron spectra

Hard-x-ray photoelectron spectroscopy (HAXPES) is a valuable source of information on band-edge profiles deep inside semiconductor thin films and heterojunctions. However, extracting this information requires robust and physically meaningful decomposition of spectra into contributions from individual atomic planes. We present an approach that utilizes the physical requirements of a monotonic dependence of the built-in electrostatic potential on depth and continuity of the potential function and its derivatives. These constraints enable efficient extraction of band-edge profiles and allow one to capture details of the electronic structure, including determination of the signs and magnitudes of the band bending as well as the valence band offsets. The utility of this approach to generate quantitative insight into the electronic structure of complex materials is illustrated for epitaxial SrTiO 3 on intrinsic Si(001).

97 MATHEMATICS AND COMPUTING↗

Influence of uranyl complexation on the reaction kinetics of the dodecane radical cation with used nuclear fuel extraction ligands (TBP, DEHBA, and DEHiBA)

Specialized extractant ligands – such as tri-butyl phosphate (TBP), N,N-di-(2-ethylhexyl)butyramide (DEHBA), and N,N-di-2-ethylhexylisobutryamide (DEHiBA) – have been developed for the recovery of uranium from used nuclear fuel by reprocessing solvent extraction technologies. These ligands must function in the presence of an intense multi-component radiation field, and thus it is critical that their radiolytic behaviour be thoroughly evaluated. This is especially true for their metal complexes, where there is negligible information on the influence of complexation on radiolytic reactivity, despite the prevalence of metal complexes in used nuclear fuel reprocessing solvent systems. Here we present a kinetic investigation into the effect of uranyl (UO 2 2+ ) complexation on the reaction kinetics of the dodecane radical cation (RH˙ + ) with TBP, DEHBA, and DEHiBA. Complexation had negligible effect on the reaction of RH˙ + with TBP, for which a second-order rate coefficient (k) of (1.3 ± 0.1) × 10 10 M -1 s -1 was measured. For DEHBA and DEHiBA, UO 2 2+ complexation afforded an increase in their respective rate coefficients: k(RH˙ + + [UO 2 (NO 3 ) 2 (DEHBA) 2 ]) = (2.5 ± 0.1) × 10 10 M -1 s -1 and k(RH˙ + + [UO 2 (NO 3 ) 2 (DEHiBA) 2 ]) = (1.6 ± 0.1) × 10 10 M -1 s -1 . This enhancement with complexation is indicative of an alternative RH˙ + reaction pathway, which is more readily accessible for [UO 2 (NO 3 ) 2 (DEHBA) 2 ] as it exhibited a much larger kinetic enhancement than [UO 2 (NO 3 ) 2 (DEHiBA) 2 ], 2.6× vs. 1.4×, respectively. Complementary quantum mechanical calculations suggests that the difference in reaction kinetic enhancement between TBP and DEHBA/DEHiBA is attributed to a combination of reaction pathway (electron/hole transfer vs. proton transfer) energetics and electron density distribution, wherein attendant nitrate counter anions effectively ‘shield’ TBP from RH˙ + electron transfer processes.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Insights into the extraction of photogenerated holes from CdSe/CdS nanorods for oxidative organic catalysis

Using aerobic oxidative coupling of thiophenol in organic media as a model reaction, we show that photogenerated holes in CdSe/CdS core–shell nanorods can be efficiently extracted. As a result, CdSe/CdS nanorods can serve as an efficient visible-light photocatalyst at a very low concentration (~1.5 × 10 -4 mol%). We show that primary amines play an important role in the transformation of thiols into disulfides by forming a soluble thiolate in nonpolar solvent. Using time-resolved optical spectroscopy and electron paramagnetic resonance spectroscopy, we show that thiolate can efficiently extract the photogenerated holes from CdSe/CdS nanorods and transform into disulfide in organic solvent. Overall, our data indicate that there are two reaction pathways responsible for S–S coupling of thiolate upon illumination of CdSe/CdS nanorods. We demonstrate that instead of scavenging of photogenerated holes by sacrificial species for prevention of photo corrosion of CdSe/CdS nanorods, the photogenerated holes can be efficiently used for oxidative organic synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗