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At least 1,531 records · Page 85

Highly Efficient Separation/Recycling Palladium(II) Ions from Aqueous Solutions by Silica Gel-Coated Graphene Oxide Modified with Mercapto Groups

The separation and recovery of precious metals from secondary resources is an extremely important and challenging task. Herein, a novel sorbent is successfully prepared by chemical grafting and utilized for the extraction and separation of Pd(II) ions from aqueous solutions. Various characterization techniques, including Fourier transform infrared spectroscopy, scanning electron microscopy, Brunauer–Emmett–Teller, X-ray photoelectron spectroscopy, and element analysis, are employed to study the structure, morphology, porous nature, and chemical composition of the as-prepared SiO{sub 2}@GO-SH nanocomposites. The adsorption of Pd(II) ions on the SiO{sub 2}@GO-SH can be described by the pseudo-second-order model and Langmuir isotherm model. The adsorption equilibrium has been attained within 90 min and the maximum adsorption capacity of 423.2 mg g{sup −1} was attained at pH 3.5 and T = 308 K. The results reveal that SiO{sub 2}@GO-SH exhibits an excellent adsorption performance towards Pd(II) ions. In addition, we have proposed the adsorption mechanism for Pd(II) ions on the SiO{sub 2}@GO-SH surface. The adsorption of Pd(II) in SiO{sub 2}@GO-SH is a chemisorption process, where partial adsorbed Pd(II) ions are reduced to Pd(0) by functional groups (-SH) in the SiO{sub 2}@GO-SH. The results indicate that SiO{sub 2}@GO-SH can serve as a promising sorbent for the efficient separation and recovery of palladium from the palladium-containing secondary resources.

36 MATERIALS SCIENCE↗

Hydrogen uptake in graphite matrix at high temperature

Tritium management is a critical challenge for the next generation of nuclear reactors, such as Fluoride Salt Cooled High Temperature Reactors (FHRs) and High Temperature Gas-cooled Reactors (HTGRs), due to the higher production rate (up to 10,000 times) than conventional Light Water Reactors (LWRs). Graphitic materials employed as moderator, reflector, and fuel pebbles offer a potential pathway for tritium recovery by serving as a sink for tritium. Prediction of uptake capacity under reactor relevant conditions remains a challenge due to a lack of low partial pressure data and significant inter-grade variability of graphite. This study addresses these gaps by providing a comprehensive characterization of hydrogen (as a tritium surrogate) uptake and release behavior in the A3-3 graphite matrix (GM) used in fuel pebbles. Uptake measurements are performed at reactor relevant temperatures of 600- 800 °C, 1-200 Torr hydrogen pressure, and 15-120 min equilibration time, followed by thermal desorption spectroscopy up to 1100 °C. Uptake experiments at different equilibration times demonstrate the role of kinetics in hydrogen uptake, which can be modeled as a diffusion-with-trapping process. In the thermodynamics limit, the Sips adsorption model is shown to capture the uptake in A3-3 GM well. Our campaign provides a set of new results for hydrogen uptake in A3-3, including limiting uptake capacity at 600 °C, apparent diffusion coefficient at 600 °C, and the first estimates of the FHR/HTGR relevant (600 °C, 20 Pa partial pressure) equilibrium uptake capacity and time to saturation. Desorption data highlights a new site for hydrogen uptake, not observed in nuclear graphite, which we attribute to the non-graphitized binder. Using the Kissinger method, we estimate activation energy for release from the desorption peaks, confirming the activation energy for release from the basal planes and providing the first estimate for the activation energy of release from the binder.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Pouch cells with 15% silicon calendar-aged for 4 years

Small amounts of high-capacity silicon-based materials are already used in the anode of commercial Li-ion batteries, helping increase their energy density. Despite their remarkable storage capability, silicon continu-ously reacts with the electrolyte, accelerating time-dependent cell performance fade. Nevertheless, very limited information is available on the specific consequences of this reactivity for the calendar aging of Li-ion cells. Here, we analyze aging effects on 450 mAh pouch cells containing 15 wt% of Si (and 73 wt% graphite) after storage at 21 °C for four years. We show that severe losses of Si capacity occurred due to particle isolation when cells were stored at high states of charge (SOC), but not when cells were fully discharged prior to storage. Impedance rise was also significantly higher when cells were kept at high SOCs and was mostly due to phenomena taking place at the cathode; the continuous electrolyte reduction at the anode did not lead to a major increase in bulk electrode resistance. A series of post-test characterization provided additional information on the effects of time and SOC on the calendar aging of Si-containing cells. In conclusion, our study highlights the many challenges posed by Si during calendar aging and can inform future studies in the field.

25 ENERGY STORAGE↗

In situ TEM annealing of neutron-irradiated Ti reveals a two-stage mechanism for elevated temperature radiation damage recovery

Understanding how irradiation-induced defects evolve at elevated temperatures is of critical importance to predicting materials' behavior under steady-state and accident scenarios. However, such mechanistic insight into microstructural evolution is limited by the nature of ex situ annealing and subsequent imaging. Here we show direct observation and quantification of defect recovery in neutron-irradiated Ti using in situ transmission electron microscopy (TEM) annealing experiments. In agreement with our prior work, and at temperatures below the irradiation temperature (T irr = 300 °C), dislocation loops are observed to glide. At elevated temperatures (>500 °C), dislocation lines become mobile and promote significant recovery of the microstructure. These mechanisms challenge the established electron irradiation-based model for radiation damage recovery, which originally suggests dissolution of static defect clusters, and demonstrates the importance of in situ characterization in understanding defect evolution in irradiated materials.

Hirst, Charles A. [Univ. of Michigan, Ann Arbor, M↗

Immunophenotypic characterization and therapeutics effects of human bone marrow- and umbilical cord-derived mesenchymal stromal cells in an experimental model of sepsis

Highlights: • Mesenchymal stromal cells (MSCs) may be a therapeutic option for sepsis. • Bone marrow (BM) vs. umbilical cord (UC) -MSCs induce different M1/M2 gene profiles. • In a CLP model of sepsis, only BM-MSCs improved survival and bacterial clearance. Sepsis is a complicated multi-system disorder characterized by a dysregulated host response to infection. Despite substantial progress in the understanding of mechanisms of sepsis, translation of these advances into clinically effective therapies remains challenging. Mesenchymal Stromal Cells (MSCs) possess immunomodulatory properties that have shown therapeutic promise in preclinical models of sepsis. The therapeutic effects of MSCs may vary depending on the source and type of these cells. In this comparative study, the gene expression pattern and surface markers of bone marrow-derived MSCs (BM-MSCs) and umbilical cord-derived MSCs (UC-MSCs) as well as their therapeutic effects in a clinically relevant mouse model of polymicrobial sepsis, cecal ligation and puncture (CLP), were investigated. The results showed remarkable differences in gene expression profile, surface markers and therapeutic potency in terms of enhancing survival and pro/anti-inflammatory responses between the two MSC types. BM-MSCs improved survival concomitant with an enhanced systemic bacterial clearance and improved inflammatory profile post CLP surgery. Despite some improvement in the inflammatory profile of the septic animals, treatment with UC-MSCs did not enhance survival or bacterial clearance. Overall, the beneficial therapeutic effects of BM-MSCs over UC-MSCs may likely be attributed to their pro-inflammatory function, and to some extent anti-inflammatory features, reflected in their gene expression pattern enhancing macrophage polarization to M1/M2 phenotypes resulting in a balanced pro- and anti-inflammatory response against polymicrobial sepsis.

60 APPLIED LIFE SCIENCES↗

Leveraging Large Language Models for Understanding Fundamental Principles of Catalysis

Heterogeneous catalysis presents a distinct challenge for artificial intelligence (AI). Data sets are often small and inconsistently reported, catalyst representations are not standardized, and extracting fundamental knowledge requires integrating performance data, spectroscopic characterizations, and mechanistic models across multiple scales. Language offers a unifying representation across these modalities, making catalysis well suited for leveraging large language models (LLMs). By standardizing how catalytic data is represented, LLMs make dispersed experimental results more accessible to downstream statistical modeling. In this perspective, we focus our discussion around three opportunities where LLMs can significantly contribute to catalysis: (1) text to properties; (2) text to structure; and (3) text to mechanistic models. The discussion is followed by a perspective section on LLM-readiness of data, aligning LLM outputs with scientific correctness, and bridging lab-scale discovery to industrial deployment. Across each area, the most productive applications couple dispersed chemical knowledge with physics-grounded validation to produce verifiable hypotheses and actionable representations.

Catalysts↗

van der Waals Epitaxy Growth of Bi 2 Se 3 on a Freestanding Monolayer Graphene Membrane: Implications for Layered Materials and Heterostructures

Research on two-dimensional and layered materials has expanded over the past 2 decades because of their unique properties and application potential. The key hurdles in realizing this potential are the challenges in controlling their atomic structure and their incompatibility with existing semiconductor nanofabrication techniques. Here we report on high-quality van der Waals epitaxial growth and characterization of a layered topological insulator on freestanding monolayer graphene transferred to different mechanical supports. This “templated” synthesis approach enables direct interrogation of the interfacial atomic structure of the as-grown materials and opens a route toward creating device structures with more traditional semiconductor nanofabrication techniques.

36 MATERIALS SCIENCE↗

X-ray Micro-Computed Tomography for Structural Analysis of All-Solid-State Battery at Pouch Cell Level

Characterizing the microstructure of all-solid-state batteries (ASSBs) during fabrication and operation is vital for their advancement, particularly as scaling to pouch cell levels introduces challenges in probing large-scale microstructural evolution. This work highlights the potential of synchrotron X-ray micro-computed tomography (sXCT) as a nondestructive, rapid (<30 min), and high-resolution technique for visualizing and quantifying key microstructural features, including overhang, porosity, contact loss, active surface area, and tortuosity, in all-solid-state pouch cells. The large field of view (up to millimeters) of sXCT enables detailed analysis at an industry-relevant scale, bridging the gap between laboratory research and commercial applications. Furthermore, integrating realistic sXCT-derived 3D models into multiphysics simulations could provide insights into chemo-mechanical degradation, particularly at the edges of the pouch cells, offering a pathway for designing robust, high-performance ASSBs. This perspective establishes sXCT as an indispensable tool for advancing both the understanding and the engineering of next-generation energy storage systems.

25 ENERGY STORAGE↗

Permafrost Carbon: Progress on Understanding Stocks and Fluxes Across Northern Terrestrial Ecosystems

Significant progress in permafrost carbon science made over the past decades include the identification of vast permafrost carbon stocks, the development of new pan-Arctic permafrost maps, an increase in terrestrial measurement sites for CO 2 and methane fluxes, and important factors affecting carbon cycling, including vegetation changes, periods of soil freezing and thawing, wildfire, and other disturbance events. Process-based modeling studies now include key elements of permafrost carbon cycling and advances in statistical modeling and inverse modeling enhance understanding of permafrost region C budgets. By combining existing data syntheses and model outputs, the permafrost region is likely a wetland methane source and small terrestrial ecosystem CO 2 sink with lower net CO 2 uptake toward higher latitudes, excluding wildfire emissions. For 2002–2014, the strongest CO2 sink was located in western Canada (median: -52 g C m -2 y -1 ) and smallest sinks in Alaska, Canadian tundra, and Siberian tundra (medians: -5 to -9 g C m -2 y -1 ). Eurasian regions had the largest median wetland methane fluxes (16–18 g CH4 m -2 y -1 ). Quantifying the regional scale carbon balance remains challenging because of high spatial and temporal variability and relatively low density of observations. More accurate permafrost region carbon fluxes require: (a) the development of better maps characterizing wetlands and dynamics of vegetation and disturbances, including abrupt permafrost thaw; (b) the establishment of new year-round CO 2 and methane flux sites in underrepresented areas; and (c) improved models that better represent important permafrost carbon cycle dynamics, including non-growing season emissions and disturbance effects.

54 ENVIRONMENTAL SCIENCES↗

Site-specific spectroscopic measurement of spin and charge in (LuFeO3)m/(LuFe2O4)1 multiferroic superlattices

Abstract Interface materials offer a means to achieve electrical control of ferrimagnetism at room temperature as was recently demonstrated in (LuFeO 3 ) m /(LuFe 2 O 4 ) 1 superlattices. A challenge to understanding the inner workings of these complex magnetoelectric multiferroics is the multitude of distinct Fe centres and their associated environments. This is because macroscopic techniques characterize average responses rather than the role of individual iron centres. Here, we combine optical absorption, magnetic circular dichroism and first-principles calculations to uncover the origin of high-temperature magnetism in these superlattices and the charge-ordering pattern in the m = 3 member. In a significant conceptual advance, interface spectra establish how Lu-layer distortion selectively enhances the Fe 2+ → Fe 3+ charge-transfer contribution in the spin-up channel, strengthens the exchange interactions and increases the Curie temperature. Comparison of predicted and measured spectra also identifies a non-polar charge ordering arrangement in the LuFe 2 O 4 layer. This site-specific spectroscopic approach opens the door to understanding engineered materials with multiple metal centres and strong entanglement.

36 MATERIALS SCIENCE↗

Physics-guided dual implicit neural representations for source separation

Significant challenges exist in efficient data analysis of most advanced experimental and observational techniques because the collected signals often include unwanted contributions, such as background and signal distortions, that can obscure the physically relevant information of interest. To address this, we have developed a self-supervised machine-learning approach for source separation using a dual implicit neural representation framework that jointly trains two neural networks: one for approximating distortions of the physical signal of interest and the other for learning the effective background contribution. Our method learns directly from the raw data by minimizing a reconstruction-based loss function without requiring labeled data or pre-defined dictionaries. We demonstrate the effectiveness of our framework by considering a challenging case study involving large-scale simulated, as well as experimental, momentum-energy-dependent inelastic neutron scattering data in a four-dimensional parameter space, characterized by heterogeneous background contributions and unknown distortions to the target signal. The method is found to successfully separate physically meaningful signals from a complex or structured background even when the signal characteristics vary across all four dimensions of the parameter space. An analytical approach that informs the choice of the regularization parameter is presented. Our method offers a versatile framework for addressing source separation problems across diverse domains, ranging from superimposed signals in astronomical measurements to structural features in biomedical image reconstructions.

47 OTHER INSTRUMENTATION↗

A reliable workflow for improving nanoscale X-ray fluorescence tomographic analysis on nanoparticle-treated HeLa cells

Abstract Scanning X-ray fluorescence (XRF) tomography provides powerful characterization capabilities in evaluating elemental distribution and differentiating their inter- and intra-cellular interactions in a three-dimensional (3D) space. Scanning XRF tomography encounters practical challenges from the sample itself, where the range of rotation angles is limited by geometric constraints, involving sample substrates or nearby features either blocking or converging into the field of view. This study aims to develop a reliable and efficient workflow that can (1) expand the experimental window for nanoscale tomographic analysis of local areas of interest within a laterally extended specimen, and (2) bridge 3D analysis at micrometer and nanoscales on the same specimen. We demonstrate the workflow using a specimen of HeLa cells exposed to iron oxide core and titanium dioxide shell (Fe3O4/TiO2) nanocomposites. The workflow utilizes iterative and multiscale XRF data collection with intermediate sample processing by focused ion beam (FIB) sample preparation between measurements at different length scales. Initial assessment combined with precise sample manipulation via FIB allows direct removal of sample regions that are obstacles to both incident X-ray beam and outgoing XRF signals, which considerably improves the subsequent nanoscale tomography analysis. This multiscale analysis workflow has advanced bio-nanotechnology studies by providing deep insights into the interaction between nanocomposites and single cells at a subcellular level as well as statistical assessments from measuring a population of cells.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Learning from metastable symmetric-tilt grain boundaries using physics-based descriptors

Grain boundaries (GBs) govern critical properties of polycrystalline materials. Although significant advancements have been made in characterizing minimum energy and ordered GBs, real GBs are seldom found in such well-defined states. This diversity of atomic arrangements in metastable states makes it challenging to establish structure-property relationships with physical insights. Here, to address this challenge, we use data-driven methods to explore these relationships and examine the underlying physics. In this study, we utilize a large atomistic database (~5000) of minimum energy and metastable states of symmetric-tilt copper GBs, combined with physically motivated local atomic environment (LAE) descriptors [strain functional descriptors (SFDs)], to predict GB properties and gain physical insights. Our regression models exhibit robust predictive capabilities using only 19 descriptors, generalizing to atomic environments in nanocrystals. A significant highlight of our work is the integration of an unsupervised method with SFDs to elucidate LAEs at GBs and their role in determining properties. The model, trained on these minimum energy and metastable GBs using SFDs, predicts the properties of unseen nanocrystals with good accuracy. Our research underscores the role of a physics-based representation of LAEs and the efficacy of data-driven methods in establishing GB structure-property relationships.

36 MATERIALS SCIENCE↗

A Survey of Thermal Sensing Application in Additive Manufacturing

Industry 4.0 represents a significant change in manufacturing with the inclusion of such technologies as additive manufacturing and data analytics. In support of these changes, infrared thermal imaging (IR) and very-near infrared (VNIR) have proven invaluable in numerous applications related to additive manufacturing. In this review, these applications will be presented as they relate to polymer and metal-based additive manufacturing processes. Applications including in-situ characterization, post-build analysis, experimental setups, modeling, and machine learning will be covered. With a general overview complete, the review will conclude with a discussion of challenges identified throughout the literature and thoughts on future trends.

Borish, Michael↗

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects

Researchers at New Mexico Tech, Los Alamos National Laboratory (LANL), Sandia National Laboratory (SNL), and other collaborators are developing a methodology to improve characterization of stress in the subsurface by means of a model-based inversion of reservoir engineering data, time lapse seismic measurements, and microseismicity. Historically, various geophysical techniques have been used in efforts to understand the state of stress in the subsurface through direct and indirect imaging of stress sensitive features (faults and fractures) and observations of transient stress related observations (time variant elastic moduli and microseismicity). Standard direct and indirect techniques for seismic fault and fracture imaging suffer from detectability limits due to reliance on high data quality and multiplicity. Variations in effective elastic properties from inversion of high quality seismic (Vertical Seismic Profile (VSP)) data may be used to infer stress near the wellbore through integration with independent experimental characterization of the stress-velocity relationship. Given a sufficiently robust observation network, microseismic emissions may be inverted to characterize focal mechanisms which, together with supporting assumptions and constraints, inform estimates of in-situ stress. While each of these techniques contributes in part to the characterization of stress within limited spatial and temporal domains, no one method provides an unambiguous stress measurement or a predictive capability over a site scale spatial extent. Challenges associated with solution non-uniqueness, measurement ambiguity, and irregular sampling may be greatly minimized through combination of one or more of independent measurements within a common framework in which realistic geological, hydrodynamic, geomechanical, and seismological constituent process models may act as constraints.

02 PETROLEUM↗

Fundamental Investigations of Mechanical and Chemical Degradation Mechanisms in Lithium Ion Battery Materials (Final Technical Report)

The objective of our effort under the DOE EPSCoR Implementation grant is to establish a comprehensive and internationally recognized research program at Brown University and University of Rhode Island in understanding degradation mechanisms and to improve the cycle and calendar life of lithium ion battery (LIB) materials. A series of basic investigations are undertaken to characterize the mechanical and chemical degradation mechanisms, which can help enable new higher capacity and longer lasting electrode designs. Controlling mechanical and chemical degradation is the primary challenge in developing the next generation of higher energy density batteries. The development of failure resistant battery microstructures will require a fundamental understanding of the evolution of stress, deformation, damage, and electrochemistry in battery materials during cyclic charging and discharging. In addition, controlling the reactions at the electrode/electrolyte interface is critical for the formation of a stable SEI layer. We address these issues through a combination of controlled experiments on model battery materials and practical composite electrodes, together with multi-scale computations. Our effort is organized into three focus areas that encompass many critical challenges in Lithium Ion Battery Technologies: (i) Mechanical properties, fracture and damage in electrode materials; (ii) Chemistry and Mechanics of Solid Electrolyte Interphase (SEI); (iii) Mechanical and Chemical Integrity of Solid-Solid Interfaces in Practical Electrodes.

25 ENERGY STORAGE↗

Evaluating Optical Techniques to Characterize Solid State Samples for the Pu-238 Supply Program

This report documents steps that have been taken to establish advanced characterization capabilities for solid-state samples to support the 238 Pu Supply Program. The program has already invested significantly in spectroscopy and online monitoring development for liquid processes. Many of the data, analytical methods, and equipment could also be leveraged for the analysis of Np/Pu oxides and Np pellets to help classify material properties and link them to operations. The techniques described in this work include diffuse reflectance spectroscopy (DRS), Raman spectroscopy, and laser-induced breakdown spectroscopy (LIBS). Each technique is sensitive to various chemical and/or elemental species and can provide complimentary information to more standard methods such as powder x-ray diffraction and scanning electron microscopy. These options are remotely deployable via fiber-optic cables. DRS and Raman spectroscopy are already approved for glove box and hot cell work, but LIBS requires US Department of Energy approval for incorporation. Raman spectroscopy does require laser shielding, which means that DRS is the easiest method to implement. However, each technique provides complimentary data, and the most robust sample characterization could be achieved when all three, among other methods, are harnessed together. This report documents some of the progress made testing these capabilities, some of the challenges, and next steps to optimize the technology and integration strategies.

07 ISOTOPE AND RADIATION SOURCES↗

Data for EMSL Project 60929 from August 2023: PI Goemann MONet Request

Just as humans rely on a healthy gut microbiome for resilience to illness, plants rely on a healthy root microbiome for resilience to environmental abiotic stress (heat, drought). To achieve a healthy root microbiome, plants release carbon (C)-rich compounds as root exudates to stimulate microbial activity and increase local nutrient mineralization. However, the enhanced performance comes at a cost: up to 44% of a plant’s C can be lost to root exudates, diverting C from plant growth and respiration. Critical knowledge gaps include how the ‘C cost’ is managed and how root exudates alter the microbiome under different environmental conditions. In addition, historical climate conditions, particularly mean annual precipitation, is known to shape local soil microbiomes and alter their sensitivity to drought. Therefore, studies that better characterize the plant-microbe responses to environmental stress will aid in efforts to harness the microbiome to improve crop resilience. However, current knowledge gaps make it challenging to engineer beneficial plant-microbe interactions to improve plant productivity in agricultural systems and to predict how increased climate variability will alter terrestrial C fluxes and climate feedbacks. To fill this knowledge gap our research group at Montana State University – Bozeman is currently studying blue grama (Bouteloua gracilis), a prairie grass native across the Northern Great Plains, as a model for drought tolerance. Our goal is to investigate the above- and belowground responses of blue grama to drought and heat stress to improve our understanding of stress-induced carbon allocation and plant-microbe interactions. Most recently, we investigated the influence of climate history on the blue grama drought response. We collected soil from three blue grama-dominated sites (those proposed to sample here) across a 150 mm mean annual precipitation gradient in SW Montana, USA, to use as inoculum for a greenhouse drought experiment. Preliminary results indicate that soil climate history has a strong influence on the blue grama physiological response to drought as well as on the chemical composition of root exudates and rhizosphere microbiome composition. Metabarcoding data from this experiment is scheduled to be submitted to public databases within the next year. Having in-depth analyses of the soil biogeochemistry and metagenomic composition through the MONet project at each of the field sites associated with this experiment will allow us to link underlying ecological processes with observed patterns of plant growth and productivity at each site. In addition, we plan to utilize the MONet database for future meta-analyses to compare the genomic and biogeochemical signatures of our field sites to others across a wider precipitation gradient throughout the native range of blue grama. This will further provide critical insights into the mechanisms that drive ecosystem functioning and resilience to drought stress.

Peyton, Brent↗