Results for “Sample selection” — Page 19

DOE OSTI2026

Excipient screening by lyophilization provides insights into spray drying formulations for nanoparticle vaccines

Nanoparticles have shown great promise as delivery platforms in the development of tunable and safe vaccines. Nanolipoprotein particles (NLPs), also known as nanodiscs, are discoidal nanoparticles composed of a lipid bilayer stabilized at their periphery by apolipoproteins. Under the right conditions, the NLP self-assembly process is highly customizable in terms of lipids and apolipoprotein constituents, allowing for tunable physical and chemical characteristics. This flexibility allows a wide range of vaccine antigens and adjuvants to be incorporated onto the NLP platform for tailored vaccine design. The stability of NLPs during long term storage is a very important factor in developing a vaccine delivery platform suitable for widespread global use. When stored in a solution for extended periods of time, NLPs dissociate into their corresponding lipids and protein constituents, leading to particle degradation. Proper stabilization of NLPs can often be achieved by lyophilization (i.e. freeze-drying), a method widely used for various applications including pharmaceuticals. This process, however, can be damaging to particles without the presence of lyoprotectants or excipients that help maintain particle stability during lyophilization. Another method used to stabilize vaccines and pharmaceuticals is spray drying, a process that converts liquid formulations into dry powders through controlled heating and airflow. While spray drying is rapid, scalable, and cost-effective, lyophilization is typically a gentler process that better retains biomolecule structure and function. Both processes use excipients for particle stabilization, so lyophilization can be used as a surrogate to test stability of NLPs, to down-select formulations that may withstand the harsher conditions of spray drying. To screen different formulations, NLPs were synthesized and purified to homogeneity by size exclusion chromatography (SEC) and samples were prepared with a wide range of lyoprotectants and/or excipients. To assess the protective effects of excipients on NLPs upon spray drying, both pre- and post-lyophilized samples were analyzed by SEC. To assess the protective effects upon heating (encountered during the spray drying process), NLP samples were incubated at elevated temperatures prior to SEC analysis. The lyoprotectants and excipients evaluated in this study had different efficiencies in protecting NLPs during lyophilization and heating tests. Trehalose, for example, exhibits stabilization on NLPs both upon lyophilization and heating whereas leucine accelerated NLP dissociation. Although some lyoprotectants are effective by themselves, different combinations can decrease the stabilization of NLPs. Shelf-stable vaccines that do not require cold-chain storage are essential for global accessibility and our findings provide fundamental insight into how to advance NLP-based vaccines for these applications.

Serrano, Litzay J [Lawrence Livermore National Lab↗

DOE OSTI2024

Learning of networked spreading models from noisy and incomplete data

Recent years have seen a lot of progress in algorithms for learning parameters of spreading dynamics from both full and partial data. Some of the remaining challenges include model selection under the scenarios of unknown network structure, noisy data, missing observations in time, as well as an efficient incorporation of prior information to minimize the number of samples required for an accurate learning. Here, in this work, we introduce a universal learning method based on a scalable dynamic message-passing technique that addresses these challenges often encountered in real data. The algorithm leverages available prior knowledge on the model and on the data, and reconstructs both network structure and parameters of a spreading model. We show that a linear computational complexity of the method with the key model parameters makes the algorithm scalable to large network instances.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Selective Deposition and Fusion of AISI 316L: An Additive Manufacturing Process for Space Environments via Direct Ink Writing and Laser Processing

Unlocking the potential of additive manufacturing (AM) for space exploration hinges on overcoming key challenges, notably the ability to manufacture or repair parts on-site during exploration missions with consideration of quality, feedstock utilization, and challenges involved in microgravity environments. While there are multiple efforts to investigate the use of existing metal AM processes such as powder bed fusion (PBF), directed energy deposition (DED), and filament-based material extrusion, each process comes with a different set of challenges in space environments. Here, in this work, we introduce a new AM method that integrates the benefits of direct ink writing (DIW) to selectively deposit metallic pastes with laser-based processing to locally debind and subsequently melt and fuse metal powder, layer by layer, enabling the manufacturing of AISI 316L samples with densities exceeding 99.0%. The impact of process parameters on single-track dimensions, surface morphology, and porosity was characterized. The efficacy of laser debinding was assessed via secondary-ion mass spectrometry, permitting the carbon content to be estimated at 0.0152%, which is safely below the acceptable limit (0.03 wt%) for AISI 316L.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Forward variable selection enables fast and accurate dynamic system identification with Karhunen-Loève decomposed Gaussian processes

A promising approach for scalable Gaussian processes (GPs) is the Karhunen-Loève (KL) decomposition, in which the GP kernel is represented by a set of basis functions which are the eigenfunctions of the kernel operator. Such decomposed kernels have the potential to be very fast, and do not depend on the selection of a reduced set of inducing points. However KL decompositions lead to high dimensionality, and variable selection thus becomes paramount. This paper reports a new method of forward variable selection, enabled by the ordered nature of the basis functions in the KL expansion of the Bayesian Smoothing Spline ANOVA kernel (BSS-ANOVA), coupled with fast Gibbs sampling in a fully Bayesian approach. It quickly and effectively limits the number of terms, yielding a method with competitive accuracies, training and inference times for tabular datasets of low feature set dimensionality. Theoretical computational complexities are O ( N P 2 ) in training and O ( P ) per point in inference, where N is the number of instances and P the number of expansion terms. The inference speed and accuracy makes the method especially useful for dynamic systems identification, by modeling the dynamics in the tangent space as a static problem, then integrating the learned dynamics using a high-order scheme. The methods are demonstrated on two dynamic datasets: a ‘Susceptible, Infected, Recovered’ (SIR) toy problem, along with the experimental ‘Cascaded Tanks’ benchmark dataset. Comparisons on the static prediction of time derivatives are made with a random forest (RF), a residual neural network (ResNet), and the Orthogonal Additive Kernel (OAK) inducing points scalable GP, while for the timeseries prediction comparisons are made with LSTM and GRU recurrent neural networks (RNNs) along with the SINDy package.

Hayes, Kyle↗

DOE OSTI2024

Comparative analysis of nutrient concentrations in generalist and specialist tree species and soils, Manaus, Brazil

This dataset was collected near Manaus, Brazil, at ZF-2 site, inside the North-South transect plots from 20221011 to 20221020. Measurements were made on specialists and generalist tree species along topographic gradient (in upland high-clay content soils of plateaus and high sandy content and partially flooded soils of valleys). We selected nine species (with four replicates each, totaling 35 individuals) occurring in different topographic positions: three plateau specialists, three valley specialists, and three generalists, where leaf and trunk samples were collected from each individual, and soil samples for carbon and nutrient analysis and quantification. Three soil pits were opened around each sample tree, about one meter apart (total of 105 soil pits each 60-cm deep), where soil samples were collected at four depths: 0-5, 5-10, 10-30 and 30-50 cm. In each of the three pits around each tree, one single sample was taken at each depth and combined to obtain a composite sample per depth per individual tree (35 trees × 4 depths = 140 soil samples). The files “Plant_Nutrient_Concentrations_NS_Transect_Manaus.csv” and “Soil_Nutrient_Concentrations_NS_Transect_Manaus.csv” contain the nutrient concentration data from plant and soil material, respectively. Additionally, the file “Sample_Info.csv” contains details about each variable including units and data type. The file “Species_Info.csv” includes information about each sampled individual, such as species, family, diameter at the breast height (DBH), and more. The dataset is ready to be used in any programming language like python or R. This dataset was originally published on the NGEE Tropics Archive and is being mirrored on ESS-DIVE for long-term archival Acknowledgement: Funding for NGEE-Tropics data resources was provided by the U.S. Department of Energy Office of Science, Office of Biological and Environmental Research.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Additively Manufactured Molten Salt to Supercritical Carbon Dioxide Heat Exchanger

Design, fabrication, and experimental characterization of the performance of a molten salt (MS)-to-supercritical carbon dioxide (sCO 2 ) heat exchanger (HE) for concentrating solar power (CSP) applications using laser powder bed fusion (LPBF) additive manufacturing (AM) of nickel-based superalloys is presented in this report. The hypothesis is that such additively manufactured HEs will result in a monolithic, compact, low-pressure drop HE that is durable under cyclic operation at high temperature and high pressure in a corrosive salt environment. Two nickel-based superalloys were considered in the project- Haynes 230 (H230) and Haynes 282 (H282). Process windows for LPBF AM were established to provide dense low porosity parts for both alloys. Creep tests results on heat treated AM H230 and H282 samples showed that the AM fabricated specimens were as robust as the wrought specimens and showed no deficit in creep strength at high temperatures. Haynes 282 was down selected for the HE fabrication based on better dimensional tolerance, better corrosion resistance to chloride salt, and higher creep strength.

14 SOLAR ENERGY↗

DOE OSTI2024

National User Resource for Biological Accelerator Mass Spectrometry

The National User Resource for Biological Accelerator Mass Spectrometry (User Resource) will provide isotopic analysis (primarily radiocarbon or 14C) by accelerator mass spectrometry (AMS) for NIH- funded researchers across the United States and will be the only User Resource of its type in the United States. The User Resource will provide measurement capability and expertise to a research community that requires highly sensitive, quantitative isotope analyses. Since commissioning a new accelerator mass spectrometer in June 2014, we have measured over 4000 samples a year for collaborators and service users. The User Resource will enable us to continue to meet these research needs, as well as provide for new users whose research programs would benefit from AMS as a measurement tool. The User Resource’s forte will be ultra-high sensitivity quantitation of radiocarbon and selected other radioisotopes for research studies where isotopes are required. Radioisotope labeling studies have been and will continue to be an important tool for addressing many complex biomedical science problems. AMS is a specialized and unique type of mass spectrometry that provides absolute quantitation of radiocarbon and other relevant radioisotopes with extreme sensitivity, having limits of detection in real samples on the order of a few attomol/mg of sample at measurement precisions of ~3%. It is the only instrumental method capable of quantifying radioisotope-labeled agents routinely in real-world samples with such precision and sensitivity. The sensitivity of AMS allows for the quantification of radiolabeled metabolites in extremely complex matrices of cells and organisms at very low concentrations and in small samples. AMS allows studies to be conducted without perturbing metabolism leading to more relevant quantification of metabolic rates and pathways. In addition, it enables quantification of pharmacokinetic and metabolic properties of toxicants at environmentally relevant concentrations in model systems as well as the ability to quantify pharmacokinetics and other molecular endpoints directly in humans. Such quantitative assessments can 1) improve risk assessment for toxicants, 2) address safety and efficacy considerations for therapeutic entities, 3) deepen understanding of xenobiotic and intermediary metabolism, 4) help understand the interactions between critical molecular pathways, and 5) improve efforts to model and predict various metabolic and biological states. These capabilities have been applied in a number of areas including research in carcinogenesis, toxicology, nutrition, pharmacology/drug development and basic biological science. As a NIGMS National Resource the National User Resource for Biological Accelerator Mass Spectrometry will help NIH funded scientists achieve a deeper understanding of the etiology of human health concerns by (1) enabling the quantification of pharmacokinetics and other molecular endpoints directly in humans; (2) offering the ability to conduct quantitative studies using biologics such as proteins or lipids, and thereby reducing the amount of radioisotope usage in biomedical labs; and (3) enabling more relevant studies of metabolic pathways in health and disease through the use of much lower, more biologically-relevant, concentrations of metabolic substrates in cells and intact organisms. Such studies support NIGMS’s basic biomedical research areas that contribute to the understanding of fundamental cellular and physiological principles and enable research supported by the Biophysics, Biomedical Technology, and Computational Biosciences (BBCB); Genetics and Molecular, Cellular, and Developmental Biology (GMCDB); Pharmacology, Physiology, Biological Chemistry (PPBC) and Training, Workforce Development, and Diversity (TWD) Divisions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

National User Resource for Biological Accelerator Mass Spectrometry (Final Report)

The National User Resource for Biological Accelerator Mass Spectrometry (User Resource) will provide isotopic analysis (primarily radiocarbon or 14C) by accelerator mass spectrometry (AMS) for NIH- funded researchers across the United States and will be the only User Resource of its type in the United States. The User Resource will provide measurement capability and expertise to a research community that requires highly sensitive, quantitative isotope analyses. Since commissioning a new accelerator mass spectrometer in June 2014, we have measured over 4000 samples a year for collaborators and service users. The User Resource will enable us to continue to meet these research needs, as well as provide for new users whose research programs would benefit from AMS as a measurement tool. The User Resource’s forte will be ultra-high sensitivity quantitation of radiocarbon and selected other radioisotopes for research studies where isotopes are required. Radioisotope labeling studies have been and will continue to be an important tool for addressing many complex biomedical science problems. AMS is a specialized and unique type of mass spectrometry that provides absolute quantitation of radiocarbon and other relevant radioisotopes with extreme sensitivity, having limits of detection in real samples on the order of a few attomol/mg of sample at measurement precisions of ~3%. It is the only instrumental method capable of quantifying radioisotope-labeled agents routinely in real-world samples with such precision and sensitivity. The sensitivity of AMS allows for the quantification of radiolabeled metabolites in extremely complex matrices of cells and organisms at very low concentrations and in small samples. AMS allows studies to be conducted without perturbing metabolism leading to more relevant quantification of metabolic rates and pathways. In addition, it enables quantification of pharmacokinetic and metabolic properties of toxicants at environmentally relevant concentrations in model systems as well as the ability to quantify pharmacokinetics and other molecular endpoints directly in humans. Such quantitative assessments can 1) improve risk assessment for toxicants, 2) address safety and efficacy considerations for therapeutic entities, 3) deepen understanding of xenobiotic and intermediary metabolism, 4) help understand the interactions between critical molecular pathways, and 5) improve efforts to model and predict various metabolic and biological states. These capabilities have been applied in a number of areas including research in carcinogenesis, toxicology, nutrition, pharmacology/drug development and basic biological science. As a NIGMS National Resource the National User Resource for Biological Accelerator Mass Spectrometry will help NIH funded scientists achieve a deeper understanding of the etiology of human health concerns by (1) enabling the quantification of pharmacokinetics and other molecular endpoints directly in humans; (2) offering the ability to conduct quantitative studies using biologics such as proteins or lipids, and thereby reducing the amount of radioisotope usage in biomedical labs; and (3) enabling more relevant studies of metabolic pathways in health and disease through the use of much lower, more biologically-relevant, concentrations of metabolic substrates in cells and intact organisms. Such studies support NIGMS’s basic biomedical research areas that contribute to the understanding of fundamental cellular and physiological principles and enable research supported by the Biophysics, Biomedical Technology, and Computational Biosciences (BBCB); Genetics and Molecular, Cellular, and Developmental Biology (GMCDB); Pharmacology, Physiology, Biological Chemistry (PPBC) and Training, Workforce Development, and Diversity (TWD) Divisions. Over the next five years, our goals are to: 1. Improve the efficiency of operation for AMS measurements through installation of new interfaces to our AMS systems, technical modifications to improve gas accepting ion source efficiency and upgrading our data analysis software for improved ease of use and data reporting. 2. Increase the accessibility and visibility of ultra-sensitive 14C measurements for the biomedical research community by training of new investigators and expanding our national user base. 3. Provide high throughput, ultra-sensitive 14C analysis for the NIGMS and NIH user community.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Evaluation of a Reference-Free Collision Cross Section Calibration Strategy for Proteomics Using SLIM-Based High-Resolution Ion Mobility Spectrometry–Mass Spectrometry

Ion mobility spectrometry (IMS) is a gas-phase analytical technique that separates ions with different sizes and shapes and is compatible with mass spectrometry (MS) to provide an additional separation dimension. The rapid nature of the IMS separation combined with the high sensitivity of MS-based detection and the ability to derive structural information on analytes in the form of the property collision cross section (CCS) makes IMS particularly well-suited for characterizing complex samples in -omics applications. In such applications, the quality of CCS from IMS measurements is critical to confident annotation of the detected components in the complex -omics samples. However, most IMS instrumentation in mainstream use requires calibration to calculate CCS from measured arrival times, with the most notable exception being drift tube IMS measurements using multifield methods. The strategy for calibrating CCS values, particularly selection of appropriate calibrants, has important implications for CCS accuracy, reproducibility, and transferability between laboratories. The conventional approach to CCS calibration involves explicitly defining calibrants ahead of data acquisition and crucially relies upon availability of reference CCS values. In this work, we present a novel reference-free approach to CCS calibration which leverages trends among putatively identified features and computational CCS prediction to conduct calibrations post-data acquisition and without relying on explicitly defined calibrants. We demonstrated the utility of this reference-free CCS calibration strategy for proteomics application using high-resolution structures for lossless ion manipulations (SLIM)-based IMS-MS. In conclusion, we first validated the accuracy of CCS values using a set of synthetic peptides and then demonstrated using a complex peptide sample from cell lysate.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Molecular-Resolution Electron Imaging of Defects and Dynamics at the Ice-Water Interface

Water crystallization into hexagonal ice (type I h ) is one of the most critical processes relevant to the Earth’s environment and human activities. However, despite recent breakthroughs in imaging non-equilibrium condensed ice structures, the ice-water interface has never been imaged at a molecular resolution. This is primarily due to the low stability of the hydrogen bonds in ice under high-resolution microscopy conditions and a lack of methods to prepare compatible samples. Here, this presentation describes the first molecular-resolution imaging of ice crystallized from liquid water and the ice-water interface using high-resolution transmission electron microscopy (HRTEM). By encapsulating deionized (DI) water between two amorphous carbon (a-C) TEM grids and subsequently freezing it with liquid N 2 on a cryo sample stage, we generated two types of ice: non-equilibrium, condensed ice from the atmosphere and encapsulated ice from the DI water (Fig. 1A). Condensed ice usually shows irregular, spherulitic shapes (Fig. 1B). Selected area electron diffraction (SAED) shows that they are a mixture of cubic and hexagonal crystals (Fig. 1C). On the contrary, encapsulated ice forms thin films that contain large-area single-crystalline regions of hexagonal ice oriented along the [0001] zone axis (Fig. 1D). Differential electron energy-loss spectroscopy (EELS) confirmed the high purity of the encapsulated ice free from organic contaminations that are common in other encapsulation methods for HRTEM such as graphene liquid cells. These single-crystalline areas are robust under the electron beam up to ~100 e/Å 2 s. Aberration-corrected HRTEM imaging in these areas achieved a line resolution of ~1.3 Å (Fig. 1E and F). This platform allows us to study near-equilibrium ice structures and dynamics at an unprecedented spatial resolution (Fig. 2). For example, we discovered subdomain-rich regions near the defective crystal edges despite the structure appearing single-crystalline according to diffraction criteria. These subdomains connect via low-angle grain boundaries with flat energy landscapes as a function of tilt angles (according to simulations), showing the high tolerance of ice to defect structures. When we tuned the sample temperature and electron flux rate, we observed radiolysis-controlled bubble generation and dissolution in ice single crystals near a steady state of bubble dynamics. Furthermore, rich beam-induced melting and recrystallization dynamics were observed at the ice-water interface with lattice resolution. These data represent the first observation of the ice-water phase transformation at the sub-nanometer level. In summary, the methods developed in this work enabled molecular-resolution observations of ice and the ice-water interface and shed light on the microstructures and phase transformation pathways. Finer control on the temperature, electron irradiation profile, and imaging detector could eventually lead to real-time observation of ice nucleation in water and address long-standing questions in the nucleation pathways.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2026

Linking DSC/TGA to Cell Levels: Energetics, Evolved Gases, and Thermal Safety of NMC811‐Graphite Micro‐Cell

Thermochemical characterization of battery materials links intrinsic material properties to decomposition pathways, heat generation, and gas evolution that govern performance and safety. Despite extensive work on NMC811-Graphite, variability across partial configurations and the limited adoption of micro-cell architectures (cathode+anode+electrolyte+separator) hinder robust cell-scale interpretation. Accordingly, this work establishes a bottom-up, component-resolved methodology integrating DSC/TGA, evolved gas analysis (EGA), and in situ XRD to link decomposition pathways and energy release across partial and micro-cell configurations, providing a transferable assessment of safety and stability in emerging chemistries. In separator-free configurations, the gas–solid reaction between cathode-evolved O 2 and anode-leached Li dominates the net heat release (1139 J g −1 ). In contrast, in the micro-cell configuration, the separator hinders O 2 transport and alters the timing and pathways of other reactions, and reduces the net energy release to 618 J g −1 . Energy release was organized into defined temperature windows that provide a framework for a thermodynamic model combining quantified gas evolution with selected decomposition pathways and effective reaction enthalpies to estimate net specific energy release, with agreement between DSC and cell-level tests. Ex situ XPS of heat-treated samples extends post-mortem analysis to thermal-abuse regimes, supporting key pathway elements.

25 ENERGY STORAGE↗

DOE OSTI2024

Intercalation-Induced Topotactic Phase Transformation of Tungsten Disulfide Crystals

Recent research has demonstrated the potential for topological superconductivity, anisotropic Majorana bound states, optical nonlinearity, and enhanced electrochemical activity for transition metal dichalcogenides (TMDs) with a 2M structure. These unique TMD compounds exhibit metastability and, upon heating, undergo a transition to the thermodynamically stable 2H phase. The 2M phase is commonly made at high temperatures using traditional solid-state methods, and this metastability further complicates the growth of large 2M WS 2 crystals. Herein, a novel synthetic method was developed, focusing on a molten salt reaction to synthesize large 2H crystals and then inducing transformation to the 2M phase through intercalation and thermal treatment. The 2H crystals were intercalated via a room-temperature sodium naphthalenide solution, producing a previously unreported Na-intercalated 2H WS 2 phase. Thermal heating was required to facilitate the phase transition to the intercalated 2M crystal structure. This phase transition was studied by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), selected area electron diffraction (SAED), electron dispersive X-ray spectroscopy (EDS), and Raman spectroscopy, which confirmed the synthesis of the intercalated 2M phase. Upon deintercalation, crystal and powder samples showed superconductivity with a T c of 8.6–8.7 K, similar to previously reported values. The generality of this process was further demonstrated using alkali metal triethyl borohydride to intercalate 2H WS 2 and produced the desired 2M phase. This novel synthetic method has broad implications for discovering metastable phases in other TMD families and layered materials. Furthermore, separation of the intercalation and phase transition also has the potential to allow for large-scale synthesis of this technologically important phase with greater control over each step of the reaction.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Exploration of structure-activity relationships for the SARS-CoV-2 macrodomain from shape-based fragment linking and active learning

The macrodomain of severe acute respiratory syndrome coronavirus 2 nonstructural protein 3 is required for viral pathogenesis and is an emerging antiviral target. We previously performed an x-ray crystallography–based fragment screen and found submicromolar inhibitors by fragment linking. However, these compounds had poor membrane permeability and liabilities that complicated optimization. Here, we developed a shape-based virtual screening pipeline—FrankenROCS. We screened the Enamine high-throughput collection of 2.1 million compounds, selecting 39 compounds for testing, with the most potent binding with a 130 μM median inhibitory concentration (IC 50 ). We then paired FrankenROCS with an active learning algorithm (Thompson sampling) to efficiently search the Enamine REAL database of 22 billion molecules, testing 32 compounds with the most potent binding with a 220 μM IC 50 . Further optimization led to analogs with IC 50 values better than 10 μM. This lead series has improved membrane permeability and is poised for optimization. FrankenROCS is a scalable method for fragment linking to exploit synthesis-on-demand libraries.

Science & Technology - Other Topics↗

DOE OSTI2025

Microscopic Measurement: Need for Nuclear Material Sample Specimen Characterization Capability

The Surveillance, Fabrication, and Off-Site Operations team at Lawrence Livermore National Laboratory is beginning an update to the nuclear material machining lab in Superblock. Plutonium and other nuclear materials tend to accelerate the aging process for equipment and machines that would otherwise be maintainable for long lives. They have their lifespans shortened from deteriorated seals, embrittled polymer components, accelerated corrosion, and damage to electronics from exposure to radioactive materials. The cost of installation of equipment into a glove box (GB) tends to outstrip the cost of the equipment itself. Due to the magnification of cost, the historical approach to equipment installs has been to purchase and install the highest-quality and most robust equipment available to maximize time between failures and updates. To make room for the installation of a new lathe, the inspection GB is being moved to a different location within the machining lab. As part of the overall effort, the equipment within the inspection GB is being revisited. Current measurement capabilities are antiquated and starting to become problematic due to age. Advances in metrology are sought for more comprehensive characterization of scientific samples. This document aims to identify several options for the replacement of current measurement equipment and identify a system for purchase and eventual installation. The intention is not to select the cheapest system, but rather to identify a system that best meets the needs of both the operators and principal investigators (PI). Following the convention of the SYSM-5620 Design Thinking and System Engineering, it was determined that a laser confocal measurement system from Keyence is the most suitable option for our programmatic need. Form factor, capability, and maintainability were considered. Along with stakeholder input, to ensure the best decision for the Nuclear Material Technology Program.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Comparison of venous and pooled capillary hemoglobin levels for the detection of anemia among adolescent girls

Introduction: Blood source is a known preanalytical factor affecting hemoglobin (Hb) concentrations, and there is evidence that capillary and venous blood may yield disparate Hb levels and anemia prevalence. However, data from adolescents are scarce. Objective: To compare Hb and anemia prevalence measured by venous and individual pooled capillary blood among a sample of girls aged 10–19 years from 232 schools in four regions of Ghana in 2022. Methods: Among girls who had venous blood draws, a random subsample was selected for capillary blood. Hb was measured using HemoCue® Hb-301. We used Lin’s concordance correlation coefficient (CCC) to quantify the strength of the bivariate relationship between venous and capillary Hb and a paired t-test for difference in means. We used McNemar’s test for discordance in anemia cases by blood source and weighted Kappa to quantify agreement by anemia severity. A multivariate generalized estimating equation was used to quantify adjusted population anemia prevalence and assess the association between blood source and predicted anemia risk. Results: We found strong concordance between Hb measures (CCC = 0.86). The difference between mean venous Hb (12.8 g/dL, ± 1.1) and capillary Hb (12.9 g/dL, ± 1.2) was not significant (p = 0.26). Crude anemia prevalence by venous and capillary blood was 20.6% and 19.5%, respectively. Adjusted population anemia prevalence was 23.5% for venous blood and 22.5% for capillary ( = 0.45). Blood source was not associated with predicted anemia risk (risk ratio: 0.99, 95% CI: 0.96, 1.02). Discordance in anemia cases by blood source was not significant (McNemar p = 0.46). Weighted Kappa demonstrated moderate agreement by severity (k =0.67). Among those with anemia by either blood source (n = 111), 59% were identified by both sources. Conclusion: In Ghanaian adolescent girls, there was no difference in mean Hb, anemia prevalence, or predicted anemia risk by blood source. However, only 59% of girls with anemia by either blood source were identified as having anemia by both sources. These findings suggest that pooled capillary blood may be useful for estimating Hb and anemia at the population level, but that caution is needed when interpreting individual-level data.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Prediction of Silicon Content in a Blast Furnace via Machine Learning: A Comprehensive Processing and Modeling Pipeline

Silicon content plays an important role in determining the operational efficiency of blast furnaces (BFs) and their downstream processes in integrated steelmaking; however, existing sampling methods and first-principles models are somewhat limited in their capability and flexibility. Current data-based prediction models primarily rely on a limited set of manually selected furnace parameters. Additionally, different BFs present a diverse set of operating parameters and state variables that are known to directly influence the hot metal’s silicon content, such as fuel injection, blast temperature, and raw material charge composition, among other process variables that have their own impacts. The expansiveness of the parameter set adds complexity to parameter selection and processing. This highlights the need for a comprehensive methodology to integrate and select from all relevant parameters for accurate silicon content prediction. Providing accurate silicon content predictions would enable operators to adjust furnace conditions dynamically, improving safety and reducing economic risk. To address these issues, a two-stage approach is proposed. First, a generalized data processing scheme is proposed to accommodate diverse furnace parameters. Second, a robust modeling pipeline is used to establish a machine learning (ML) model capable of predicting hot metal silicon content with reasonable accuracy. The method employed herein predicted the average Si content of the upcoming furnace cast with an accuracy of 91% among 200 target predictions for a specific furnace provisioned by the XGBoost model. This prediction is achieved using only the past shift’s operating conditions, which should be available in real time. This performance provides a strong baseline for the modeling approach with potential for further improvement through provision of real-time features.

Chemistry↗

DOE OSTI2026

Probing cosmic velocities with the pairwise kinematic Sunyaev-Zel’dovich signal in DESI Bright Galaxy Sample DR1 and ACT DR6

We present a measurement of the pairwise kinematic Sunyaev-Zel’dovich (kSZ) signal using the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Sample (BGS) Data Release 1 (DR1) galaxy sample overlapping with the Atacama Cosmology Telescope (ACT) CMB temperature map. Our analysis makes use of 1.6 million galaxies with stellar masses log⁡ 𝑀 ⋆ /𝑀 ⊙ >10, and we explore measurements across a range of aperture sizes (2.1′ <𝜃 ap <3.5′) and stellar mass selections. This statistic directly probes the velocity field of the large-scale structure, a unique observable of cosmic dynamics and modified gravity. In particular, at low redshifts, this quantity is especially interesting, as deviations from General Relativity are expected to be largest. Notably, our result represents the highest-significance low-redshift (𝑧 ∼ 0.3) detection of the kSZ pairwise effect yet. In our most optimal configuration (𝜃 ap =3.3′, log⁡ 𝑀 ⋆ >11), we achieve a 5⁢𝜎 detection. Assuming that an estimate of the optical depth and galaxy bias of the sample exists via e.g., external observables, this measurement constrains the fundamental cosmological combination 𝐻 0 ⁡𝑓⁡𝜎$^2_8$. A key challenge is the degeneracy with the galaxy optical depth. We address this by combining CMB lensing, which allows us to infer the halo mass and galaxy population properties, with hydrodynamical simulation estimates of the mean optical depth, $\bar{𝜏}$ . We stress that this is a proof-of-concept analysis; with BGS DR2 data we expect to improve the statistical precision by roughly a factor of two, paving the way toward robust tests of modified gravity with kSZ-informed velocity-field measurements at low redshift.

Hadzhiyska, Boryana [Institute of Astronomy; Kavli↗

DOE OSTI2026

Light-Driven Iodine Loss and Photoluminescence Homogenization in Mixed-Halide Perovskite Semiconductors

Carrier-induced instabilities in lead halide perovskites are often investigated as either transient phenomena, e.g., photoinduced halide segregation or permanent performance changes, e.g., photodegradation, while the mechanistic links between them remain unclear. Here, we aim to connect these observations by studying a model mixed-halide system, MAPb(Br x I 1–x ) 3 . By combining grazing-incidence X-ray diffraction, photothermal deflection spectroscopy, and photoluminescence measurements with hyperspectral microscopy, we investigate the role of mobile halide defects and local chemistry on reversible and long-term instabilities in these materials. Our results show that mixed-halide perovskites are uniquely susceptible to photoinduced changes with illumination driving initial iodide redistribution (i.e., halide segregation), eventual selective iodine expulsion, and subsequent changes in photoinduced halide segregation behavior. By quantifying structural and compositional changes, we estimate an approximately 3–5% iodine loss in our mixed-halide samples after only 24 h of illumination. Further, using microscale measurements, we identify pre-existing iodide-rich domains as key contributors to both the observed transient photostability and permanent iodine loss in MAPbBrI 2 , and see evidence that extended light soaking results in iodide redistribution that improves optoelectronic homogeneity. Overall, our results emphasize the importance of carrier-induced halide oxidation in creating a dynamic defect landscape in mixed-halide perovskites and provide a framework for interpreting apparent light-driven changes in optoelectronic behavior through the lens of permanent compositional changes.

electrical conductivity↗