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114 records · Page 7

H 2 O-assisted O 2 reduction by H 2 on Pt and PtAu bimetallic nanoparticles: Influences of composition and reactant coverages on kinetic regimes, rates, and selectivities

Hydrogen peroxide (H 2 O 2 ) can replace hazardous oxidants in industrial processes but is currently too expensive for many such applications. While direct synthesis of H 2 O 2 (H 2 + O 2 → H 2 O 2 ) may reduce costs in comparison to incumbent technology, current catalysts lack the requisite stability and selectivity. Here, we examine the direct synthesis of H 2 O 2 on bimetallic Pt 1 Au x (0 ≤ x ≤ 230) and Pt catalysts at steady-state in pure water and relate kinetic parameters for H 2 O 2 and H 2 O formation to possible active site structures informed by complementary characterization methods. X-ray photoelectron spectra show significant Pt surface enrichment compared to the bulk composition. Analysis of infrared spectra of mixed monolayers of 12 CO* and 13 CO* indicate that Pt and Au form substitutional surface alloys. The Pt 1 Au x nanoparticles with the greatest mole fractions of Au predominantly expose Pt monomers (i.e., isolated Pt atoms), yet Pt atoms exposed upon all these nanoparticles possess electronic structures distinct from bulk Pt. Despite these differences, rate measurements are consistent with product formation through proton-electron transfer pathways for all Pt 1 Au x catalysts. In situ XAS indicate that Pt remains metallic during H 2 O 2 synthesis. Under the most oxidizing conditions, selectivities toward H 2 O 2 increase strongly with the Au to Pt ratio from 2% for monometallic Pt to 85% for Pt 1 Au 170 . However, selectivities are similar among all catalysts within reducing conditions. Comparisons of apparent activation enthalpies for the formation of H 2 O 2 and H 2 O across these catalysts and the range of conditions suggest that Pt monomers within Au provide the greatest selectivities for H 2 O 2 formation, because these active sites present high barriers for O-O bond rupture. Further, selectivities decrease with increasing ratios of H 2 to O 2 pressures, because Pt atoms aggregate and form oligomers that readily dissociate dioxygen intermediates. The combined use of spectroscopy, kinetics, and concepts employed in reaching these conclusions take inspiration from the legacy of Prof. Michel Boudart, and specifically his elegant methods for interrogating bimetallic catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mesoscale fractal whey protein particles derived from microscale linear-shaped protein assemblies (Part 1): Manufacturing method and particle characteristics

Whey protein isolates (WPI) are widely used in processed foods for their versatile functional properties. Modifying the structural properties of proteins by assembling them into mesoscale or microscale particles may improve their functionality and broaden their applications. This study aims to manufacture and characterize mesoscale whey protein particles (WPP) derived from WPI. Two types of WPP, WPP1 (0.05 mL/min) and WPP2 (0.25 mL/min), were prepared through a multistep approach involving liquid antisolvent (LAS) precipitation, heat treatment, and microfluidization. Liquid antisolvent precipitation was performed by injecting a 20% (wt/vol) WPI dispersion (pH 7) into an ethanol-glycerol mixture (75:25, vol/vol) under laminar flow, followed by heat treatment at 80°C for 20 min as a particle hardening step. This process produced stable fiber- and ribbon-shaped whey protein assemblies (WPA), which served as precursors to WPP. Subsequent microfluidization (150 MPa, 6 passages) reduced the size of WPA, yielding mesoscale WPP with irregular morphologies and a more uniform size distribution, as revealed by microscopy and dynamic light scattering. ζ-Potential and fluorescence labeling indicated higher surface charge and surface hydrophobicity of WPP compared with untreated WPI. The WPP showed internal mass fractal and surface fractal structures at larger length scales, analyzed using small-angle X-ray scattering. Fourier transform infrared spectroscopy demonstrated an increased fraction of intermolecular β-sheets in WPP, suggesting that hydrogen bonding contributed to their formation. Gel electrophoresis confirmed that disulfide bonds served as the primary cross-links stabilizing the WPP structure. Furthermore, turbidity measurements showed that WPP exhibited superior colloidal phase stability compared with untreated WPI and maintained high colloidal stability under both acidic and neutral pH conditions.

Antisolvent precipitation↗

A Step-Down Test Procedure for Wavelet Shrinkage Using Bootstrapping

Wavelet thresholding (or shrinkage) attempts to remove the noises existing in the signals while preserving inherent pattern characteristics in the reconstruction of true signals. For data-denoising purpose, we present a new wavelet thresholding procedure which employs the step-down testing idea of identifying active contrasts in unreplicated fractional factorial experiments. The proposed method employs bootstrapping methods to a step-down test for thresholding wavelet coefficients. By introducing the concept of a false discovery error rate in testing wavelet coefficients, we shrink the wavelet coefficients with p -values higher than the error rate. The error rate controls the expected proportion of wrongly accepted coefficients among chosen wavelet coefficients. Bootstrap samples are used to approximate the p -value for computational efficiency. We also present some guidelines for selecting the values of hyper-parameters which affect the performance in the step-down thresholding procedure. Based on some common testing signals and an air-conditioner sounds example, the comparison of our proposed procedure with other thresholding methods in the literature is performed. The analytical results show that the proposed procedure has a potential in data-denoising and data-reduction in a variety of signal reconstruction applications.

42 ENGINEERING↗

Coal-based Bricks & Blocks (CBBs): Process Development to Prototype Fabrication Coupled with Techno-Economic Analysis and Market Survey

The decline of coal use for energy production provides an abundance of local feedstock for new innovative uses and value-added products. Expanding the U.S. coal-value chain to manufacture high-value carbon products can strengthen the nation’s energy and mineral security, enhance the U.S. national defense security, increase the United States’ economic prosperity, while achieving U.S. environmental objectives. The primary project goal is a relatively light-weight composite product with superior (or comparable) compressive strength. Both virgin and, where available, post-consumer recycled thermoplastic versions are tested for each thermoplastic species. A useful attribute of thermoplastics as binders is that they can be heated to their melting point, cooled, and reheated again without significant degradation. A key advantage of thermoset CBBs is that they require only mixing and molding. CBB advantages include low cost, availability, binding ability and processability. Coal-based bricks and blocks (CBBs) weigh about 50% less than clay bricks and can be manufactured with an interlocking design to promote ease of use for the novice builder. CBB formulation is evaluated according to a design-of-experiments (DoE) approach. DoE variables are a) relative weight fractions of binder, b) relative proportions of large versus small (milled) anthracite size fractions, and c) additive percentage. Fabrication methods include hot-press molding and extrusion, the later being the most commercially viable. CBBs are tested for compressive strength, modulus of rupture (by flexure test) and water absorption per ASTM C67, with density determined by the Archimedes drainage method. Fractured interfaces are examined by SEM (Scanning Electron Microscopy) to resolve fracture dynamics and interior microstructure uniformity. Differential scanning calorimetry (DSC) is used to compare plastic transition temperatures i.e., glass and melting temperatures to contrast virgin with post-consumer recycled thermoplastics and optimize their usage. These results are used in the DoE analysis to identify the binder and relative weight percentages for optimum strength, density, and porosity. Overall, CBBs possess strength comparable to clay-based bricks but are non-permeable and hydrophobic, and hence resistant to degradation by freeze-fracturing, corrosion, and efflorescence. The strongest composites have been made with the following thermoplastic binders (in order of strength): thermoset, high-density polyethylene crosslink resin, high-density polyethylene, nylon 6/6, and polypropylene. Results from a techno-economic analysis TEA show economy of scale for CBBs by modularization and reveal the binder as the cost driver for material costs. Ideally, the incorporation of post-consumer recycled thermoplastic will decrease material acquisition costs and increase product sustainability. Notably, CBBs do not require the high temperature calcination needed to produce cement, nor do they require firing in the 1600-2400 °F range for three days using natural gas, as do clay brick equivalents. Instead, CBBs are heated to a modest <600 °F according to the melt flow index of the thermoplastic binder. Existing anthracite mines can be expanded to produce CBBs to reduce aggregate transportation costs and emissions that exist for clay bricks. TEA reflects this reduced energy cost while a comparative CO2 emission analysis quantifies the reduced environmental footprint. The market survey identifies several commercialization opportunities, dependent upon the brick classification.

01 COAL, LIGNITE, AND PEAT↗

Data, model inputs, and analysis scripts associated with a manuscript on stream intermittency controls across spatial scales in Pacific Northwest watersheds

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript "Hydroclimatic Memory and Watershed Template Shape Stream Intermittency: Multi-scale Attribution Using Process-based Simulation and Explainable ML" by Niroula et al. (2026), submitted to Water Resources Research (WRR). The study investigates the dominant controls on stream intermittency across local, reach, and watershed scales using a coupled process-based simulation and explainable machine-learning framework. Long-term daily simulations from the Advanced Terrestrial Simulator (ATS) were used to generate wetness states and ponded-depth responses over river-corridor cells. These ATS outputs were then aggregated across scales and used to train XGBoost (eXtreme Gradient Boosting) models. SHAP (SHapley Additive exPlanations) was applied to quantify the relative importance of hydroclimatic forcings, watershed template attributes, and antecedent-memory effects in shaping intermittency behavior. The analysis is carried out for three contrasting Pacific Northwest watersheds: Oak Creek (OCW), American River Watershed (ARW), and H.J. Andrews (HJA). Across these testbeds, the package contains ATS-ready watershed inputs, ATS run configuration and selected output files, model-evaluation data products, intermittency-analysis datasets, machine-learning target-feature tables, SHAP outputs, and notebooks used to organize, analyze, and visualize results. At a high level, the package documents a workflow in which ATS provides the physically based simulation backbone and explainable machine learning is used as a post-processing attribution tool. The contents are intended to support interpretation of the manuscript figures and results, provide context for how intermittency metrics were generated at multiple scales, and preserve the key artifacts needed to understand and reuse the analysis workflow. The package contains a high-level directory summary file (`summary.txt`) and four main content folders (1) `evaluation_plots` contains evaluation figures and supporting evaluation datasets; (2) `intermittency_plots` contains intermittency-focused analysis notebook and prepared datasets; (3) `ml-training-and-shap_values_plots` contains ML training inputs, SHAP outputs, and figure-generation notebooks; and (4) `watershed_mesh_and_ats_input` contains ATS model setup materials, forcing inputs, geometry, and selected run files. More specifically, the `evaluation_plots` folder contains the notebook used for ATS evaluation plotting and site-specific evaluation datasets. These include evapotranspiration and water-balance products for three watersheds, as well as an Oak Creek field-measurement discharge file. The `intermittency_plots` folder contains the notebook used for intermittency analysis and the prepared datasets used to analyze intermittent and non-intermittent wetness behavior across the study watersheds. The `ml-training-and-shap_values_plots` folder contains notebooks and outputs for the machine-learning and explainability workflow. This includes the main XGBoost and SHAP notebook(s), a beeswarm plotting notebook, target-feature tables for machine-learning training, SHAP summary tables, and per-sample SHAP value archives. The `watershed_mesh_and_ats_input` folder contains ATS-related watershed inputs and supporting materials. This includes mesh and shape products, ATS-readable LAI and meteorological forcing inputs, selected ATS spinup and transient-run files, and a watershed workflow example notebook. Subdirectories are organized by watershed where applicable.All files are .cpg (codepage files), .csv (comma-separated values), .dbf (database files), .exo (Exodus mesh format), .h5 (HDF5 format), .ipynb (Jupyter notebooks), .pkl (Python pickle), .prj (projection files), .sh (shell scripts), .shp (shapefile geometry), .shx (shapefile index), .txt (text files), or .xml (markup data).

Advanced Terrestrial Simulator↗