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At least 1,441 records · Page 80

Pt Nanoparticle Disintegration at Oxide Interfaces Enhances CO Oxidation Catalysis

Understanding how supported metal nanoparticles dynamically evolve under reaction conditions is critical for controlling their catalytic function. Here, the mechanism behind the dynamic disintegration of Pt nanoparticles (NPs) supported on CeOx-TiO2 (CT) during CO oxidation is elucidated, leading to the formation of single atoms (SAs) and/or sub-nanometer clusters. Density functional theory (DFT) calculations reveal that strong Pt-CO interactions weaken Pt─Pt cohesion, while electronic coupling between Pt and Ce ions stabilizes Pt-CO* intermediates at the oxide interface. Surface oxygen vacancies kinetically trap Pt-CO*, but the vacancies are replenished under oxygen-rich conditions, enabling Pt-CO* surface diffusion and subsequent structural reorganization. In situ spectroscopic analyses confirm the oxygen-driven transformation of Pt NPs, correlating with a threefold increase in mass-specific activity at 150 °C. These findings demonstrate that interfacial oxygen dynamics and metal-support interactions can be leveraged to induce nanoparticle disintegration and optimize catalytic performance, highlighting the catalytic potential of interface-engineered Pt nanostructures.

CO oxidation↗

Post‐Annealing Treatment on Hydrothermally Grown Antimony Sulfoselenide Thin Films for Efficient Solar Cells

Herein, antimony sulfoselenide (Sb 2 (S, Se) 3 ) thin‐film solar cells are fabricated by a hydrothermal method followed by a post‐deposition annealing process at different temperatures and the impact of the annealing temperature on the morphological, structural, optoelectronic, and defect properties of the hydrothermally grown Sb 2 (S, Se) 3 films is investigated. It is found that a proper annealing temperature leads to high‐quality Sb 2 (S, Se) 3 films with large crystal grains, high crystallinity, preferred crystal orientation, smooth and uniform morphology, and reduced defect density. These results show that suppressing deep‐level defects is crucial to enhance solar cell performance. After optimizing the annealing process, Sb 2 (S, Se) 3 solar cells with an improved power conversion efficiency 2.04 to 8.48% are obtained.

14 SOLAR ENERGY↗

Design space exploration and decision‐making for a segmented ultralight morphing 50‐MW wind turbine

Abstract Wind turbine design encompasses many different aspects including aerodynamic, structural, electrical, and control system design. To achieve optimal plant performance, a system design approach is utilized in which the performance of the whole wind turbine is evaluated and quantified during operational scenarios with subsystem interactions. In this paper, the design for a Segmented Ultralight Morphing Rotor (SUMR) 50‐MW wind turbine is presented utilizing levelized cost of energy (LCOE) for design choices, with additional quantification of simulated performance shortcomings at the 50‐MW scale. The multi‐disciplinary design process results in a final ultra‐scale turbine configuration that outperforms other existing offshore wind farms regarding the LCOE.

Kianbakht, Sepideh↗

The FMO-DFTB Method

Although the fragment molecular orbital (FMO) method enables electronic structure calculations with near-linear scaling behavior with respect to system size, the computational cost of ab initio methods typically employed in conjunction with FMO is still prohibitive for routine calculations of very large systems or long timescale molecular dynamics simulations. We, therefore, combined the FMO and density-functional tight-binding (DFTB) method, which is one of the emerging semi-empirical quantum chemical methods, and have demonstrated that FMO-DFTB is capable of performing geometry optimizations for systems containing up to one million atoms using limited computational resources. In this chapter, we will review the basics of the DFTB method first before introducing FMO-DFTB, focusing on the relationship with density functional theory and other FMO methodologies. We also demonstrate the latest scalings of FMO-DFTB2 and DFTB3 using three-dimensional water clusters, showing that the most favorable scaling is O(N1.16). Applications of FMO-DFTB to various systems are briefly summarized, and an outlook to future applications is provided.

Nishimoto, Yoshio↗

Possible role of interference, protein noise, and sink effects in nonphotochemical quenching in photosynthetic complexes

Here, we analyze theoretically a simple and consistent quantum mechanical model that reveals the possible role of quantum interference, protein noise, and sink effects in the nonphotochemical quenching (NPQ) in light-harvesting complexes (LHCs). The model consists of a network of five interconnected sites (excitonic states of light-sensitive molecules) responsible for the NPQ mechanism. The model also includes the “damaging” and the dissipative channels. The damaging channel is responsible for production of singlet oxygen and other destructive outcomes. In this model, both damaging and “dissipative” charge transfer channels are described by discrete electron energy levels attached to their sinks, that mimic the continuum part of electron energy spectrum. All five excitonic sites interact with the protein environment that is modeled using a stochastic process. Our approach allowed us to derive the exact and closed system of linear ordinary differential equations for the reduced density matrix and its first momentums. Moreover, these equations are solved numerically including for strong interactions between the light-sensitive molecules and protein environment. As an example, we apply our model to demonstrate possible contributions of quantum interference, protein noise, and sink effects in the NPQ mechanism in the CP29 minor LHC. The numerical simulations show that using proper combination of quantum interference effects, properties of noise, and sinks, one can significantly suppress the damaging channel. Finally, our findings demonstrate the possible role of interference, protein noise, and sink effects for modeling, engineering, and optimizing the performance of the NPQ processes in both natural and artificial light-harvesting complexes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Adaptive wavelet compression of large additive manufacturing experimental and simulation datasets

New manufacturing technologies such as additive manufacturing require research and development to minimize the uncertainties in the produced parts. The research involves experimental measurements and large simulations, which result in huge quantities of data to store and analyze. We address this challenge by alleviating the data storage requirements using lossy data compression. We select wavelet bases as the mathematical tool for compression. Unlike images, additive manufacturing data is often represented on irregular geometries and unstructured meshes. Thus, we use Alpert tree-wavelets as bases for our data compression method. We first analyze different basis functions for the wavelets and find the one that results in maximal compression and miminal error in the reconstructed data. We then devise a new adaptive thresholding method that is data-agnostic and allows a priori estimation of the reconstruction error. Finally, we propose metrics to quantify the global and local errors in the reconstructed data. One of the error metrics addresses the preservation of physical constraints in reconstructed data fields, such as divergence-free stress field in structural simulations. While our compression and decompression method is general, we apply it to both experimental and computational data obtained from measurements and thermal/structural modeling of the sintering of a hollow cylinder from metal powders using a Laser Engineered Net Shape process. The results show that monomials achieve optimal compression performance when used as wavelet bases. The new thresholding method results in compression ratios that are two to seven times larger than the ones obtained with commonly used thresholds. Overall, adaptive Alpert tree-wavelets can achieve compression ratios between one and three orders of magnitude depending on the features in the data that are required to preserve. Furthermore, these results show that Alpert tree-wavelet compression is a viable and promising technique to reduce the size of large data structures found in both experiments and simulations.

42 ENGINEERING↗

The Effect of Membrane Structure Prepared from Carboxymethyl Cellulose and Cellulose Nanofibrils for Cationic Dye Removal

Water-stable and eco-friendly membranes were fabricated from carboxymethyl cellulose (CMC) acting as anionic adsorbent and cellulose nanofibrils (CNFs) as strengthening filler by solvent- and unidirectional freeze-casting processes, both supported with simultaneous citric acid (CA) mediated cross-linking. Spectroscopic, thermogravimetric and potentiometric titration techniques were applied to evaluate the efficacy of the cross-linking as well as to quantify the processing-dependant surface charge. In addition, the CMC/CNF assembling and membrane porosity were identified microscopically as the combinatorial effect of components ratio and the applied fabrication technique. Finally, the membrane’s cationic dyes adsorption capacity and kinetic were evaluated depending on the dyes ionization constants, solution pH, and the contact time using batch equilibrium experiment, and further evaluated for filtration performance at optimal pH. The resulting, freeze-casted membranes demonstrate anisotropic to isotropic and highly (> 90%) porous structures with gradient pore sizes (from few nm up to 200 µm range). This provides relatively high and stable flux rates (150–190 kL/m{sup 2} h MPa) with ~ 100% cationic dye adsorption, fast dynamic (8.536–5.446 kg/g min) and capacity (1828–1398 g/kg), which highlight their potential in dead-end filtration technologies without need for additional separation step. The similar dye adsorption capacity was assessed for denser and nano-porous (< 50 nm) solvent-casted membranes, however, with much lower and time-declining flux rates (100–10 L/m{sup 2} h MPa), demonstrating their potential usage in spiral wound-cross-flow modules. Both types of membranes anyhow showed high dye removal capacity (≥ 90%) even after 4th (solvent-casted) and 50th (freeze-casted) reusing cycle, present a high-value alternative to commercial activated carbons or other bio-nano-absorbents.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Enhanced sensitivity of hemoglobin sensor using dual-core photonic crystal fiber

A Hemoglobin (Hb) biosensor based on dual-core photonic crystal fiber is proposed and analyzed. In this paper, the effective refractive index dependency on the Hb concentration within a blood sample is utilized in obtaining the transmission spectrum variation. The results are calculated using full vectorial finite element method. Through this study, the effect of the structure geometrical parameters on the sensor performance is optimized to maximize the sensor sensitivity. The numerical results show a sensitivity of 8.013 nm/g/dL for the X-polarized mode at 3.7 cm fiber length and 7.68 nm/g/dL for the Y-polarized mode at 3.2 cm fiber length of the proposed sensor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

High-Cycle Fatigue Behavior of Vacuum-Carburized 20Cr2Ni4 Steel with Different Case Depths

High-cycle fatigue behavior of vacuum-carburized 20Cr2Ni4 steel with three different case depths was studied by using rotating bending fatigue test. The results show that fatigue strength exhibits an increase–decrease pattern with increasing effective case dept, which is regarded to be mainly due to the unavoidable change in other parameters such as residual stress and grain size in case layer besides case depth. The present data and data in the available literature suggest that a dimensionless parameter of relative case depth is more appropriate to reflect the influence of case depth on fatigue strength. Further fracture surface analysis revealed that the fatigue failure was dominated by surface crack initiation mainly due to the extremely high cleanness of the tested steel with inclusion control. It is thus concluded that both relative case depth and other parameters should be comprehensively considered in obtaining optimized fatigue performance of vacuum-carburized steel.

36 MATERIALS SCIENCE↗

Effectiveness of nature-based solutions to reduce flooding in Quad Cities Metro Area (QCMA) using SWMM-HEC based flood model

Nature-based solutions (NbS) have gained significant attention as strategies for addressing urban environmental challenges, particularly since the establishment of the UN Sustainable Development Goals (SDGs) for 2030. However, the current research on NbS for urban flood management lacks comprehensive methodological approaches for identifying suitable areas and evaluating their effectiveness across different urban settings. Here, this study attempts to fill this gap by proposing a methodological framework integrating multi-criteria analysis with a SWMM-HEC-based hydrologic and hydraulic (HH) model to assess the suitability of NbS for the Quad Cities Metro Area (QCMA), consisting of Davenport, Bettendorf, Moline, and Rock Island. Eight NbS options-green roofs, rain gardens, infiltration trenches, permeable pavements, vegetative swales, dry detention basins, retention ponds, and rain barrels/cisterns - were considered based on volumetric efficiency and runoff reduction efficiency. The study reveals that implementing the proposed NbS could have substantially reduced flood depths in key historical flood events by 21% in 1993, 15% in 2008, 16% in 2011, 23% in 2014, 40% in 2019, and 10% in 2023. The findings highlight a critical trade-off between peak runoff and NbS implementation: while NbS effectively reduce flood impacts, they also enhance volumetric efficiency by approximately 43%. In high-density areas of the QCMA, flood depth reductions of around 20% suggest that NbS are a viable solution for dense urban environments with limited space. This shows the potential for integrating NbS into existing infrastructure, offering a promising approach for cities facing increasing flooding risks. The proposed methodology provides a practical framework for incorporating NbS into urban stormwater management, addressing gaps in optimizing NbS performance, and offering a pathway to scale their application in other urban areas with various environmental and social contexts.

CMIP6↗

Metal Amorphous Nanocomposite (MANC) Alloy Cores with Spatially Tuned Permeability for Advanced Power Magnetics Applications

Metal amorphous nanocomposite (MANC) alloys are an emerging class of soft magnetic materials showing promise for a range of inductive components targeted for higher power density and higher efficiency power conversion applications including inductors, transformers, and rotating electrical machinery. Magnetization reversal mechanisms within these alloys are typically determined by composition optimization as well as controlled annealing treatments to generate a nanocomposite structure composed of nanocrystals embedded in an amorphous precursor. Here in this paper we demonstrate the concept of spatially varying the permeability within a given component for optimization of performance by using the strain annealing process. The concept is realized experimentally through the smoothing of the flux profile from the inner to outer core radius achieved by a monotonic variation in tension during the strain annealing process. Great potential exists for an extension of this concept to a wide range of other power magnetic components and more complex spatially varying permeability profiles through advances in strain annealing techniques and controls.

36 MATERIALS SCIENCE↗

Computational Design of Alloys for Energy Technologies

Advanced materials that maintain their mechanical performance under elevated temperatures, corrosive environments, and a range of static and evolving stresses are needed to improve the efficiency and reduce the environmental impact of a wide spectrum of energy technologies. For instance, cost-efficient alloys that can withstand high temperatures (e.g., 700 °C) have a critical role in improving the efficiency and economics of power generation to support decarbonization of the energy sector; such is true of both the nuclear and fossil energy sectors. Considering both the threats of the energy crisis, namely soaring costs of greenhouse gas emission-producing energy and climate change, it is essential to increase the pace of material discovery and enable rapid paths for material qualification to advance clean energy technologies. Conventionally, alloy development has followed a slow Edisonian process that uses repeated cycles of making, characterizing, and modifying to arrive at optimum composition and processing conditions to achieve the desired component performance. This optimization is followed by the necessary stepwise materials qualification. Furthermore, the increasing adoption of sound data management and physics-informed machine learning represents the next step in the acceleration of materials design and development. In the integrated computational materials engineering (ICME) approach, computational modeling and simulation data from different length and time scales can be combined with complex microstructural details from multimodal experimental characterization and selective property testing to close the design loop for rapid alloy development.

Computational Design Of Materials↗

Substrate-Coated Illumination Droplet Spray Ionization: Real-Time Monitoring of Photocatalytic Reactions

Real-time monitoring of photocatalytic reactions facilitates the elucidation of the mechanisms of the reactions. However, suitable tools for real-time monitoring are lacking. Herein, a novel method based on droplet spray ionization named substrate-coated illumination droplet spray ionization (SCI-DSI) for direct analysis of photocatalytic reaction solution is reported. SCI-DSI addresses many of the analytical limitations of electrospray ionization (ESI) for analysis of photocatalytic-reaction intermediates, and has potential for both in situ analysis and real-time monitoring of photocatalytic reactions. In SCI-DSI-mass spectrometry (MS), a photocatalytic reaction occurs by loading sample solutions onto the substrate-coated cover slip and by applying UV light above the modified slip; one corner of this slip adjacent to the inlet of a mass spectrometer is the high-electric-field location for launching a charged-droplet spray. After both testing and optimizing the performance of SCI-DSI, the value of this method for in situ analysis and real-time monitoring of photocatalytic reactions was demonstrated by the removal of cyclophosphamide (CP) in TiO{sub 2}/UV. Reaction times ranged from seconds to minutes, and the proposed reaction intermediates were captured and identified by tandem mass spectrometry. Moreover, the free hydroxyl radical (·OH) was identified as the main radicals for CP removal. These results show that SCI-DSI is suitable for in situ analysis and real-time monitoring of CP removal under TiO{sub 2}-based photocatalytic reactions. SCI-DSI is also a potential tool for in situ analysis and real-time assessment of the roles of radicals during CP removal under TiO{sub 2}-based photocatalytic reactions.Graphical Abstract .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A long-term pilot-scale algal cultivation on power plant flue gas – Cultivation stability and biomass accumulation

A long-term culture of a selected freshwater microalgal assemblage on power plant flue gas was realized using a pilot-scale photobioreactor. Different culture conditions of light cycle, harvesting amount, pH stabilization, and sulfur addition were tested during a 12-month continuous operation at a natural gas fired power plant. The results concluded that the daily harvesting amount of 60% with no light-cycle and NH 4 NO 3 as the nitrogen source and pH stabilization agent, resulted in optimal cultivation performance. Biomass concentration and biomass productivity reached 1.07 ± 0.23 g L -1 and 0.43 ± 0.14 g L -1 d -1 , respectively. During the year-long cultivation period, the algal assemblage was relatively stable with average abundances of 88 ± 4% and 12 ± 4% for algae and bacteria, respectively, and no significant differences between individual case scenarios. The stable culture fostered a stable biomass composition. Protein, carbohydrate, and lipid contents of the algal biomass were 58.60 ± 2.41%, 19.5 ± 2.44%, and 9.70 ± 1.68%, respectively.

09 BIOMASS FUELS↗

Densification and microstructure features of lithium hydride fabrication

The manufacturing of lithium hydride (LiH) utilizing uniaxial pressing, which offers fabrication with tailorable properties via microstructure control, can lead to the expansion in application of LiH while bypassing the challenges presented by historical casting manufacturing techniques. Through control of consolidation conditions such as pressure, temperature, dwell time and powder load, the presented work highlights the densification of LiH, with an emphasis on quantifying oxygen content, for applications requiring a specific density range necessary for optimized material performance. Karl Fischer Titration and X-ray Diffraction proved useful in determining oxygen and phase content while Computed Tomography and Scanning Electron Microscopy provided structural analysis. The temperature dependent densification of LiH fit with an Arrhenius term resulted in an activation energy of 21.2 kJ/mol. Images of fractured surfaces of LiH pressed at 500 °C revealed drastic grain coarsening, aided by the presence of oxygen impurities.

36 MATERIALS SCIENCE↗

Tuning transition metal nanoparticles on a non-traditional support via experimental design

The ability to control metal nanoparticle size and morphology on supported catalysts is crucial for optimizing catalytic performance in targeted applications. Here, this work presents a systematic approach for tuning Ni particle and crystallite size on an unconventional, low-porosity silica fume support through select thermal treatments. The catalyst was synthesized via the deposition of nickelocene onto silica fume, resulting in well-dispersed Ni nanoparticles. A face-centered central composite design was employed to systematically assess the effects of time, temperature, and sintering gas environment on metal particle growth. The results demonstrate that the sintering gas environment is the primary factor governing particle and crystallite evolution, with temperature as the next most significant influence. Nickel nanoparticles sintered at temperatures of 650 °C and above under inert conditions exhibited substantial growth and polycrystalline structures, whereas samples treated in oxidative environments formed NiO, restricting particle mobility. Minimally oxidative (500 ppm O₂) environments facilitated rapid sintering while effectively removing residual ligands from the one-step nickelocene deposition process. Extensive structural characterization via a combination of scanning transmission electron microscopy, X-ray diffraction, hydrogen temperature programmed reduction, and small-angle X-ray scattering revealed that oxidative treatments enhanced metal-support interactions, as evidenced by increased reduction temperatures and narrower particle size distributions. These findings establish quantitative relationships between sintering parameters and Ni nanoparticle characteristics, providing a framework for rational catalyst design through controlled thermal treatments. This methodology is broadly applicable to other catalytic systems and provides a quantitative foundation for catalyst design.

CVD↗

A comparative study on cubic and tetragonal Ce-ZrO 2 supported Rh catalysts for N 2 O decomposition

Zirconium oxide (ZrO 2 ) exhibits strong synergy with cerium oxide (CeO 2 ), acting as a structural and electronic promoter during catalytic redox reactions. As a result, Ce-ZrO 2 composite oxides are widely used as supports in various catalytic systems. In our previous work, we demonstrated that the incorporation of Zr 4+ into the CeO 2 lattice significantly enhanced Rh dispersion, improved redox ability, and stabilized surface Rh species, which collectively boosted the de-N 2 O activity of Rh/Ce-ZrO 2 catalysts. Building on these findings, the present study emphasizes that the crystallographic phase of Ce-ZrO 2 , governed by the Ce/Zr ratio, plays a decisive role in tuning the physicochemical environment of Rh active sites and thereby optimizing catalytic performance. In conclusion, tailoring the Ce/Zr ratio to favor the cubic fluorite structure emerges as a promising strategy for the rational design of highly active and stable catalysts for N 2 O decomposition and potentially other redox-sensitive environmental applications.

36 MATERIALS SCIENCE↗