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At least 775 records · Page 43

Compositional analysis of dilute nitride doped indium antimonide bulk crystal by VDS technique

Dilute nitrides are suitable materials for fabrication of devices in detection of long wavelength infrared region. Dilute nitride doped Indium antimonide bulk crystals were grown using vertical directional solidification technique. The compositional characteristics of the crystals were carried out using EDS. The analysis was simulated and compared with observations using DTSA II software for accuracy. The ingots have uniform composition of Indium and Antimony. The actual nitrogen composition measured using EDS was 0.136% for doped nitrogen composition 0.1% except near conical end where it was 0.1%. The study of bonding between nitrogen, Indium and antimony was carried out using SIMS. The analysis shows strong presence of In-N bonding along with In-Sb bonds which indicates nitrogen has replaced antimony atoms in crystal lattice.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Constituent properties, process, and formulation effects contributing to functional characteristics in pharmaceutical and explosive composites [Slides]

Crystal properties and defects contribute substantially to basic properties. Dip-coated films display a number of properties which are expected to be present in wet agglomeration / real formulation. Nanoindentation provides more detailed information about static dislocations and a useful simulation of real deformation processes during formulation of pressed composites. Continuum measurements are limited in what can be mechanistically determined, but we are on the verge of breakthroughs in dynamic in situ experiments!

36 MATERIALS SCIENCE↗

Modeling biomass gasification system using multistep kinetics under various oxygen–steam conditions

Biomass gasification is an effective method to convert low‐value lingocellulosic biomass into useful gas products. The ability to predict the gas composition is important to process design. In this study, simulations of biomass gasification were carried out for various feedstocks at different operating conditions, and the model results were validated using experimental data. A multistep kinetics model was developed to predict the syngas composition using different biomass feedstocks under various oxygen‐enriched air and steam conditions. The oxygen level in the gasifying agent ranged from 21% (air) to 45% (pure oxygen). Five different biomass materials were used, including pine, maple–oak mixture, seed corn, corn stover, and switchgrass. The fluidized bed gasifier was maintained at 800°C. The present kinetics model was able to predict the concentrations of H 2 , CO, CO 2 , H 2 O, CH 4 , and N 2 in the syngas, and the predicted compositions were in good agreement with the experimental data. The results show that the model was sensitive to the variation in the oxygen level, steam flow rate, and the composition of the biomass material. As the oxygen level increased, the model also predicted the increase in H 2 , CO, CH 4 , and the H 2 /CO ratio. The mechanism on improving the syngas quality was also explained by analyzing the reaction equations. The increase in hydrogen is believed to be due to the use of steam for gasification. The present model can further be integrated into the process simulation model for predicting the performance of a biorefinery to help utilize biomass energy. © 2015 American Institute of Chemical Engineers Environ Prog, 34: 1148–1155, 2015

Banerjee, Sudhanya↗

Composite Structured Surfaces for Durable Dropwise Condensation

Condensation heat transfer is a vital process for a plethora of industrial application. Dropwise condensation of steam on hydrophobic polymers, typified by the formation of discrete water droplets which shed and clear the surface for re-nucleation, has a 10X higher heat transfer coefficient when compared to filmwise condensation on bare metallic surfaces. However, 8 decades of research have conclusively demonstrated a lack of durability of the hydrophobic coatings during dropwise condensation to quantify industrial implementation. They key bottleneck is the coating conundrum, which states that thick hydrophobic coatings (> 10 µm) are required for higher durability, while thin hydrophobic coatings (< 1 µm) are required for low parasitic thermal resistance due to the low intrinsic thermal conductivity of polymeric materials (k ~ 0.1 W/m·K). Here, we attempt to solve the conundrum by developing rationally-designed metal-polymer composite coatings to increase the effective thermal conductivity of the hydrophobic coating, thereby enabling thicker coatings for higher durability. We study nanowire, inverse opal, and sintered sphere metallic structures infilled with hydrophobic polymers. To quantify the heat transfer performance, we analyze the vapor-to-coolant and vapor-to-surface heat transfer coefficients of composite coated flat surfaces having varying wire/sphere diameters (D = 100 nm, 1 μm, 10 μm) and coating thickness (10 nm < t < 100 μm) using three-dimensional (3D), steady state, Comsol simulations. We show that analytical models such as Maxwell or effective medium theory fail to predict the composite thermal conductivity. By conducting simulation with two independent sets of boundary conditions; isothermal surfaces and convection, as well as by varying the interfacial metal fractions, we demonstrate the importance of 3D heat spreading near the coating-vapor and coating-substrate interface. To predict the wetting characteristics to ensure stable dropwise condensation, we coupled our 3D heat transfer simulations to a unified model for contact angle hysteresis on heterogeneous surfaces. Our wetting predictions identify the key tradeoff between low spreading resistance (high k, filmwise condensation) and low contact angle hysteresis (low k, dropwise condensation) on high and low surface metal fractions, respectively, and identify the optimum metallic structure, volume fraction, interfacial solid fraction, and thickness for enhanced durability. Our work provides a novel approach to utilize rational metallic nanostructuring to create composite hydrophobic coatings which promise enhanced durability.

Chang, Ho Chan↗

Load Model Data Tool

The LMDT software automates the process of the load composite model data preparation in the format supported by the major power system software vendors (GE and Siemens). Proper representation of the load composite model in power system dynamic analysis is very important. Software tools for power system simulation like GE PSLF and Siemens PSSE already include algorithms for the load composite modeling. However, these tools require that the input information on composite load to be provided in custom formats. Preparation of this data is time consuming and requires multiple manual operations. The LMDT software enables to automate this process. Software is designed to generate composite load model data. It uses the default load composition data, motor information, and bus information as an input. Software processes the input information and produces load composition model. Generated model can be stored in .dyd format supported by GE PSLF package or .dyr format supported by Siemens PSSE package.

Etingov, Pavel↗

Degradation behavior of hydroxyapatite/poly(lactic-co-glycolic) acid nanocomposite in simulated body fluid

Graphical abstract: In this manuscript, we initiated a systematic study to investigate the effect of HA on thermal properties, inner structure, reduction of mechanical strength, surface morphology and the surface deposit of n-HA/PLGA composite with respect to the soaking time. The results showed that n-HA played an important role in improving the degradation behavior of n-HA/PLGA composite, which can accelerate the degradation of n-HA/PLGA composite and endow it with bioactivity, after n-HA was detached from PLGA during the degradation, so that n-HA/PLGA composite may have a more promising prospect of the clinical application than pure PLGA as bone fracture internal fixation materials, and the results would be of reference significance to predict the in vivo degradation and biological properties. - Highlights: • Effect of n-HA on degradation behavior of n-HA/PLGA composite was investigated. • Degradation behaviors of n-HA/PLGA and PLGA were carried out in SBF for 6 months. • Viscosity, thermal properties, inner structure and bending strength were tested. • n-HA can accelerate the degradation and endows it with bioactivity. - Abstract: To investigate the effect of hydroxyapatite(HA) on the degradation behavior of hydroxyapatite/poly(lactic-co-glycolic) acid (HA/PLGA) nanocomposite, the degradation experiment of n-HA/PLGA composite and pure PLGA were carried out by soaking in simulated body fluid(SBF) at 37 °C for 1, 2, 4 and 6 months. The change of intrinsic viscosity, thermal properties, inner structure, bending strength reduction, surface morphology and the surface deposit of n-HA/PLGA composite and pure PLGA with respect to the soaking time were investigated by means of UbbeloHde Viscometer, differential scanning calorimeter (DSC), scanning electron microscope(SEM), electromechanical universal tester, a conventional camera and X-ray diffraction (XRD). The results showed that n-HA played an important role in improving the degradation behavior of n-HA/PLGA composite, which can accelerate the degradation PLGA and endow it with bioactivity, after n-HA was detached from PLGA during the degradation, so that n-HA/PLGA composite may have a more promising prospect of the clinical application than pure PLGA as bone fracture internal fixation materials.

36 MATERIALS SCIENCE↗

Noble gas constraints on spent fuel irradiation histories

Fission gas isotopic compositions are sensitive to a variety of reactor operating parameters that include the neutron flux, neutron fluence at different neutron energies, and operating temperature. Measurements of fission gas isotopic compositions thus have potential to constrain reactor simulations for nuclear forensics and safeguards applications. In this paper, we present Kr and Xe isotope measurements from a suite of samples obtained from locations that span the axial length a fuel pin with a well-characterized irradiation history and compare these data to spatially resolved reactor simulations. Here, we observed positive correlations between fluence sensitive isotopic ratios and burnup and between a flux sensitive ratio and power, although some discrepancies are observed between the measured data and model predictions. These differences may be due to simplifications in the model and/or inaccuracies in the cross sections. A much broader measurement to model comparison is required to better understand the discrepancies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Genomic materials design: CALculation of PHAse Dynamics

The CALPHAD system of fundamental phase-level databases, now known as the Materials Genome, has enabled a mature technology of computational materials design and qualification that has already met the acceleration goals of the national Materials Genome Initiative. Here, as first commercialized by QuesTek Innovations, the methodology combines efficient genomic-level parametric design of new material composition and process specifications with multidisciplinary simulation-based forecasting of manufacturing variation, integrating efficient uncertainty management. Recent projects demonstrated under the multi-institutional CHiMaD Design Center notably include novel alloys designed specifically for additive manufacturing. With the proven success of the CALPHAD-based Materials Genome technology, current university research emphasizes new methodologies for affordable accelerated expansion of more accurate CALPHAD databases. Rapid adoption of these new capabilities by US apex corporations has compressed the materials design and development cycle to under 2 years, enabling a new “materials concurrency” integrated into a new level of concurrent engineering supporting an unprecedented level of manufacturing innovation.

36 MATERIALS SCIENCE↗

Carbon sequestration of steel slag and carbonation for activating RO phase

Carbonation of Ca/Mg minerals in industrial alkaline residues is a technology to sequester CO{sub 2} and reduce its emissions to the atmosphere. In this work, BSE-EDS were used to determine the mineral phase in steel slag; compositions of RO phase were identified and simulated. The carbon sequestration of steel slag was studied, and RO phase was activated by carbonation. Result shows that the amount of CO{sub 2} sequestered in steel slag and RO phase increases as carbonation time increases. Under autoclaving condition, the hydration ratio of MgO in RO phase was 20.10%. Through carbonation, up to 58.83% of MgO in RO phase can be converted into MgCO{sub 3}, and the activation of RO phase by carbonation was manifested. The mechanical properties and volume stability of carbonated steel slag were improved, proving that the positive effect of carbonation on steel slag when applied in cement and cementitious materials.

36 MATERIALS SCIENCE↗

Assessment of CO 2 trapping mechanisms in partially depleted oil-bearing sands

The goal of this work is to evaluate various CO 2 sequestration mechanisms occurring in the Morrow B Sandstone in the Farnsworth Unit. A history-matched numerical simulation model was created using extensive geological, petrophysical, and operational data collected from the field. The numerical model is competent to investigate the impact of residual, structural-stratigraphic, solubility, and mineral trapping mechanisms on the fluid transportation dynamics and petrophysical property variations. The model forecasts the field response of 20 years of WAG injections. Afterward, all wells were shut-in, and the reservoir was allowed to evolve for 1000 years to investigate the fate of injected CO 2 . In this paper, we assess the impacts of various trapping mechanisms on oil recovery and CO 2 storage efficacy. By analyzing the results reported from the numerical simulation model, the in-situ fluid composition and mineralogy changes are also investigated. More importantly, we seek to confirm the petrophysical property variations due to the CO 2 injection with observations from laboratory measurements. The experiences gained from this study provide valuable insights regarding physiochemical storage induced by the CO 2 injection activities and serve as a benchmark case for future CO 2 enhanced oil recovery (EOR) projects involving reactive solute transport.

42 ENGINEERING↗

Multifidelity deep operator networks for data-driven and physics-informed problems

Operator learning for complex nonlinear systems is increasingly common in modeling multi-physics and multi-scale systems. However, training such high-dimensional operators requires a large amount of expensive, high-fidelity data, either from experiments or simulations. In this work, we present a composite Deep Operator Network (DeepONet) for learning using two datasets with different levels of fidelity to accurately learn complex operators when sufficient high-fidelity data is not available. Additionally, we demonstrate that the presence of low-fidelity data can improve the predictions of physics-informed learning with DeepONets. We demonstrate the new multi-fidelity training in diverse examples, including modeling of the ice-sheet dynamics of the Humboldt glacier, Greenland, using two different fidelity models and also using the same physical model at two different resolutions.

97 MATHEMATICS AND COMPUTING↗

Predicting the Phase Stability of Multicomponent High-Entropy Compounds

A generic method to estimate the relative feasibility of formation of high-entropy compounds in a single phase, directly from first principles, is developed. As a first step, the relative formation abilities of 56 multicomponent, AO, oxides were evaluated. These were constructed from five cation combinations chosen from A = {Ca, Co, Cu, Fe, Mg, Mn, Ni, Zn}. Candidates for multicomponent oxides are predicted from descriptors related to the enthalpy and configurational entropy obtained from the mixing enthalpies of two-component oxides. The utility of this approach is evaluated by comparing the predicted combinations with the experimentally realized entropy-stabilized oxide, (MgCoCuNiZn)O. In the second step, Monte Carlo simulations are utilized to investigate the phase composition and local ionic segregation as a function of temperature. This approach allows for the evaluation of potential secondary phases, thereby making realistic predictions of novel multicomponent compounds that can be synthesized.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Methanogenesis and Acetogenesis in Hydrogenotrophy with Carbonate Minerals: Dependence on Mineral Surface Area, Biofilm Growth, and Microbial Community

The production, storage, and use of hydrogen are anticipated to grow substantially to achieve energy and climate goals. Consequently, microbial communities in many terrestrial and subsurface Earth environments could be exposed to elevated hydrogen concentrations. Hydrogen stimulates metabolic processes that reduce aqueous chemical species, such as bicarbonate or sulfate, that can exchange with solid mineral phases, but the controls on microbial hydrogenotrophy with mineral sources of electron acceptors are not fully understood. Herein, we applied laboratory experiments and biogeochemical modeling to study the response of a natural microbial community to an elevated partial pressure of hydrogen in the presence of carbonate minerals of varying composition, solubility, and size. Experimental incubations and simulation results showed that hydrogen consumption by microbial communities was initially dominated by sulfate reduction and, subsequently, transitioned to acetogenesis and methanogenesis. The rates of acetogenesis and methanogenesis were not correlated with the solubility of carbonate minerals. Instead, we observed strong linear correlations between the rates and surface area of carbonate minerals. Methane and acetate production slowed down in all incubations after about 2 weeks of incubation, although biogeochemical modeling predicted that the metabolic processes were not thermodynamically limited. Electron microscopy and infrared spectroscopy showed that biofilms with diverse microorganisms grew on the carbonates during this period. The methane δ13C value significantly increased, consistent with slower growth at elevated pH. This work highlights that microbial communities form biofilm on carbonate mineral surfaces as a response to hydrogen and that biofilm formation could pose a strong kinetic limitation to hydrogenotrophic metabolism utilizing carbonate minerals.

Acetobacterium↗

Comparison of Current and Future PM2.5 Air Quality in China Under CMIP6 and DPEC Emission Scenarios

The latest scenarios for the sixth Coupled Model Intercomparison Project (CMIP6) provide opportunities to explore future climate and air pollution mitigation pathways with socioeconomic features. However, to what extent inadequate consideration of region-specific policies in the CMIP6 scenarios would affect regional air quality projections is still not clear. Here, we simulated China’s future PM2.5 concentrations and compositions with local policy-based scenarios and the original CMIP6 datasets, for the first time estimating future air quality differences induced by the lack of local pollution control policies in the CMIP6 scenarios. We found that the CMIP6-driven projections overestimate major chemical aerosols by 10% – 70% in 2015 and fail to capture the rapid PM2.5 concentration decline during 2015–2019. Near-term differences further lead to 43% – 49% (5 – 9 µg/m3) PM2.5 overpredictions in 2050 in CMIP6 scenarios compared with policy-based mitigation scenarios. Our study demonstrates the indispensable influences of local policies on regional analyses and suggests that the research community should incorporate more region-specific information in future scenario designs.

Cheng, Jing↗

Regularization via f -Divergence: An Application to Multi-Oxide Spectroscopic Analysis

In this paper, we explore the application of convolutional neural networks (CNNs) for predicting the chemical composition of complex geologic samples in a simulated Martian atmospheric environment. Specifically, we aim to characterize oxide weight percentages (wt.%) of rock samples analyzed by remote Laser-Induced Breakdown Spectroscopy (LIBS), framing the problem as a multi-target regression task . Neural networks trained on LIBS spectra are prone to overfitting due to high spectral complexity, limited labeled data, and measurement noise. While regularization is critical for improving generalization, common methods (e.g., ℓ 2 regularization) impose constraints not directly tied to data distribution properties. We propose a novel regularization method based on a specific ƒ-divergence induced by a graph-based estimator, designed to constrain the distributional discrepancy between predictions and targets. This regularizer serves a dual purpose: (a) mitigating overfitting by enforcing a constraint on the distributional difference between predictions and noisy targets, and (b) acting as an auxiliary loss that penalizes large divergences. To enable backpropagation, we develop a differentiable approximation of this particular ƒ-divergence, making the method feasible for neural networks. Experiments on ChemCam and SuperCam LIBS calibration spectra show that mathematical equation-divergence regularization outperforms or matches standard regularization methods (ℓ 1 , ℓ 2 , dropout) and the classical baseline, partial least squares (PLS). Combining ƒ-divergence regularization with standard regularization yields further performance gains, indicating that distributional regularization is useful in this context giving a promising direction for robust model training in planetary science applications. Source code is publicly available at Klein and Li (2025), https://doi.org/10.11578/dc.20250530.7.

58 GEOSCIENCES↗

Methylation enables the use of fluorine-free ether electrolytes in high-voltage lithium metal batteries

Lithium metal batteries represent a promising technology for next-generation energy storage, but they still suffer from poor cycle life due to lithium dendrite formation and cathode cracking. Fluorinated solvents can improve battery longevity by improving LiF content in the solid-electrolyte interphase; however, the high cost and environmental concerns of fluorinated solvents limit battery viability. Here, for this work, we designed a series of fluorine-free solvents through the methylation of 1,2-dimethoxyethane, which promotes inorganic LiF-rich interphase formation through anion reduction and achieves high oxidation stability. The anion-derived LiF interphases suppress lithium dendrite growth on the lithium anode and minimize cathode cracking under high-voltage operation. The Li + -solvent structure is investigated through in situ techniques and simulations to draw correlations between the interphase compositions and electrochemical performances. The methylation strategy provides an alternative pathway for electrolyte engineering towards high-voltage electrolytes while reducing dependence on expensive fluorinated solvents.

25 ENERGY STORAGE↗

Energy resolved actinometry for simultaneous measurement of atomic oxygen densities and local mean electron energies in radio-frequency driven plasmas

A diagnostic method for the simultaneous determination of atomic oxygen densities and mean electron energies is demonstrated for an atmospheric pressure radio-frequency plasma jet. The proposed method is based on phase resolved optical emission measurements of the direct and dissociative electron-impact excitation dynamics of three distinct emission lines, namely, Ar 750.4 nm, O 777.4 nm, and O 844.6 nm. The energy dependence of these lines serves as basis for analysis by taking into account two line ratios. In this frame, the method is highly adaptable with regard to pressure and gas composition. Results are benchmarked against independent numerical simulations and two-photon absorption laser-induced fluorescence experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Functionally graded magnetic materials: a perspective to advance charged particle optics through compositional engineering

Additive manufacturing has ushered in a new paradigm of bottom-up materials-by-design of spatially non-uniform materials. Functionally graded materials have locally tailored compositions to provide optimized global properties and performance. In this letter, we propose an opportunity for the application of graded magnetic materials as lens elements for charged particle optics. A Hiperco50/Hymu80 (FeCo-2 V/Fe-80Ni-5Mo) graded magnetic alloy was successfully additively manufactured via Laser Directed Energy Deposition with spatially varying magnetic properties. The compositional gradient is then applied using computational simulations to demonstrate how a tailored material can enhance the magnetic performance of a critical, image-forming component of a transmission electron microscope.

36 MATERIALS SCIENCE↗