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Chen, Wei

Publications and source records attributed to Chen, Wei.

At least 55 records · Page 3

Highly Selective Photoelectroreduction of Carbon Dioxide to Ethanol over Graphene/Silicon Carbide Composites

Using sunlight to produce valuable chemicals and fuels from carbon dioxide (CO 2 ), i.e., artificial photosynthesis (AP) is a promising strategy to achieve solar energy storage and a negative carbon cycle. However, selective synthesis of C 2 compounds with a high CO 2 conversion rate remains challenging for current AP technologies. Here, we performed CO 2 photoelectroreduction over a graphene/silicon carbide (SiC) catalyst under simulated solar irradiation with ethanol (C 2 H 5 OH) selectivity of>99 % and a CO 2 conversion rate of up to 17.1 mmol g cat -1 h -1 with sustained performance. Experimental and theoretical investigations indicated an optimal interfacial layer to facilitate the transfer of photogenerated electrons from the SiC substrate to the few-layer graphene overlayer, which also favored an efficient CO 2 to C 2 H 5 OH conversion pathway.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phosphorylated tri-block copolymers with antimicrobial properties

The disclosure provides products and methods of treating diseases and disorders involving microbial pathogens, such as intestinal microbial pathogens, e.g., Pseudomonas aeruginosa, by administering an effective amount of a phosphorylated polyethylene glycol compound of defined structural organization. Those diseases and disorders characterized by an epithelium attacked by a microbial pathogen are contemplated, including gastrointestinal infections and inflammation, e.g., treatment of intestinal or esophageal anastomosis or treatment or suppression of anastomotic leakage.

Alverdy, John C.↗

Bottom-up evolution of perovskite clusters into high-activity rhodium nanoparticles toward alkaline hydrogen evolution

Self-reconstruction has been considered an efficient means to prepare efficient electrocatalysts in various energy transformation process for bond activation and breaking. However, developing nano-sized electrocatalysts through complete in-situ reconstruction with improved activity remains challenging. Herein, we report a bottom-up evolution route of electrochemically reducing Cs 3 Rh 2 I 9 halide-perovskite clusters on N-doped carbon to prepare ultrafine Rh nanoparticles (~2.2 nm) with large lattice spacings and grain boundaries. Various in-situ and ex-situ characterizations including electrochemical quartz crystal microbalance experiments elucidate the Cs and I extraction and Rh reduction during the electrochemical reduction. These Rh nanoparticles from Cs 3 Rh 2 I 9 clusters show significantly enhanced mass and area activity toward hydrogen evolution reaction in both alkaline and chlor-alkali electrolyte, superior to liquid-reduced Rh nanoparticles as well as bulk Cs 3 Rh 2 I 9 -derived Rh via top-down electro-reduction transformation. Theoretical calculations demonstrate water activation could be boosted on Cs 3 Rh 2 I 9 clusters-derived Rh nanoparticles enriched with multiply sites, thus smoothing alkaline hydrogen evolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A constitutive framework for rocks undergoing solid dissolution

Here, we formulate a time-dependent damage theory for rocks subjected to mechanical deformation and solid dissolution. The constitutive description is inspired by the transition state theory, which states that the rate of dissolution is a function of the reactive surface area measured through the crack density in the volume. We use a gradient-enhanced damage framework in which damage depends on the deformation of the material as well as on the amount of solid mass dissolved over time. The gradient-enhanced formulation is characterized by a three-field variational formulation with the solid displacement, nonlocal equivalent strain, and nonlocal rate of solid dissolution as the basic state variables. Traditionally, time-independent damage theories have only allowed damage to increase with increasing external load. In the proposed framework, the degree of damage may increase due to solid dissolution even when the external load is held fixed. In this way, solid dissolution is viewed as a process that is responsible for bringing about rate-dependent effects such as creep and stress-relaxation, which are two common features of geomaterial behavior.

42 ENGINEERING↗

Interface formation and Schottky barrier height for Y, Nb, Au, and Pt on Ge as determined by hard x-ray photoelectron spectroscopy

Development of a robust, thin, hole-blocking (n+) contact on high purity germanium (HPGe) has been the main challenge in the development of Ge-based radiation sensors. Yttrium has been reported to be a viable hole-blocking contact on HPGe, and detectors with low leakage have been fabricated. Niobium has also been considered as a potential hole-blocking contact due to its low work function. Here, we investigate interface chemistry and the Schottky barrier height of Y and Nb, as well as electron-blocking contacts Au and Pt, on Ge(100) surfaces using hard x-ray photoelectron spectroscopy. We find a barrier height of 1.05 ± 0.10 eV for Y/HPGe, confirming the formation of a hole-blocking barrier. For Nb/HPGe, the barrier height of 0.13 ± 0.10 eV demonstrates that the interface is not hole-blocking. The Schottky barrier of Au and Pt was found to be 0.45 ± 0.10 and 0.51 ± 0.10 eV, respectively.

36 MATERIALS SCIENCE↗

Broccoli seed extract rich in polysaccharides and glucoraphanin ameliorates DSS ‐induced colitis via intestinal barrier protection and gut microbiota modulation in mice

Abstract BACKGROUND Broccoli has received widespread attention because of its anti‐inflammatory and antioxidant effects. The present study aimed to explore the composition of broccoli seed extract (BSE) and its effect on colitis induced by dextran sulfate sodium (DSS). RESULTS BSE mainly comprises glucoraphanin and polysaccharides composed of arabinose, galactose, glucose and mannose. Animal experiments suggested that BSE intervention effectively reversed body weight loss, suppressed the levels of proinflammatory interleukin‐6, tumor necrosis factor‐α and interleukin‐1β, and elevated the levels of anti‐inflammatory interleukin‐10 and the activities of superoxide dismutase and glutathione in DSS‐induced colitis mice. According to histopathologic and immunohistochemical analysis of colon tissue, BSE intervention may repair the intestinal barrier by upregulating mRNA levels and the expression of tight junction proteins (claudin‐1, occludin and zonula occludens‐1). Gas chromatography–mass spectrometry (MS) analysis demonstrated that cecal short‐chain fatty acids in mice with BSE administration were significantly increased compared with the model group. Sulforaphane and sulforaphane‐ N ‐acetylcysteine were only detected in BSE group mice by ultra‐performance liquid chromatography‐MS analysis. In addition, BSE intervention evidently increased the abundance of Alistipeds , Coriobacteriaceae UCG‐002 and Bifidobacterium and decreased the abundance of Escheichia‐Shinella , Lachnospiraceae others , Parabacteroides , Ruminococcaceae others and Turicibacter , which possibly promoted carbohydrate metabolism and short‐chain fatty acid production. CONCLUSION The present study aimed to elucidate the effect of BSE on colitis and found that BSE, as a novel food ingredient, has great potential for the improvement of colitis. © 2022 Society of Chemical Industry.

Wu, Jiaying↗

Uncertainty-aware mixed-variable machine learning for materials design

Abstract Data-driven design shows the promise of accelerating materials discovery but is challenging due to the prohibitive cost of searching the vast design space of chemistry, structure, and synthesis methods. Bayesian optimization (BO) employs uncertainty-aware machine learning models to select promising designs to evaluate, hence reducing the cost. However, BO with mixed numerical and categorical variables, which is of particular interest in materials design, has not been well studied. In this work, we survey frequentist and Bayesian approaches to uncertainty quantification of machine learning with mixed variables. We then conduct a systematic comparative study of their performances in BO using a popular representative model from each group, the random forest-based Lolo model (frequentist) and the latent variable Gaussian process model (Bayesian). We examine the efficacy of the two models in the optimization of mathematical functions, as well as properties of structural and functional materials, where we observe performance differences as related to problem dimensionality and complexity. By investigating the machine learning models’ predictive and uncertainty estimation capabilities, we provide interpretations of the observed performance differences. Our results provide practical guidance on choosing between frequentist and Bayesian uncertainty-aware machine learning models for mixed-variable BO in materials design.

36 MATERIALS SCIENCE↗

First survey of centimeter-scale AC-LGAD strip sensors with a 120 GeV proton beam

We present the first beam test results with centimeter-scale AC-LGAD strip sensors, using the Fermilab Test Beam Facility and sensors manufactured by the Brookhaven National Laboratory. Sensors of this type are envisioned for applications that require large-area precision 4D tracking coverage with economical channel counts, including timing layers for the Electron Ion Collider (EIC), and space-based particle experiments. A survey of sensor designs is presented, with the aim of optimizing the electrode geometry for spatial resolution and timing performance. Several design considerations are discussed towards maintaining desirable signal characteristics with increasingly larger electrodes. The resolutions obtained with several prototypes are presented, reaching simultaneous 18 micron and 32 ps resolutions from strips of 1 cm length and 500 micron pitch. With only slight modifications, these sensors would be ideal candidates for a 4D timing layer at the EIC.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Descriptor Aided Bayesian Optimization for Many-Level Qualitative Variables With Materials Design Applications

Abstract Engineering design often involves qualitative and quantitative design variables, which requires systematic methods for the exploration of these mixed-variable design spaces. Expensive simulation techniques, such as those required to evaluate optimization objectives in materials design applications, constitute the main portion of the cost of the design process and underline the need for efficient search strategies—Bayesian optimization (BO) being one of the most widely adopted. Although recent developments in mixed-variable Bayesian optimization have shown promise, the effects of dimensionality of qualitative variables have not been well studied. High-dimensional qualitative variables, i.e., with many levels, impose a large design cost as they typically require a larger dataset to quantify the effect of each level on the optimization objective. We address this challenge by leveraging domain knowledge about underlying physical descriptors, which embody the physics of the underlying physical phenomena, to infer the effect of unobserved levels that have not been sampled yet. We show that physical descriptors can be intuitively embedded into the latent variable Gaussian process approach—a mixed-variable GP modeling technique—and used to selectively explore levels of qualitative variables in the Bayesian optimization framework. This physics-informed approach is particularly useful when one or more qualitative variables are high dimensional (many-level) and the modeling dataset is small, containing observations for only a subset of levels. Through a combination of mathematical test functions and materials design applications, our method is shown to be robust to certain types of incomplete domain knowledge and significantly reduces the design cost for problems with high-dimensional qualitative variables.

Engineering↗

Investigation of signal characteristics and charge sharing in AC-LGADs with laser and test beam measurements

AC-LGADs, also referred to as resistive silicon detectors, are a recent development of low-gain avalanche detectors (LGADs), based on a sensor design where the multiplication layer and n + contact are continuous, and only the metal layer is patterned. In AC-LGADs, the signal is capacitively coupled from the continuous, resistive n + layer over a dielectric to the metal electrodes. Therefore, the spatial resolution is not only influenced by the electrode pitch, but also the relative size of the metal electrodes. Signal propagation between the metallized areas and charge sharing between electrodes plays a larger role in these detectors than in conventional silicon sensors read out in DC mode. AC-LGADs from two manufacturers were studied in beam tests and with infrared laser scans. The impact of n + layer resistivity and metal electrode pitch on the charge sharing and achievable position resolution is shown. For strips with 100 μm pitch, a resolution of ¡ 5 μm can be reached. Additionally, the charge sharing between neighboring strips is investigated in more detail, indicating the induction of signal charge and subsequent re-sharing over the n + layer. Furthermore, an approach to identify signal sharing over large distances is presented.

47 OTHER INSTRUMENTATION↗

Nonunique fraction of Fock exchange for defects in two-dimensional materials

By investigating the vacancy and substitutional defects in monolayer WS 2 with hybrid functionals, we find that there is no unique amount of Fock exchange that concurrently satisfies the generalized Koopmans' condition and reproduces the band-gap and band-edge positions. Fixing the mixing parameter of Fock exchange based on the band gap can lead to qualitatively incorrect defect physics in two-dimensional materials. Instead, excellent agreement is achieved with both experiment and many-body perturbation theory within the GW approximation once the mixing parameters are tuned individually for the defect species and the band edges. Here, we show the departure from a unique optimized mixing parameter is inherent to two-dimensional systems as the band edges experience a reduced screening while the localized defects are subject to bulklike screening.

2-dimensional systems↗

First-principles comparative study of Cr migration in O3 and O/P hybrid-phased NaCrO 2

In layered Na transition-metal (TM) oxides, TM migration usually occurs at highly charged states and severely deteriorates the capacity and reversibility. Meanwhile, the formation of hybrid phases with the intergrowth of octahedral (O-type) and prismatic (P-type) Na layers also takes place at highly charged states. These hybrid phases are often more stable than simple O3 or P3 stackings. However, little is known about the mechanism and impact of TM migration in these hybrid phases. In this work, a comparative first-principles study is performed to understand the connections between structural changes and Cr migration in layered O3 and hybrid-phased NaCrO 2 . After Cr migration, the hybrid-phased NaCrO 2 suffers from greater layer shrinkage than the O3 phase. Three factors affect the Cr migration energy E mig : the Na concentration, local 3D configurations, and 2D in-plane geometries. Low Na concentrations and certain local 3D configurations facilitate the Cr migration. The Cr migration barriers in both O3 and hybrid-phased NaCrO 2 are positively correlated with the Cr E mig . The Cr migration in 17 doped O3 and hybrid-phased NaCrO 2 is surveyed. In these doped NaCrO 2 , a more uniform distribution of the Cr–O bond lengths usually suggests suppressed Cr migration. Optimal dopants for suppressing Cr migration are identified by considering E mig for both Cr and the dopant. Finally, our comparative study on Cr migration in O3 and hybrid-phased NaCrO 2 reveals the significant role of hybrid-phased structures in the development of layered cathode materials.

36 MATERIALS SCIENCE↗

Direct Observation of Solvent–Reaction Intermediate Interactions in Heterogeneously Catalyzed Alcohol Coupling

The relative stability of reactive intermediates and reactants on a surface, which dictates the rate and selectivity of catalytic reactions in both gas and liquid phases, is dependent on numerous factors. One well-established example is secondary interactions, such as van der Waals interactions between the catalyst surface and the pendant group of the intermediate, which can govern reaction selectivity for coupling reactions. In this work, we directly show that interactions between adsorbed reaction intermediates and reactant molecules increase the binding energy and affects the geometrical arrangement of coadsorbed reactant/solvent molecules. Evidence for this effect is demonstrated for the oxidative coupling reaction of methanol on a single crystal gold (Au(110)) surface. The rate-limiting reaction intermediate for methanol selfcoupling, methoxy, stabilizes excess adsorbed methanol, which desorbs as a result of beta-hydride decomposition of the adsorbed methoxy. Direct molecular-scale imaging by scanning tunneling microscopy, supplemented by density functional theory, revealed interactive structures formed by methoxy and coadsorbed methanol. Interactions between the methoxy intermediate and coadsorbed methanol stabilizes a hydrogen-bonded network comprising methoxy and methanol by a minimum of 0.13 eV per methanol molecule. Inclusion of such interactions between reaction intermediates and coadsorbed reactants and solvents in kinetic models is important for microkinetic analysis of the rates and selectivities of catalytic reactions in both the gas and liquid phases whenever appreciable coverages of species from the ambient phase exist.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design metastability in high-entropy alloys by tailoring unstable fault energies

Metastable alloys with transformation-/twinning-induced plasticity (TRIP/TWIP) can overcome the strength-ductility trade-off in structural materials. Originated from the development of traditional alloys, the intrinsic stacking fault energy (ISFE) has been applied to tailor TRIP/TWIP in high-entropy alloys (HEAs) but with limited quantitative success. Here, we demonstrate a strategy for designing metastable HEAs and validate its effectiveness by discovering seven alloys with experimentally observed metastability for TRIP/TWIP. We propose unstable fault energies as the more effective design metric and attribute the deformation mechanism of metastable face-centered cubic alloys to unstable martensite fault energy (UMFE)/unstable twin fault energy (UTFE) rather than ISFE. Among the studied HEAs and steels, the traditional ISFE criterion fails in more than half of the cases, while the UMFE/UTFE criterion accurately predicts the deformation mechanisms in all cases. The UMFE/UTFE criterion provides an effective paradigm for developing metastable alloys with TRIP/TWIP for an enhanced strength-ductility synergy.

36 MATERIALS SCIENCE↗