Single-atom tailoring of platinum nanocatalysts for high-performance multifunctional electrocatalysis

Platinum-based nanocatalysts play a crucial role in various electrocatalytic systems that are important for renewable, clean energy conversion, storage and utilization. However, the scarcity and high cost of Pt seriously limit the practical application of these catalysts. Decorating Pt catalysts with other transition metals offers an effective pathway to tailor their catalytic properties, but often at the sacrifice of the electrochemical active surface area (ECSA). Here we report a single-atom tailoring strategy to boost the activity of Pt nanocatalysts with minimal loss in surface active sites. By starting with PtNi alloy nanowires and using a partial electrochemical dealloying approach, we create single-nickel-atom-modified Pt nanowires with an optimum combination of specific activity and ECSA for the hydrogen evolution, methanol oxidation and ethanol oxidation reactions. The single-atom tailoring approach offers an effective strategy to optimize the activity of surface Pt atoms and enhance the mass activity for diverse reactions, opening a general pathway to the design of highly efficient and durable precious metal-based catalysts

Single-atom tailoring of platinum nanocatalysts for high-performance multifunctional electrocatalysis

Platinum-based nanocatalysts play a crucial role in various electrocatalytic systems that are important for renewable, clean energy conversion, storage and utilization. However, the scarcity and high cost of Pt seriously limit the practical application of these catalysts. Decorating Pt catalysts with other transition metals offers an effective pathway to tailor their catalytic properties, but often at the sacrifice of the electrochemical active surface area (ECSA). Here we report a single-atom tailoring strategy to boost the activity of Pt nanocatalysts with minimal loss in surface active sites. By starting with PtNi alloy nanowires and using a partial electrochemical dealloying approach, we create single-nickel-atom-modified Pt nanowires with an optimum combination of specific activity and ECSA for the hydrogen evolution, methanol oxidation and ethanol oxidation reactions. The single-atom tailoring approach offers an effective strategy to optimize the activity of surface Pt atoms and enhance the mass activity for diverse reactions, opening a general pathway to the design of highly efficient and durable precious metal-based catalysts

Strategies for manipulating Rubisco and creating photorespiratory bypass to boost C3 photosynthesis : Prospects on modern crop improvement

Photosynthesis is a process that uses solar energy to fix CO2 in the air and converts it into sugar, and ultimately powers almost all life activities on the earth. C3 photosynthesis is the most common form of photosynthesis in crops. Current efforts of increasing crop yields in response to growing global food requirement are mostly focused on improving C3 photosynthesis. In this review, we summarized the strategies of C3 photosynthesis improvement in terms of Rubisco properties and photorespiratory limitation. Potential engineered targets include Rubisco subunits and their catalytic sites, Rubisco assembly chaperones, and Rubisco activase. In addition, we reviewed multiple photorespiratory bypasses built by strategies of synthetic biology to reduce the release of CO2 and ammonia and minimize energy consumption by photorespiration. The potential strategies are suggested to enhance C3 photosynthesis and boost crop production

Automated Detection and Characterization of Surface Restructuring Events in Bimetallic Catalysts

Surface restructuring in bimetallic systems has recently been shown to play a crucial role in heterogeneous catalysis. In particular, the segregation in binary alloys can be reversed in the presence of strongly bound adsorbates. Mechanistic characterization of such restructuring phenomena at the atomic level remains scarce and challenging due to the large configurational space that must be explored. To this end, we propose an automated method to discover elementary surface restructuring processes in an unbiased fashion, using Pd/Ag as an example. We employ high-temperature classical molecular dynamics (MD) to rapidly detect restructuring events, isolate them, and optimize using density functional theory (DFT). In addition to confirming the known exchange descent mechanism, our systematic approach has revealed three new predominant classes of events at step edges of close-packed surfaces that have not been considered before: (1) vacancy insertion; (2) direct exchange; (3) interlayer exchange. The discovered events enable us to construct the complete set of mechanistic pathways by which Pd is incorporated into the Ag host in vacuum. These atomistic insights provide a step toward systematic understanding and engineering of surface segregation dynamics in bimetallic catalysts.</div

LASSO-based machine learning algorithm to predict the incidence of diabetes in different stages

AbstractBackground Formal risk assessment is crucial for diabetes prevention. We aimed to establish a practical nomogram for predicting the risk incidence of prediabetes and prediabetes conversion to diabetes.Methods A cohort of 1428 subjects was collected to develop prediction models. The LASSO was used to screen for important risk factors in prediabetes and diabetes and was compared with other algorithms (LR, RF, SVM, LDA, NB, and Treebag). Multivariate logistic regression analysis was used to construct the prediction model of prediabetes and diabetes, and drawn the predictive nomogram. The performance of the nomograms was evaluated by receiver-operating characteristic curve and calibration.Results These findings revealed that the other six algorithms were not as good as LASSO in terms of diabetes risk prediction. The nomogram for individualized prediction of prediabetes included “Age,” “FH,” “Insulin_F,” “hypertension,” “Tgab,” “HDL-C,” “Proinsulin_F,” and “TG” and the nomogram of prediabetes to diabetes included “Age,” “FH,” “Proinsulin_E,” and “HDL-C”. The results showed that the two models had certain discrimination, with the AUC of 0.78 and 0.70, respectively. The calibration curve of the two models also indicated good consistency.Conclusions We established early warning models for prediabetes and diabetes, which can help identify prediabetes and diabetes high-risk populations in advance

Replication Data for: Automated Detection and Characterization of Surface Restructuring Events in Bimetallic Catalysts

The data underlying this published work have been made publicly available in this repository as part of the IMASC Data Management Plan. This work was supported as part of the Integrated Mesoscale Architectures for Sustainable Catalysis (IMASC), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences under Award # DE-SC0012573

Preparation of multiferroic lead iron niobate thin film with low crystallization temperature via sol-gel method using monoethanolamine

This study reports the synthesis of a multiferroic lead iron niobate (PbFe1/2Nb1/2O3, PFN) thin film with a low crystallization temperature using monoethanolamine (MEA) as a chelating agent via a sol-gel method. The results revealed that the presence of MEA led the Nb precursor to react at similar to 150 degrees C instead of 325-350 degrees C, thus indicating that the Nb precursor reacted first with the Fe precursor rather than the Pb precursor. Furthermore, X-ray diffraction patterns revealed that the addition of MEA allowed the PFN thin films to be sintered as a single phase at low temperatures (similar to 500 degrees C), while this can be only achieved at temperatures above 800 degrees C in the absence of MEA. The scanning electron microscope images revealed that the obtained PFN thin film was uniformly coated on the SiO2/Si substrate both in the absence and presence of MEA. Consequently, the presence of MEA can broaden the application scope of PFN thin films in photovoltaic devices

Predicting and Improving Interlaminar Bonding Uniformity during the Robotic Fiber Steering Process

With their high specific stiffness, corrosion resistance and other characteristics, especially their outstanding performance in product weight loss, fiber-reinforced resin matrix composites are widely used in the aviation, shipbuilding and automotive fields. The difficulties in minimizing defects are an important factor in the high cost of composite material component fabrication. Fiber steering is one of the typical means of producing composite parts with increased strength or stiffness. However, fiber waviness is an important defect induced by fiber steering during the fiber placement process. Meanwhile, the laying speeds of the inner and outer tows along the path width direction are different during the fiber steering process, resulting in different interlaminar bond strengths. Therefore, the fiber waviness and uneven interlaminar bonding strength during fiber steering not only affect the dimensions of a composite product, but also influence the mechanical properties of the part. This study aims to reduce fiber waviness and improve interlaminar bonding uniformity along the path width direction using a multi-piece compaction roller. By analyzing the mechanism of the generation of fiber waviness, the interlaminar bonding strength for each tow during fiber steering is investigated. Through analyzing and optimizing the compaction force, laying temperature and laying velocity during fiber steering experiments, the optimization approach is verified

Data underlying publication: Neglecting acclimation of photosynthesis under drought can cause significant errors in predicting leaf photosynthesis in wheat

This dataset contains leaf gas exchange and chlorophyll fluorescence data, leaf morphological data, and irrigation data collected in two experiments conducted in 2019 (EXP2019) and 2020 (EXP2020), at Wageningen University & Research, Wageningen, the Netherlands. The objective of this study was to investigate the response of leaf photosynthetic parameters to growth temperature and drought stress in winter wheat. Briefly, in EXP2019, two winter wheat (Triticum aestivum L.) genotypes, Thésée and Récital, were subjected to well-watered and drought treatments; in EXP2020 the two water regimes combined with high (HT), medium (MT) and low (LT) growth temperatures were imposed on Thésée. For the processes of data collection: firstly, irrigation data were collected once water stress treatment was imposed. Weight of each pot was measured by weighing pots daily. Secondly, gas exchange and chlorophyll fluorescence data were collected simultaneously by using a portable photosynthetic system (Li-Cor 6800; Li-Cor Inc., Lincoln, NE, USA) equipped with an integrated fluorescence chamber head of 6 cm2. Lastly, the portion of the flag leaves used for gas exchange and chlorophyll fluorescence measurements was cut to determine its area, weight (i.e., leaf morphological data), as well as leaf carbon and nitrogen concentrations