The experimental high-throughput (HT) exploration for a suitable solar water splitting photoanode has greatly relied on photoactivity as the sole descriptor to identify a promising region within the searched composition space. Although activity is essential, it is not sufficient for describing the overall performance and excludes other pertinent criteria for photoelectrochemical (PEC) water splitting. Photostability in the form of (photo)electrocatalyst dissolution must be tracked to illustrate the intricate relation between activity and stability for multinary photoelectrocatalysts. To access these two important metrics simultaneously, an automated PEC scanning flow cell coupled to an inductively coupled plasma mass spectrometer (PEC-ICP-MS) was used to study an Fe-Ti-W-O thin film materials library. The results reveal an interrelation between composition, photocurrent density, and element-specific dissolution. These structure-activity-stability correlations can be represented using data science tools like principal component analysis (PCA) in addition to common data visualization approaches. This study demonstrates the importance of addressing two of the most important catalyst metrics (activity and stability) in a rapid and parallel fashion during HT experiments to adequately discover high-performing compositions in the multidimensional search space.
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http://dx.doi.org/10.1039/d2sc05115j | DOI Listing |
Sci Rep
December 2024
College of Economics and Management, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
In light of the Chinese government's dual carbon goals, achieving cleaner production activities has become a central focus, with regional environmental collaborative governance, including the management of agricultural carbon reduction, emerging as a mainstream approach. This study examines 268 prefecture-level cities in China, measuring the carbon emission efficiency of city agriculture from 2001 to 2022. By integrating social network analysis and a modified gravity model, the study reveals the characteristics of the spatial association network of city agricultural carbon emission efficiency in China.
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December 2024
Department of Clinical Pharmacy, Baoshan Hospital Affiliated to, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
This study investigates the potential treatment of breast cancer utilizing Gentiana robusta King ex Hook. f. (QJ) through an integrated approach involving network pharmacology, molecular docking, and molecular dynamics simulation.
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December 2024
State Key Laboratory of Digital Medical Engineering, Southeast University, Nanjing, 210096, China.
Microelectrode arrays (MEAs) have been widely used in studies on the electrophysiological features of neuronal networks. In classic MEA experiments, spike or burst rates and spike waveforms are the primary characteristics used to evaluate the neuronal network excitability. Here, we introduced a new method to assess the excitability using the voltage threshold of electrical stimulation.
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December 2024
Bioinformatics Laboratory, College of Computing, University Mohammed VI Polytechnic, Ben Guerir, Morocco.
Hepatitis C virus (HCV) presents a significant global health issue due to its widespread prevalence and the absence of a reliable vaccine for prevention. While significant progress has been achieved in therapeutic interventions since the disease was first identified, its resurgence underscores the need for innovative strategies to combat it. The nonstructural protein NS5A is crucial in the life cycle of the HCV, serving as a significant factor in both viral replication and assembly processes.
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December 2024
School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, Australia.
Sponges harbour complex microbiomes and as ancient metazoans and important ecosystem players are emerging as powerful models to understand the evolution and ecology of symbiotic interactions. Metagenomic studies have previously described the functional features of sponge symbionts, however, little is known about the metabolic interactions and processes that occur under different environmental conditions. To address this issue, we construct here constraint-based, genome-scale metabolic networks for the microbiome of the sponge Stylissa sp.
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