Semiconductor nanomaterials and nanostructured interfaces have important technological applications, ranging from fuel production to electrosynthesis. Their photocatalytic activity is known to be highly heterogeneous, both in an ensemble of nanomaterials and within a single entity. Photoelectrochemical imaging techniques are potentially useful for high-resolution mapping of photo(electro)catalytic active sites; however, the nanoscale spatial resolution required for such experiments has not yet been attained. In this article, we report photoreactivity imaging of two-dimensional MoS photocatalysts by two modes of photoscanning electrochemical microscopy (photo-SECM): diffusion and tunneling-based modes. Diffusion-based (feedback mode) photo-SECM is used to map the electron transfer and hydrogen evolution rates on mixed-phase MoS nanosheets and MoS chemical vapor deposition (CVD)-grown triangles. An extremely high resolution of photoelectrochemical imaging (about 1-2 nm) by the tunneling mode of the photo-SECM is demonstrated.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1021/acsnano.4c13276 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
EEG-to-EEG: Scalp-to-Intracranial EEG Translation Using a Combination of Variational Autoencoder and Generative Adversarial Networks.
Sensors (Basel)
January 2025
Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK.
A generative adversarial network (GAN) makes it possible to map a data sample from one domain to another one. It has extensively been employed in image-to-image and text-to image translation. We propose an EEG-to-EEG translation model to map the scalp-mounted EEG (scEEG) sensor signals to intracranial EEG (iEEG) sensor signals recorded by foramen ovale sensors inserted into the brain.
View Article and Find Full Text PDFFine-Grained Building Classification in Rural Areas Based on GF-7 Data.
Sensors (Basel)
January 2025
Bureau of Emergency Management of Pingquan City, Pingquan 067500, China.
Building type information is widely used in various fields, such as disaster management, urbanization studies, and population modelling. Few studies have been conducted on fine-grained building classification in rural areas using China's Gaofen-7 (GF-7) high-resolution stereo mapping satellite data. In this study, we employed a two-stage method combining supervised classification and unsupervised clustering to classify buildings in the rural area of Pingquan, northern China, based on building footprints, building heights, and multispectral information extracted from GF-7 data.
View Article and Find Full Text PDFStructure-Based Approaches for Protein-Protein Interaction Prediction Using Machine Learning and Deep Learning.
Biomolecules
January 2025
Institute of Chemical Biology, National Hellenic Research Foundation, 11635 Athens, Greece.
Protein-Protein Interaction (PPI) prediction plays a pivotal role in understanding cellular processes and uncovering molecular mechanisms underlying health and disease. Structure-based PPI prediction has emerged as a robust alternative to sequence-based methods, offering greater biological accuracy by integrating three-dimensional spatial and biochemical features. This work summarizes the recent advances in computational approaches leveraging protein structure information for PPI prediction, focusing on machine learning (ML) and deep learning (DL) techniques.
View Article and Find Full Text PDFHigh-resolution spatially resolved proteomics of complex tissues based on microfluidics and transfer learning.
Cell
January 2025
Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Key Laboratory of Systems Biology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, China; University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address:
Despite recent advances in imaging- and antibody-based methods, achieving in-depth, high-resolution protein mapping across entire tissues remains a significant challenge in spatial proteomics. Here, we present parallel-flow projection and transfer learning across omics data (PLATO), an integrated framework combining microfluidics with deep learning to enable high-resolution mapping of thousands of proteins in whole tissue sections. We validated the PLATO framework by profiling the spatial proteome of the mouse cerebellum, identifying 2,564 protein groups in a single run.
View Article and Find Full Text PDFWar-induced soil disturbances in north-eastern Ukraine (Kharkiv region): Physical disturbances, soil contamination and land use change.
Sci Total Environ
January 2025
NGO "Ukrainian Researchers Society", Ukraine; Institute of Geography of National Academy of Sciences of Ukraine, Ukraine.
The war in Ukraine is having a dramatic impact on the physical, chemical and biological soil properties. A comprehensive study of the war-affected soils during the ongoing war is a challenging task owing to the many constrains that arise during fieldworks. Remote sensing data is the best solution for overall analysis of physical soil disturbances.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!