For photoelectrocatalytic cells, a limitation exists in finding appropriate photoelectrode configurations that couple efficient extraction of high-energy electrons from absorbed photons and selective catalysis. Here we report an organic p-n junction approach to fabricate molecular photoelectrodes for conversion of solar energy and nitrate into valuable ammonia product. Solar irradiation of the photoelectrode generates charge-separated states with electrons and holes spatially separated at the n-type and p-type components, as revealed by surface photovoltage mapping, at a quantum yield of 90 %. The high-flux photogenerated electrons are rapidly transferred to the catalyst for solar ammonia production from nitrate reduction at an external quantum efficiency (EQE) and an internal quantum efficiency (IQE) of 57 % and 86 %, respectively. Time-resolved spectroscopic studies reveal that the large IQE originates from the combined high efficiencies for photoelectron generation, catalyst activation and dark catalysis. In a flow-cell setup coupled with a silicon solar cell, the photoelectrode without bias generates photocurrent of 57 mA cm and ammonia at an EQE of 52 %.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1002/anie.202415729 | DOI Listing |
ChemSusChem
January 2025
CSIR Central Glass & Ceramic Research Institute, EMDD, 196 Raja S C Mullick Road, 700032, Kolkata, INDIA.
The advancement of photocatalytic technology for solar-driven hydrogen (H2) production remains hindered by several challenges in developing efficient photocatalysts. A key issue is the rapid recombination of charge carriers, which significantly limits the light-harvesting ability of materials like BiOCl and Cu2SnS3 quantum dots (CTS QDs), despite the faster charge mobility and quantum confinement effect, respectively. Herein, a BiOCl/CTS (BCTS) heterostructure was synthesized by loading CTS QDs onto BiOCl 2D nanosheets (NSs), that demonstrated excellent photocatalytic activity under visible light irradiation.
View Article and Find Full Text PDFNat Commun
January 2025
Key Laboratory of Quantum Materials and Devices of Ministry of Education, School of Physics, Southeast University, Nanjing, 21189, China.
Directly generating material structures with optimal properties is a long-standing goal in material design. Traditional generative models often struggle to efficiently explore the global chemical space, limiting their utility to localized space. Here, we present a framework named Material Generation with Efficient Global Chemical Space Search (MAGECS) that addresses this challenge by integrating the bird swarm algorithm and supervised graph neural networks, enabling effective navigation of generative models in the immense chemical space towards materials with target properties.
View Article and Find Full Text PDFJ Colloid Interface Sci
January 2025
State Key Laboratory of Bio-Fibers and Eco-Textiles, Qingdao University, No. 308 Ningxia Road, Qingdao 266071 PR China. Electronic address:
Luminescent solar concentrators (LSCs) are large scale sunlight collector and can be used for building-integrated photovoltaics (BIPV). Achieving high-performance LSCs requires fluorophores with broad absorption, high quantum yield and a large Stokes shift. Nevertheless, conventional high-efficiency LSCs typically rely on heavy metal-based quantum dots as fluorophores.
View Article and Find Full Text PDFComput Biol Med
January 2025
College of Electronic Information, Xijing University, Xi'an, China. Electronic address:
Accurate and efficient drug-drug interaction extraction (DDIE) from the medical corpus is essential for pharmacovigilance, drug therapy and drug development. To solve the problems of unbalance dataset and lack of accurate manual annotations in DDIE, a cross-attention guided Siamese quantum BiGRU (CA-SQBG) is constructed to improve feature representation learning ability for DDIE. It mainly consists of two quantum BiGRUs (QBiGRUs) and a cross-attention, where two QBiGRUs are Siamese implemented in a variational quantum environment to learn the contextual semantic feature representation of drug pairs, cross-attention is employed to learn mutual information from the Siamese QBiGRUs, which in turn allows the two modules to extract DDI more collaboratively.
View Article and Find Full Text PDFLight Sci Appl
January 2025
National Research Center for High-Efficiency Grinding, College of Mechanical and Vehicle Engineering, Hunan University, 410082, Changsha, China.
Accurately and swiftly characterizing the state of polarization (SoP) of complex structured light is crucial in the realms of classical and quantum optics. Conventional strategies for detecting SoP, which typically involves a sequence of cascaded optical elements, are bulky, complex, and run counter to miniaturization and integration. While metasurface-enabled polarimetry has emerged to overcome these limitations, its functionality predominantly remains confined to identifying SoP within the standard Poincaré sphere framework.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!