In Situ MXene Anchored Structure for Highly Durable Solar Steam Generation

Jin Yan,Haoran Kong,Yuting Li,Qinhuan Wang,Xiang Liu,Yu Wang

Nano Letters（2024）SCI 1区SCI 2区

Cited 0|Views26

Abstract

As a promising fresh water harvesting technology, interfacial solar steam generation has attracted growing interest. Efficient solar absorption and long-term operational performance are critical requirements of this technology. However, developing robust evaporators to promote practical applications under extreme conditions is still a grand challenge. Herein, we propose a light-assisted strategy to in situ prepare a Ti3C2Tx MXene anchored structure (MXAS) for enhanced solar evaporation with superior mechanical properties (compressive strength of 78.47 MPa, which can withstand a pressure of 3.92 x 10(6) times its own weight). Light irradiation enlarges the interlayer spacing of MXene and improves the solar absorption capability. Under one sun, the three-dimensional MXAS evaporator exhibits a steam generation rate of 2.48 kg m(-2) h(-1)and an evaporation efficiency of 89.3%, and it demonstrates long-term durability when testing in seawater. This strategy provides valuable insights into the potential application of a high-performance water evaporation system.

Translated text

Key words

in situ MXene anchored structure,compressive strength,electrochemistry,solar evaporator,desalinization

求助PDF

上传PDF

Bibtex

AI Read Science

AI Summary

AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.

Example

Background

Key content

Introduction

Methods

Results

Related work

Fund

Key content

Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

Upload PDF to Generate Summary

Must-Reading Tree

Example

Generate MRT to find the research sequence of this paper