Environmental energy enhanced solar-driven evaporator with spontaneous internal convection for highly efficient water purification.

Water Res

Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Ministry of Education, College of Environment, Hohai University, No.1, Xikang road, Nanjing 210098, China. Electronic address:

Published: October 2023

Solar-driven interfacial evaporation for water purification is limited by the structural design of the solar evaporator and, more importantly, by the inability to separate the water from volatile organic compounds (VOCs) present in the water source. Here, we report a three-dimensional (3D) bifunctional evaporator based on N-doped carbon (CoNC/CF), which enables the separation of fresh water from VOCs by activating PMS during the evaporation process with a VOC removal rate of 99%. There is abundant van der Waals interaction between peroxymonosulfate (PMS) and CoNC/CF, and pyrrolic N is confirmed as the active site for binding phenol, thus contributing to the separation of phenol from water. With the advantageous features of sufficient light absorption, adequate water storage capacity, and spontaneous internal convection flow on its top surface, the 3D evaporator achieves a high evaporation rate under one sun (1 kW/m) at 3.16 kg/m/h. More notably, through careful structural design, additional energy from the environment and water can be utilized. With such a high evaporation rate and satisfactory purification performance, this work is expected to provide a promising platform for wastewater treatment.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.watres.2023.120514DOI Listing

Publication Analysis

Top Keywords

spontaneous internal
8
internal convection
8
water
8
water purification
8
structural design
8
high evaporation
8
evaporation rate
8
environmental energy
4
energy enhanced
4
enhanced solar-driven
4

Similar Publications

Caloric depletion leads to behavioral changes that help an animal find food and restore its homeostatic balance. Hunger increases exploration and risk-taking behavior, allowing an animal to forage for food despite risks; however, the neural circuitry underlying this change is unknown. Here, we characterize how hunger restructures an animal's spontaneous behavior as well as its directed exploration of a novel object.

View Article and Find Full Text PDF

Background: Atrial fibrillation (AF) is rare during pregnancy and current data on the impact of AF during delivery is scarce. In this study, we aim to analyze the impact of AF in patients who underwent delivery via cesarean section (CS), natural spontaneous delivery (NSD), or instrumental delivery (ID).

Methods: This study analyzed discharge data from the National Inpatient Sample (NIS) from 2016 to 2020.

View Article and Find Full Text PDF

Background: Serpentine supravenous hyperpigmentation (SSH) is known as a phenomenon occurring during the infusion of chemotherapy agents in the underlying veins. Chemotherapy agents have potential to cause infusion reactions when used systematically. Linear hyperpigmentation and reticular hyperpigmentation are the differential diagnosis for this phenomenon.

View Article and Find Full Text PDF

The ability to coactivate (or "superpose") multiple conceptual representations is a fundamental function that we constantly rely upon; this is crucial in complex cognitive tasks requiring multi-item working memory, such as mental arithmetic, abstract reasoning, and language comprehension. As such, an artificial system aspiring to implement any of these aspects of general intelligence should be able to support this operation. I argue here that standard, feed-forward deep neural networks (DNNs) are unable to implement this function, whereas an alternative, fully brain-constrained class of neural architectures spontaneously exhibits it.

View Article and Find Full Text PDF

Electroencephalography (EEG) provides high temporal resolution neural data for brain-computer interfacing via noninvasive electrophysiological recording. Estimating the internal brain activity by means of source imaging techniques can further improve the spatial resolution of EEG and enhance the reliability of neural decoding and brain-computer interaction. In this work, we propose a novel EEG data-driven source imaging scheme for precise and efficient estimation of macroscale spatiotemporal brain dynamics across thalamus and cortical regions with deep learning methods.

View Article and Find Full Text PDF

Want 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!