Enhanced Capacitive Deionization with Hollow Carbon Spheres Derived from Melamine–Formaldehyde Templates DOI
Wenting Ma, Haozhi Zhang,

Jia Fang

и другие.

ACS ES&T Water, Год журнала: 2024, Номер 4(9), С. 4218 - 4227

Опубликована: Авг. 27, 2024

The architectural configuration of an electrode material significantly impacts its capacitive deionization (CDI) performance, particularly due to the disparity in ion diffusion resistance between surface and core. To mitigate this disparity, a hollowing methodology was employed revamp conventional porous carbon spheres. Hierarchically hollow spheres (HCSs) were synthesized by thermal annealing phenol formaldehyde resin-coated melamine resin (MFSs) inert gas at 800 °C. advantage employing modified MFSs as templates lies their complete degradation during annealing, feature not observed with commercial polystyrene microspheres. Unlike mesoporous SiO2 microspheres which require additional hydrofluoric acid treatment, these do not. HCS-100 exhibited exceptional NaCl adsorption capacity, achieving salt capacity 25.20 mg g–1 rate 2.78 min–1 under working voltage 1.2 V. This performance demonstrated initial solution concentration 500 L–1, it maintained impressive stability over 70 cycles. results demonstrate that strategy is direct yet powerful way enhance CDI materials. utilization MFS template simplifies fabrication process, contributing overall effectiveness approach.

Язык: Английский

Tactics for boosting the desalination stability of capacitive deionization DOI
Hao Wang, Yong Liu, Yuquan Li

и другие.

Chemical Engineering Journal, Год журнала: 2024, Номер 496, С. 153808 - 153808

Опубликована: Июль 6, 2024

Язык: Английский

Процитировано

31

Machine Learning-Assisted High-Donor-Number Electrolyte Additive Screening toward Construction of Dendrite-Free Aqueous Zinc-Ion Batteries DOI
Haoran Luo, Qianzhi Gou, Yu Zheng

и другие.

ACS Nano, Год журнала: 2025, Номер unknown

Опубликована: Янв. 7, 2025

The utilization of electrolyte additives has been regarded as an efficient strategy to construct dendrite-free aqueous zinc-ion batteries (AZIBs). However, the blurry screening criteria and time-consuming experimental tests inevitably restrict application prospect additive strategy. With rise artificial intelligence technology, machine learning (ML) provides avenue promote upgrading energy storage devices. Herein, we proposed intriguing ML-assisted method accelerate development efficiency on AZIBs. Concretely, selected Gutmann donor number (DN value) a screen parameter, which can reflect interaction between solvent molecules ions, integrated ML model that predict DN values organic via molecular fingerprints, thereby achieving additives. Then, combined with theoretical calculations, influence law three different thermodynamic stability Zn anode its corresponding optimization mechanisms were revealed; are in positive correlation electrochemical performance anode. Especially, isopropyl alcohol (IPA) high value (36) various Zn-based cells presented superior performance, including calendar life (1500 h), stable Coulombic (99% within 450 cycles), favorable cycling retention. This work pioneers techniques for predicting additives, offering compelling investigation

Язык: Английский

Процитировано

9

Machine Learning Accelerated Discovery of Covalent Organic Frameworks for Environmental and Energy Applications DOI
Hao Wang, Yuquan Li, Xiaoyang Xuan

и другие.

Environmental Science & Technology, Год журнала: 2025, Номер unknown

Опубликована: Март 30, 2025

Covalent organic frameworks (COFs) are porous crystalline materials obtained by linking ligands covalently. Their high surface area and adjustable pore sizes make them ideal for a range of applications, including CO2 capture, CH4 storage, gas separation, catalysis, etc. Traditional methods material research, which mainly rely on manual experimentation, not particularly efficient, while with advancements in computer science, high-throughput computational screening based molecular simulation have become crucial discovery, yet they face limitations terms resources time. Currently, machine learning (ML) has emerged as transformative tool many fields, capable analyzing large data sets, identifying underlying patterns, predicting performance efficiently accurately. This approach, termed "materials genomics", combines ML to predict design high-performance materials, significantly speeding up the discovery process compared traditional methods. review discusses functions screening, design, prediction COFs highlights their applications across various domains like thereby providing new research directions enhancing understanding COF applications.

Язык: Английский

Процитировано

5

Advancement of capacitive deionization propelled by machine learning approach DOI
Hao Wang, Yuquan Li, Yong Liu

и другие.

Separation and Purification Technology, Год журнала: 2024, Номер 354, С. 129423 - 129423

Опубликована: Авг. 30, 2024

Язык: Английский

Процитировано

12

Tailoring the electrode material and structure of rocking-chair capacitive deionization for high-performance desalination DOI
Hao Wang, Yong Liu, Yuquan Li

и другие.

Materials Horizons, Год журнала: 2024, Номер 11(21), С. 5209 - 5219

Опубликована: Янв. 1, 2024

With the gradually increasing requirement for freshwater, capacitive deionization (CDI) as a burgeoning desalination technique has gained wide attention owing to its merits of easy operation, high efficiency, and environmental friendliness. To enhance performance CDI, different CDI architectures are designed, such membrane hybrid flow-electrode CDI. However, these systems have their own drawbacks, cost membranes, capacity limitation carbon materials slurry blockage, which severely limit practical application. Notably, rocking-chair (RCDI) composed symmetric electrode delivers excellent because special dual chamber structure, can not only break through limitations materials, but also deliver continuous process. Although RCDI showcases promise efficient desalination, few works systematically summarize advantages applications in field. This review offers thorough analysis RCDI, focusing on structure designs applications. Furthermore, performances other compared demonstrate prospect is elucidated.

Язык: Английский

Процитировано

7

Space-mediated confinement engineering of NaTi2(PO4)3 inside hollow carbon nanofibers via coaxial electrospinning: Enabling ultra-robust and highly-efficient faradic capacitive deionization DOI
Ziping Wang, Qianhui Ma,

Xuekairui Shen

и другие.

Separation and Purification Technology, Год журнала: 2025, Номер unknown, С. 131978 - 131978

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

1

Machine learning-based prediction of desalination capacity of electrochemical performance of nitrogen-doped for capacitive deionization DOI
Hao Kong, Ming Gao, Ran Li

и другие.

Desalination, Год журнала: 2025, Номер unknown, С. 118820 - 118820

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

1

Evaluation of machine learning applied in membrane-based water desalination: A review DOI
Yuanji Zhang, Jianxing He, Dongyang Li

и другие.

Desalination, Год журнала: 2025, Номер unknown, С. 119041 - 119041

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

1

Carbon-modified bentonite ion-exchange electrode in rocking-chair capacitive deionization with superior desalination capacity and high stability DOI
Hao Wang,

Yue Zhu,

Bin Hu

и другие.

Desalination, Год журнала: 2024, Номер 586, С. 117879 - 117879

Опубликована: Июнь 26, 2024

Язык: Английский

Процитировано

6

Marrying Fe nanoclusters with 3D carbon nanofiber aerogels: Triggering fast and robust faradic capacitive deionization DOI
Qianhui Ma, Ziping Wang, Lingyu Zhang

и другие.

Separation and Purification Technology, Год журнала: 2024, Номер 353, С. 128503 - 128503

Опубликована: Июнь 24, 2024

Язык: Английский

Процитировано

5