Tactics for boosting the desalination stability of capacitive deionization

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

Опубликована: Июль 6, 2024

Язык: Английский

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Machine Learning‐Guided Prediction of Desalination Capacity and Rate of Porous Carbons for Capacitive Deionization

Small, Год журнала: 2024, Номер unknown

Опубликована: Июнь 17, 2024

Abstract Nowadays, capacitive deionization (CDI) has emerged as a prominent technology in the desalination field, typically utilizing porous carbons electrodes. However, precise significance of electrode properties and operational conditions shaping performance remains blurry, necessitating numerous time‐consuming resource‐intensive CDI experiments. Machine learning (ML) presents an emerging solution, offering prospect predicting with minimal investment material synthesis testing. Herein, four ML models are used for carbons. Among them, gradient boosting model delivers best on test set low root mean square error values 2.13 mg g −1 0.073 min capacity rate, respectively. Furthermore, SHapley Additive exPlanations is introduced to analyze conditions. It highlights that electrolyte concentration specific surface area exert substantially more influential role determining compared other features. Ultimately, experimental validation employing metal–organic frameworks‐derived biomass‐derived electrodes conducted affirm prediction accuracy models. This study pioneers techniques performance, compelling strategy advancing technology.

Язык: Английский

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Work-function-prompted interfacial charge kinetics in hierarchical heterojunction flexible electrode for efficient capacitive deionization

Separation and Purification Technology, Год журнала: 2024, Номер 347, С. 127563 - 127563

Опубликована: Апрель 18, 2024

Язык: Английский

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High‐Efficiency Electrochemical Desalination: The Role of a Rigid Pseudocapacitive Polymer Electrode with Diverse Active Sites

Advanced Functional Materials, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 12, 2024

Abstract Hybrid capacitive deionization (HCDI) emerges as a burgeoning electrochemical desalination technology due to the utilization of profitable pseudocapacitive reactions. Although tunable organic compounds are potential faradaic electrode materials, their insufficient active sites and high water‐solubility restrict practical HCDI applications. Herein, polymer (PNDS) is proposed with diverse redox‐active for deionization. The pronounced molecular aromaticity strong π‐electron delocalization not only endow PNDS framework rigidity, but refine its electronic structure bolster redox activity electron affinity. As an material, demonstrates substantial capacitance 390 F g −1 sustains long‐term stability at 96.3% after 5000 cycles, surpassing reported Na + ‐capturing electrodes. In‐operando monitoring techniques theoretical calculations reveal efficient capture C═N C═O within during repeated electrosorption processes. conceptual demonstration, high‐performance device equipped exhibits impressive salt removal capacity (66.4 mg ), rapid rate (2.2 min ) stable regeneration property. More importantly, integrated system engineered rapidly repeatedly treat saltwater resources human consumption agricultural irrigation, highlighting promising prospects high‐efficiency

Язык: Английский

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Machine Learning Accelerated Discovery of Covalent Organic Frameworks for Environmental and Energy Applications

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

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Unveiling the neglected role of oxygen doping in nitrogen-doped carbon for enhanced capacitive deionization performance

Nature Communications, Год журнала: 2025, Номер 16(1)

Опубликована: Фев. 26, 2025

Nitrogen-doped carbons (NCs) have demonstrated notable advantages for application in capacitive deionization (CDI). However, the potential roles of different nitrogen configurations CDI process, especially how neglected oxygen doping synergistically works, remain unclear. In this work, we systematically addressed these critical issues and revealed significant role trace enhancing desalination performance NC electrodes. By introducing into nitrogen-doped carbon nanosheets (ONC-S), using guanine as precursor, obtained abundant pyridinic pyrrolic configurations. This design aims to enhance charge distribution, wettability, ion diffusion target Compared with commercial activated other state-of-the-art materials, our ONC-S electrode demonstrates superior specific capacitance, excellent cycling stability, enhanced efficiency. These findings highlight synergistic effects configuration, offering valuable insights mechanisms driving improved performance. shown applications, but effect Here, study addresses reveals crucial impact

Язык: Английский

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Pseudo-capacitive behaviors induced dual-ion selective deionization system based on MoS2/PPy//Ag@PANI/AC

Separation and Purification Technology, Год журнала: 2025, Номер unknown, С. 131906 - 131906

Опубликована: Фев. 1, 2025

Язык: Английский

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Ultrafine molybdenum carbide nanocrystals into three-dimensional nitrogen-doped carbon framework for capacitive deionization: with metal-organic framework as a template

Chemical Science, Год журнала: 2024, Номер 15(29), С. 11540 - 11549

Опубликована: Янв. 1, 2024

Ultrafine MoC nanocrystals are confined within the MOF-derived NC matrix to generating NC/MoC. The NC/MoC based electrode achieves high CDI performance.

Язык: Английский

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Enabling High Capacity and Stable Sodium Capture in Simulated Saltwater by Highly Crystalline Prussian Blue Analogues Cathode

Small Structures, Год журнала: 2024, Номер unknown

Опубликована: Июнь 10, 2024

Prussian blue analogues (PBAs) are considered as promising cathode materials for capacitive deionization (CDI) technology due to their 3D open‐frame structure and tunable redox active sites. However, the inevitably high content of [Fe(CN) 6 ] vacancies in crystal results a low salt adsorption capacity (SAC) poor recycling performance. Herein, high‐salt nano‐reaction system is established by mechanochemical ball milling, enabling preparation variety highly crystallized PBAs (metal hexacyanoferrate, MHCF‐B‐170, M = Ni, Co, or Cu) with (0.05–0.06 per formula unit). The reduction lattice not only strengthens conductivity promotes rapid transfer electrons, but also reduces migration energy barrier accelerates fast reversible diffusion Na + ions. structural characterization method theoretical simulation demonstrates excellent reversibility stability MHCF‐B‐170 during CDI process. Impressively, NiHCF‐B‐170 exhibits performance, characterized an exceptionally SAC up 101.4 mg g −1 at 1.2 V, remarkable cycle no significant degradation observed even after 100 cycles. This Fe(CN) expected be competitive candidate material electrodes.

Язык: Английский

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Advancement of capacitive deionization propelled by machine learning approach

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

Опубликована: Авг. 30, 2024

Язык: Английский

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