Knowledge and Technology Used in Capacitive Deionization of Water

Empowering Capacitive Devices: Harnessing Transfer Learning for Enhanced Data-Driven Optimization

Developing data-driven models has found successful applications in engineering tasks, such as material design, process modeling, and process monitoring. In capacitive devices like deionization and supercapacitors, there exists potential for applying this data-driven machine learning (ML) model in optimizing its potential use in energy-efficient separations or energy generation. However, these models are faced with limited datasets, and even in large quantities, the datasets are incomplete, limiting their potential use for successful data-driven modeling. Here, the success of transfer learning in resolving the challenges with limited datasets was exploited. A two-step data-driven ML modeling framework named ImputeNet involving training with ML-imputed datasets and then with clean datasets was explored. Through data imputation and transfer learning, it is possible to develop a data-driven model with acceptable metrics mirroring experimental measurements. By using the model, optimization studies using the genetic algorithm were implemented to analyze the solution under the Pareto optimality. This early insight can be used in the initial stage of experimental measurements to rapidly identify experimental conditions worthy of further investigation. Moreover, we expect that the insights from these results will drive accurate predictive modeling in other fields including healthcare, genomic data analysis, and environmental monitoring with incomplete datasets.

Development of Composite Nanostructured Electrodes for Water Desalination via Membrane Capacitive Deionization

Novel two-layer nanostructured electrodes are successfully prepared for their application in membrane capacitive deionization (MCDI) processes. Nanostructured carbonaceous materials such as graphene oxide (GO) and carbon nanotubes (CNTs), as well as activated carbon (AC) are dispersed in a solution of poly(vinyl alcohol) (PVA), mixed with polyacrylic acid (PAA) or polydimethyldiallylammonium chloride (PDMDAAC), and subsequently cast on the top surface of an AC-based modified graphite electrode to form a thin composite layer that is cross-linked with glutaraldehyde (GA). Cyclic voltammetry (CV) is performed to investigate the electrochemical properties of the composite electrodes and desalination experiments are conducted in batch mode using a MCDI unit cell to investigate the effects of i) the nanostructured carbonaceous material, ii) its concentration in the polymer blend, and iii) the molecular weight of the polymers on the desalination efficiency of the system. Comparative studies with commercial membranes are performed proving that the composite nanostructured electrodes are more efficient in salt removal. The improved performance of the composite electrodes is attributed to the ion exchange properties of the selected polymers and the increased specific capacitance of the nanostructured carbonaceous materials. This research paves the way for wider application of MCDI in water desalination.

Optimizing the Micro/Mesoporous Structure of Hierarchical Porous Carbon Synthesized from Petroleum Pitch Using the Solvent-Free Method for Ultra-Fast Capacitive Deionization

In this work, a solvent-free ZnO-template method is used to synthesize hierarchical porous carbons (denoted as HPC-X; X = 1, 1.5, 2, and 4 g of ZnO) via the pyrolysis of petroleum industrial-residual pitch with ZnO. The proposed method allows precise control of the micro/meso/macroporous structure of the HPC by adjusting the amount of ZnO. The results show that the average pore size of HPCs prominently increases from 2.4 to 3.7 nm with the increase in the ZnO/pitch ratio. In addition, it is shown that HPCs have a high surface area between 1141 and 1469 m² g^-1, a wide-range pore size distribution (micro-, meso-, and macropores), and a tap density ranging from 0.2 to 0.57 g cm^-3. The capacitive deionization performances of HPCs for sodium and chloride ions are investigated. The results show that HPC-2 exhibits the highest electrosorption capacity of 9.94 mg g^-1 within 10.0 min and a maximum electrosorption capacity of 10.62 mg g^-1 at 1.2 V in a 5.0 mM NaCl solution. Hence, HPC-2 is a highly promising candidate as an electrode material for rapid deionization.

Recent Progresses in Adsorption Mechanism, Architectures, Electrode Materials and Applications for Advanced Electrosorption System: A Review

As an advanced strategy for water treatment, electrosorb technology has attracted extensive attention in the fields of seawater desalination and water pollution treatment due to the advantages of low consumption, environmental protection, simplicity and easy regeneration. In this work, the related adsorption mechanism, primary architectures, electrode materials, and applications of different electrosorption systems were reviewed. In addition, the developments for advanced electrosorb technology were also summarized and prospected.