{"doi":"10.17760/d20659746","title":"Simulation of contaminant redox and removal in flow-through electrochemical water treatment systems","abstract":"This study is focused on developing models for the simulation of redox condition in flow-through electrochemical reactors for transformation and removal of contaminants from water. Two models are discussed in this study: (1) electrocoagulation (EC) model for hexavalent chromium reduction and precipitation, using iron electrodes, and (2) electrochemical generation of hydrogen peroxide for removal of trichloroethene (TCE).In electrocoagulation systems ferrous iron species are introduced into the electrolyte using iron anodic dissolution, inducing reduction of chromium by the resulting alteration of the redox potential in the electrolyte. The electrochemical process relies upon the redox reactions taking place at the surface of the conductive electrodes as a voltage gradient is applied. However, the iron passivation effect often reduces the efficiency of the electrode dissolution, hence the chromium removal. The reaction model presented for the batch system represents species complexation, precipitation/dissolution, acid/base, and oxidation-reduction reactions. Electrochemical reactions induced by a constant current are assumed parallel for oxide layer formation and dissolved iron release. Batch reactor simulation is verified using experimental data, where the effect of initial chromium concentration, pH, volumetric current density, and ionic strength is considered. Design parameters are presented for the operation of a flow-through hexavalent chromium removal using electrocoagulation by iron electrode to treat Cr(VI) in the range of 10-50 mg/l. In the electrochemical generation of hydrogen peroxide, the model considers parallel competing 2-e and 4-e oxygen reduction reactions (ORRs). The parallel electrode reactions can occur invariably to different extents which dynamically changes throughout the remediation process and controls the removal efficacy of TCE. The optimal operational parameters of such systems are operational conditions that would result in the limiting current condition when the concentration of the limiting reactive species is zero at the electrode/electrolyte interface. The model assumes (1) the batch bulk electrolyte is completely stirred with no concentration variation, (2) stagnant film theory is applied at the cathode surface, where the diffusion layer has no advective velocity. The boundary conditions at the electrode/electrolyte interface are developed using the partial current densities of the electrochemical reactions. Electrode reactions are modeled considering two steps: (1) transfer of species from bulk electrolyte to the electrode surface, (2) chemical and physical transformations on the electrode surface. Mass transfer between the bulk and electrode/electrolyte interface (i.e. stern layer) can be considered by diffusion and ion migration due to concentration and potential gradient, respectively. Under the assumption of constant stirring in operation of the cell at different current intensities, increasing the current intensity, results in higher H_2 O_2 accumulation in the cell. However, increasing the double layer thickness hinders the transport of species between the electrode surface and bulk electrolyte. The model determines the current efficiency of hydrogen peroxide electro-generation as a function of applied current density or applied potential at galvanostatic and potentiostatic systems, respectively.--Author's abstract","journal":null,"year":2024,"id":497570,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9463,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1344477,"name":"Shayan Hojabri Fouladizadeh","orcid":null,"position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-19T02:09:34.764412Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}