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Hydrodechlorination of TCE in a circulated electrolytic column at high flow rate.

ABSTRACT: Palladium-catalytic hydrodechlorination of trichloroethylene (TCE) by cathodic H2 produced from water electrolysis has been tested. For a field in-well application, the flow rate is generally high. In this study, the performance of Pd-catalytic hydrodechlorination of TCE using cathodic H2 is evaluated under high flow rate (1 L min(-1)) in a circulated column system, as expected to occur in practice. An iron anode supports reduction conditions and it is used to enhance TCE hydrodechlorination. However, the precipitation occurs and high flow rate was evaluated to minimize its adverse effects on the process (electrode coverage, clogging, etc.). Under the conditions of 1 L min(-1) flow, 500 mA current, and 5 mg L(-1) initial TCE concentration, removal efficacy using iron anodes (96%) is significantly higher than by mixed metal oxide (MMO) anodes (66%). Two types of cathodes (MMO and copper foam) in the presence of Pd/Al2O3 catalyst under various currents (250, 125, and 62 mA) were used to evaluate the effect of cathode materials on TCE removal efficacy. The similar removal efficiencies were achieved for both cathodes, but more precipitation generated with copper foam cathode (based on the experiments done by authors). In addition to the well-known parameters such as current density, electrode materials, and initial TCE concentration, the high velocities of groundwater flow can have important implications, practically in relation to the flush out of precipitates. For potential field application, a cost-effective and sustainable in situ electrochemical process using a solar panel as power supply is being evaluated.

SUBMITTER: Fallahpour N

PROVIDER: S-EPMC4695317 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Hydrodechlorination of TCE in a circulated electrolytic column at high flow rate.

Fallahpour Noushin N Yuan Songhu S Rajic Ljiljana L Alshawabkeh Akram N AN

Chemosphere 20150905

Palladium-catalytic hydrodechlorination of trichloroethylene (TCE) by cathodic H2 produced from water electrolysis has been tested. For a field in-well application, the flow rate is generally high. In this study, the performance of Pd-catalytic hydrodechlorination of TCE using cathodic H2 is evaluated under high flow rate (1 L min(-1)) in a circulated column system, as expected to occur in practice. An iron anode supports reduction conditions and it is used to enhance TCE hydrodechlorination. Ho ...[more]

PMID: 26344148

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Project description:Background: High flow nasal cannula (HFNC) is commonly used as non-invasive respiratory support in critically ill children. There are limited data to inform consensus on optimal device parameters, determinants of successful patient response, and indications for escalation of support. Clinical scores, such as the respiratory rate-oxygenation (ROX) index, have been described as a means to predict HFNC non-response, but are limited to evaluating for escalations to invasive mechanical ventilation (MV). In the presence of apparent HFNC non-response, a clinician may choose to increase the HFNC flow rate to hypothetically prevent further respiratory deterioration, transition to an alternative non-invasive interface, or intubation for MV. To date, no models have been assessed to predict subsequent escalations of HFNC flow rates after HFNC initiation. Objective: To evaluate the abilities of tree-based machine learning algorithms to predict HFNC flow rate escalations. Methods: We performed a retrospective, cohort study assessing children admitted for acute respiratory failure under 24 months of age placed on HFNC in the Johns Hopkins Children's Center pediatric intensive care unit from January 2019 through January 2020. We excluded encounters with gaps in recorded clinical data, encounters in which MV treatment occurred prior to HFNC, and cases electively intubated in the operating room. The primary study outcome was discriminatory capacity of generated machine learning algorithms to predict HFNC flow rate escalations as compared to each other and ROX indices using area under the receiver operating characteristic (AUROC) analyses. In an exploratory fashion, model feature importance rankings were assessed by comparing Shapley values. Results: Our gradient boosting model with a time window of 8 h and lead time of 1 h before HFNC flow rate escalation achieved an AUROC with a 95% confidence interval of 0.810 ± 0.003. In comparison, the ROX index achieved an AUROC of 0.525 ± 0.000. Conclusion: In this single-center, retrospective cohort study assessing children under 24 months of age receiving HFNC for acute respiratory failure, tree-based machine learning models outperformed the ROX index in predicting subsequent flow rate escalations. Further validation studies are needed to ensure generalizability for bedside application.

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Hydrodechlorination of TCE in a circulated electrolytic column at high flow rate.

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Hydrodechlorination of TCE in a circulated electrolytic column at high flow rate.

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