Dynamics of Chemical Degradation in Water Using Photocatalytic Reactions in an Ultraviolet Light Emitting Diode Reactor

Abstract

This work examined ultraviolet (UV) light emitting diodes (LED) and hydrogen peroxide in an advanced oxidation process in support of a USAF installation net zero water initiative. A UV LED reactor was used for degradation of soluble organic chemicals. There were linear relationships between input drive current, optical output power, and first order degradation rate constants. When drive current was varied, first order degradation rates depended on chemical identities and the drive current. When molar peroxide ratios were varied, kinetic profiles revealed peroxide-limited or radical-scavenged phenomena. Molar absorptivity helped explain the complexity of chemical removal profiles. Degradation kinetics were used to compare fit of molecular descriptors from published quantitative structure property relationship (QSPR) models. A novel QSPR model was built using zero point energy and molar absorptivity as predictors. Finally, a systems architecture was used to describe a net zero water program and proposed areas for UV LED reactor integration. Facility-level wastewater treatment was found to be the most feasible near-term application.

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Document Details

Document Type
Technical Report
Publication Date
Sep 14, 2017
Accession Number
AD1051600

Entities

People

  • John E. Stubbs

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies
  • Engineered Resilient Systems
  • Sensors

DTIC Thesaurus Topics

  • Chemical Analysis
  • Chemical Compounds
  • Chemical Engineering
  • Chemical Kinetics
  • Chemical Synthesis
  • Chemistry
  • Climate Change Adaptation
  • Ecotoxicology
  • Groundwater
  • Health Services
  • Liquid Chromatography
  • Mass Spectrometry
  • Medical Personnel
  • Metallic Nanoparticles
  • Organic Chemistry
  • Water Purification

Fields of Study

  • Environmental science

Readers

  • Computational Modeling and Simulation
  • Organic Chemistry
  • Spectroscopy.