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Electrochemistry (surface engineering) PhD Projects, Programs & Scholarships

We have 10 Electrochemistry (surface engineering) PhD Projects, Programs & Scholarships

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  Carbon foams and hydrogen from zero emission fossil fuels
  Dr N Bimbo, Dr R Dawson
Applications accepted all year round

Funding Type

PhD Type

A four-year fully funded PhD studentship for UK/EU citizens is available at the Leverhulme Doctoral Training Centre for Materials Social Futures to start in October 2020.
  Simulation Modelling of Distortion and Shrinkage in Stereolithography 3D Printing.
  Dr E Sabet
Applications accepted all year round

Funding Type

PhD Type

This project offers a chance to work on a truly disruptive and innovative research project in the high-tech and high-value manufacturing, with very high potential impact in aerospace and energy sectors.
  Modelling the effect of the electric double layer on electron transfer kinetics
  Dr L Lue
Applications accepted all year round

Funding Type

PhD Type

Electron transfer between molecules in solution and a surface (e.g., a metallic electrode or semiconducting substrate) occurs in a wide variety of important areas, including catalysis, corrosion, electrodeposition, photochemistry, etc.
  Investigating the Causal Biological Effects on Microbial Induced Corrosion (MIC) Occurring Within Components of Advanced Maritime Systems
  Dr B Connolly
Applications accepted all year round

Funding Type

PhD Type

Applications are invited for a full time PhD studentship in the Department of Materials at the University of Manchester. The project is supported by BAE Systems, who will provide both industrial supervision, access to research facilities and secondments during the studentship.
  High Power Renewable Energy Nano Catalysis – Fundamental and Applied Electrochemistry
  Prof A Schechter
Applications accepted all year round

Funding Type

PhD Type

The development of a low-cost, high-performance fuel cell is hindered by the lack of an active and electrocatalysts at the anode and cathode.
  Bacteria Recognition-Extraction from Wastewater (BREW) for next generation Microbial Fuel Cell Technology (Ref: Renu20-06)
  Dr M Peeters
Application Deadline: 31 January 2020

Funding Type

PhD Type

The EPSRC Centre for Doctoral Training (CDT) in Renewable Energy Northeast Universities (ReNU) is a collaborative doctoral training programme run by the Universities of Northumbria, Newcastle and Durham.
  PhD Studentship Opportunity in Lithium-Sulphur Batteries
  Dr C Lekakou
Application Deadline: 10 December 2019

Funding Type

PhD Type

We are advertising for the allocation of a PhD studentship on Lithium-Sulphur batteries. The project will be in association with the research programme LiSTAR, which is funded under the umbrella of the Faraday Institution in UK (Powering Britain’s battery revolution.
  Supramolecular sensors for the detection and removal of environmental pollutants
  Dr T A Barendt
Applications accepted all year round

Funding Type

PhD Type

The development of selective supramolecular sensors that undergo a macroscopic, detectable response upon binding a particular substrate is an intense area of interest.
  Electrochemical mechanisms of coating failure
  Research Group: Metallurgy and Corrosion
  Dr N Stevens
Application Deadline: 27 April 2020

Funding Type

PhD Type

Sustainable Coatings by Rational Design (SusCoRD) is a multi-disciplinary project which aims to, for the first time, connect a detailed scientific understanding of the mechanisms of coatings failure with state-of-the-art-machine learning to deliver a framework for the optimisation of protective coatings and nanocomposite materials.
  Molecular modelling insights into the performance of polymeric coatings containing active corrosion inhibitors
  Research Group: Multiscale Modelling
  Dr F Siperstein, Prof X Zhou, Dr C Avendano
Application Deadline: 27 January 2020

Funding Type

PhD Type

Sustainable Coatings by Rational Design (SusCoRD) is a multi-disciplinary project which aims to, for the first time, connect a detailed scientific understanding of the mechanisms of coatings failure with state-of-the-art-machine learning to deliver a framework for the optimisation of protective coatings and nanocomposite materials.
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