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WEB Rational Design of Metal Anchored Carbon Quantum Dots as Optimal Efficient Electrocatalysts for Hydrogen production Using Machine Learning and High-throughput Experimentation

Friday (17.07.2020)
04:03 - 04:03 Poster Room
Part of:
- Poster *web*Simulation of Spinning Processes with Experimental Validation 1 Stefan Hermanns
- Poster *web*Screening Solubility-Enhancing Coformers in Amorphous Solid Dispersions: a Group Contribution based Miscibility Method 1 Milad Asgarpour Khansary
- Poster *web*Thermal emission of colloid-based plasmonic structures for radiative cooling 1 Kishin Matsumori
- Poster *web*Free energies of segregation: thermodynamic integration at grain boundaries using pyiron 1 Dr. Liam Huber
- Poster *web*Effective mobility of BCC dislocations in two-dimensional discrete dislocation plasticity 1 Tarun Katiyar
- Poster TBA -
- Poster *web*Computer Aided Reliability by additive manufacturing of components with locally varied properties 1 Dr. Iliya Radulov
- Poster *web*Numerical Study of Solidification in Metallic Droplet 1 Dandan Yao
- Poster TBA -
- Poster TBA -
- Poster TBA -
- Poster TBA -
- Poster *web*Thermodynamic assessment and modelling of interactions in liquid Ni alloys/oxide systems 1 Saverio Sitzia
- Poster *web*The limiting effect of interfacial band alignment on efficiency of earth-abundant chalcogenide photovoltaic materials 1 Dr. Elaheh Ghorbani
- Poster *web*HMC hub matter for as a resource for materials research in the German research landscape 1 Dr. Oonagh Mannix
- Poster *web*Nanoindentation of Al: Molecular dynamics simulations and dislocation dynamics simulations 1 Sa-Ly Dang
- Poster *web*Rational Design of Metal Anchored Carbon Quantum Dots as Optimal Efficient Electrocatalysts for Hydrogen production Using Machine Learning and High-throughput Experimentation 1 Yujin Chae
- Poster *web*Correlating Raman Spectra of Ibuprofen, Nicotinamide and Their Dimers 1 Milad Asgarpour Khansary
- Poster *web*High Throughput Screening for Electrochemical Nitrogen Reduction for the Ammonia Synthesis via Machine Learning 1 JaeHyoung Lim
- Poster Thermodynamic investigation of oxidation behavior of NiAl intermetallics with embedded Cr and Mo 1 Golnar Geramifard

Session -M: Modelling, Simulation, and Data
Belongs to:
Topic X: Poster Session

Hydrogen (H2) has been considered a promising candidate as a sustainable energy source for restricting carbon dioxide emissions, which electrochemical water splitting is recognized as one of the most potential technology for producing hydrogen. However, it is still a critical issue that practically required voltage for operating full water splitting needs more overpotential than the theoretical potential range of 1.23 V. As these challenges, electrocatalysts have been researched, while noble metal materials such as Pt and RuO2 are broadly used due to its superior catalytic activity. Although they have advantageous catalytic performance, their high cost and scarcity restrict the realization of economic electrochemical water splitting. To overcome the drawback, carbon-based materials showing earth-abundant, low cost, and high catalytic activity have studied for substituting noble metal-based catalysts. Especially, carbon quantum dots (CQDs) have been reported as an electrochemical catalyst due to nanoparticle size, high stability, and good electrical conductivity. In addition, the optimization design of experiments (DoE) has been increasingly attracted to achieve the superior performance of the prepared catalysts. Herein, Nitrogen-enriched CQDs (N-CQDs) are synthesized and doped with various heteroatoms (Ni, Co, Mn, Fe, and Zn) for enhancing the kinetic process of reactions. Moreover, DoE is investigated by a novel machine learning (ML) method of the Bayesian genetic algorithm (BGA) regarding various parameters for system such as loading amount, conductor, and pH conditions, which can affect catalytic activity. The ML-based method can minimize the number of experiments from 90,720 to 52 in order to reach optimized conditions where the catalyst can exhibit maximized catalyst performance. As a result, we discovered that the reasoning optimal DoE of Ni/N-CQDs exhibited the lowest overpotential value of 110 mV for HER.

Yujin Chae
Chonnam National University
Additional Authors:
  • Duong Nguyen Nguyen
    Sungkyunkwan University
  • Dr. Namsoo Shin
    Deep Solution Inc.
  • Jaehyoung Lim
    Chonnam National University
  • Dr. Heechae Choi
    University of Cologne
  • Prof. Jung Kyu Kim
    Sungkyunkwan University
  • Prof. Uk Sim
    Chonnam National University


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