Professor

Phùng Thị Việt Bắc

Affiliation: VinUniversity, Hanoi, Viet Nam

Research Management Office / College of Engineering and Computer Science / Center for Environmental Intelligence

Introduction

Dr. Phung Thi Viet Bac received her PhD in Computational Science and Physics from Kanazawa University, Japan in 2009, and her MSc and BSc in Chemistry from Vietnam National University, Hanoi and Hanoi National University of Education in 2005 and 2002, respectively. After receiving her PhD, she continued her postdoctoral research at Kanazawa University and the National Institute of Industrial Science and Technology (AIST) from 2009 to 2012. Dr. Viet Bac’s research focuses on Material Simulation Design, applications in sensors, energy conversion and storage. In 2013, she was a researcher at the Japan Advanced Institute of Science and Technology (JAIST) working in the fields of photovoltaic cells, low-dimensional materials and nano-devices. After that, Dr. Viet Bac spent 4 years teaching and researching at Fukui University, Japan. From 2018 to 2023, she worked at Vietnam Japan University – Vietnam National University, Hanoi as a lecturer and researcher. She led a research group on Multi-scale Material Design and Simulation at the Institute for Sustainable Science. She was the founding Executive Scientific Secretary of the VinFuture Prize Foundation, established in 2021. From 2023, she joined VinUniversity as a Head of Research Management Office and faculty member of the College of Engineering and Computer Science. She currently serves as Director of Research and Innovation and Chief Executive Officer of the Center for Environmental Intelligence (CEI). Her research focuses on the design and development of advanced materials for next-generation energy storage batteries, recycled materials, green hydrogen production, and sustainable clean energy solutions. Dr. Viet Bac is a member of the American Chemical Society (ACS) and the Materials Research Society (MRS), USA.

Affiliation: VinUniversity, Hanoi, Viet Nam

Research Output

Deciphering energy storage mechanisms and pore structure effects in sugarcane bagasse-derived biomass carbon for lithium – ion batteries and supercapacitors

Nguyen Quynh Nhu, Nguyen Nghia Trong, Vuong Thuy Trang T., La Viet-Duy, Phung Thi Viet Bac, Nguyen Nhat Van, Vu Phat Tan, Nguyen Hoang Van, Le Phung My Loan, Nguyen Phi Long
  • Biomass
  • Energy storage
  • Pore structure
  • Pseudo-capacitive
  • Sugarcane bagasse

Adsorption mechanisms of ethanol, propanal, butanone, and benzene on the monolayer WS₂ Surface: Insights from non-local van der Waals density functional theory

Tran Quang Huy, Luong Thi Theu, Nguyen Thi Hai Yen, Tran Thi Nhan, Phung Viet Bac T., Dinh Van An
  • Adsorption
  • Benzene
  • Butanone
  • Ethanol
  • Propanal
  • VOC
  • WS2, DFT

High-temperature behavior at 100 ℃ of nanoporous copper-metal-organic framework for strong duration symmetrical solid-state supercapacitors

Le Phuoc-Anh, Van Le Hoang, Tran ThiNhan, Vuong ThuyTrangT., La Viet Duy, Vu Van-Hao, Nguyen-Dang Tung, Nguyen PhiLong, Phung ThiVietBac
  • CuBDC
  • CuBTC
  • Energy storage
  • Gel polymer electrolyte
  • Metal organic frameworks
  • Supercapacitors

Resolving adsorption mechanism of sodium polysulfides on Tim+1CmO2 MXenes for application in sodium-sulfur batteries: A first-principles study

Dang Minh Triet, Long Nguyen Truong, Thi Phung Viet Bac, Trang Nguyen Thi Bao, Nguyen Truc Anh, Tran Thi Nhan, Duy Nguyen Vo Anh, Van Nguyen To, Nghia Nguyen Van, Schall Peter
  • Anchoring materials
  • Density functional theory
  • MXenes
  • Sodium sulfide clusters
  • Sodium-sulfur batteries

Investigation of Structural and Electrochemical Modulation in NaFe0.5Co0.5O2Cathode Material via Zn Substitution for Fe

Nguyen Hoang Van, Tran Thi Nhan, Nguyen Minh Le, Nguyen Quynh Nhu, Tran Van Man, Le Phung M-L., Nguyen An-Giang, Nguyen Phi Long, Phung Viet-Bac Thi
  • cathode materials
  • O3-type layered structure
  • performance
  • sodium-ion batteries
  • sol–gel process
  • zinc doping

Graphene/hexagonal boron nitride heterostructure: A promising material for ammonia gas sensing devices in humid environments

  • ammonia
  • co-adsorption
  • DFT calculations
  • graphene/hexagonal boron nitride heterostructures
  • water

Unraveling fundamental characteristics of Na2Mg3Cl8 as a solid-state electrolyte for Na-ion batteries

Zulueta Yohandys A., Fernández-Gamboa Jose R., Phung Thi Viet Bac, Pham-Ho My Phuong, Nguyen Minh Tho

Electric field enhances the electronic and diffusion properties of penta-graphene nanoribbon anodes in lithium-ion batteries

Tran Thi Nhan, Anh Duy Nguyen Vo, Hieu Nguyen Hoang, Nguyen Truc Anh, Van Nguyen To, Bac Phung Thi Viet, Zulueta Yohandys A., Nguyen Minh Tho, Schall Peter, Dang Minh Triet

Hydrovoltaic–piezoelectric hybridized device for microdroplet-pressure dual energy harvesting and piezo sensing

Dinh Trung Vuong, Le Phuoc-Anh, Natsuki Jun, Zhao Weili, Viet Bac Phung Thi, Tan Jing, Yang Weimin, Natsuki Toshiaki
  • Hybridized device
  • Hydrovoltaic capacitor
  • Piezoelectric
  • Sensor system
  • Solid-state battery

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Keyphrases

  • Biomass
  • Energy storage
  • Pore structure
  • Pseudo-capacitive
  • Sugarcane bagasse
  • Adsorption
  • Benzene
  • Butanone
  • Ethanol
  • Propanal
  • VOC
  • WS2, DFT
  • CuBDC
  • CuBTC
  • Gel polymer electrolyte
  • Metal organic frameworks
  • Supercapacitors
  • Anchoring materials
  • Density functional theory
  • MXenes
  • Sodium sulfide clusters
  • Sodium-sulfur batteries
  • Chemical Engineering
  • Environmental engineering
  • Water geochemistry
  • Water resources engineering
  • cathode materials
  • O3-type layered structure
  • performance
  • sodium-ion batteries
  • sol–gel process
  • zinc doping
  • ammonia
  • co-adsorption
  • DFT calculations
  • graphene/hexagonal boron nitride heterostructures
  • water
  • Hybridized device
  • Hydrovoltaic capacitor
  • Piezoelectric
  • Sensor system
  • Solid-state battery
  • density functional theory
  • DFT
  • machine learning
  • materials informatics
  • metal-organic frameworks
  • MOFs
  • neural network model
  • All-solid-state supercapacitor
  • High energy density
  • Hybrid supercapacitor
  • Synergistic effect

Computer Science

  • Forestry