Junhong Chen

About

Professor Junhong Chen leads the Junhong Chen Research Group at the University of Chicago, focusing on the multidisciplinary design and discovery of novel nanomaterials for advanced sensing and energy devices. The group combines experimental approaches with first-principles calculations to engineer materials that exhibit unique electronic charge separation and transfer at interfaces, enabling superior device performance. Their research addresses critical needs in low-cost, real-time, sensitive, and selective detection of a wide range of analytes relevant to food-energy-water systems, smart and connected health, communities, the Internet of Things, and next-generation smart infrastructures. These sensors integrate with smartphones and terminals equipped with machine learning and big data analytics to enhance functionality and accessibility. In addition to sensor development, Professor Chen's group works on cost-effective, high-performance energy devices aimed at renewable energy production and storage. The research themes also include scalable nanomanufacturing of electronic devices through inkjet printing and nano-enabled water and air pollution control. Professor Chen's work is highly interdisciplinary, involving collaborative projects in AI-enabled molecular engineering and bio-based compound printing for advanced electronics. His contributions have been recognized through numerous interviews, keynote talks, and listings as a highly cited researcher globally. He holds the…

Research topics

• Computer Science
• Chemistry
• Nanotechnology
• Materials science
• Artificial Intelligence
• Environmental chemistry
• Waste management
• Environmental science

Selected publications

• Understanding, discovery, and synthesis of 2D materials enabled by machine learning

  Chemical Society Reviews · 2022 · 162 citations

  Senior authorCorresponding

  Machine learning (ML) is becoming an effective tool for studying 2D materials. Taking as input computed or experimental materials data, ML algorithms predict the structural, electronic, mechanical, and chemical properties of 2D materials that have yet to be discovered. Such predictions expand investigations on how to synthesize 2D materials and use them in various applications, as well as greatly reduce the time and cost to discover and understand 2D materials. This tutorial review focuses on th…

  DOI

• Selectivity of Per- and Polyfluoroalkyl Substance Sensors and Sorbents in Water

  ACS Applied Materials & Interfaces · 2021 · 135 citations

  Senior authorCorresponding

  Per- and polyfluoroalkyl substances (PFAS) are a large group of engineered chemicals that have been widely used in industrial production. PFAS have drawn increasing attention due to their frequent occurrence in the aquatic environment and their toxicity to animals and humans. Developing effective and efficient detection and remediation methods for PFAS in aquatic systems is critical to mitigate ongoing exposure and promote water reuse. Adsorption-based removal is the most common method for PFAS…

  DOI

• Leveraging data mining, active learning, and domain adaptation for efficient discovery of advanced oxygen evolution electrocatalysts

  Science Advances · 2025-04-04 · 27 citations

  articleOpen accessSenior authorCorresponding

  Developing advanced catalysts for acidic oxygen evolution reaction (OER) is crucial for sustainable hydrogen production. This study presents a multistage machine learning (ML) approach to streamline the discovery and optimization of complex multimetallic catalysts. Our method integrates data mining, active learning, and domain adaptation throughout the materials discovery process. Unlike traditional trial-and-error methods, this approach systematically narrows the exploration space using domain…

  PublisherDOI

• Reversible parts-per-trillion-level detection of perfluorooctane sulfonic acid in tap water using field-effect transistor sensors

  Nature Water · 2025-09-25 · 9 citations

  articleSenior author
  PublisherDOI

• Pound–Drever–Hall stabilized single-frequency diamond Raman laser with sub-10 kHz linewidth

  Optics Letters · 2025-04-10 · 8 citations

  article

  Benefiting from the exceptional properties of diamond crystals and the absence of spatial hole burning in stimulated Raman scattering, diamond Raman lasers (DRLs) are effective materials for achieving a single longitudinal mode laser output at specific wavelengths. The use of resonant pumping techniques can yield a low-threshold single longitudinal mode DRL output. However, the polarization dependence of the Raman gain in diamond and the birefringence induced by high-power lasers affect the outp…

  PublisherDOI

Recent grants

• Collaborative Research: Engineering Miniaturized Gas Sensors with Hybrid Nanostructures

  NSF · $300k · 2009–2012

• NER: Carbon Nanotubes Coated with Nanoparticles - An Enabling Structure for Nanomanufacturing and Nanodevices

  NSF · $176k · 2006–2008

• SNM: Customized Inkjet Printing of Graphene-Based Real-time Water Sensors

  NSF · $1.5M · 2017–2020

Frequent coauthors

• Shun Mao

  Shanghai East Hospital

  153 shared

• Ganhua Lu

  University of Wisconsin–Milwaukee

  113 shared

• Hongting Pu

  Tongji University

  108 shared

• Zhenhai Wen

  Chinese Academy of Sciences

  74 shared

• Shumao Cui

  University of Wisconsin–Milwaukee

  65 shared

• Xiaoyu Sui

  Qiqihar Medical University

  61 shared

• Kehan Yu

  Nanjing University of Posts and Telecommunications

  57 shared

• Yuqin Wang

  University of Chicago

  57 shared

Education

• Ph.D., Mechanical Engineering

  University of Minnesota System

  2002

Awards & honors

• Fellow of the National Academy of Inventors (NAI)
• Fellow of the Royal Society of Chemistry (RSC)
• Fellow of the American Society of Mechanical Engineers (ASME…
• 2016 Wisconsin Innovation Award

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• Giulia Gallih-99
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