Research

Research Vision

Modern chemical manufacturing and the energy industry supply essential chemicals and fuels for agriculture, transportation, healthcare, and consumer products sectors, yet many foundational processes remain energy-intensive and carbon-intensive. As global demand for chemicals and fuels continues to grow, developing sustainable and scalable alternatives is imperative.

Electrified chemical processes powered by renewable electricity offer a compelling pathway. These approaches enable the conversion of abundant, low-value feedstocks, such as carbon dioxide, wastewater-derived species, and plastic waste into valuable chemicals and fuels. However, their practical implementation is limited by sluggish multi-electron transfer kinetics, low selectivity, and catalyst instability under operating conditions. Overcoming these barriers requires catalytic materials that are active, selective, and durable. Conventional discovery relies on slow, sequential trial-and-error workflows that cannot efficiently explore vast material and process spaces.

Our research establishes a new paradigm that integrates high-throughput experimentation with artificial intelligence (AI) to accelerate materials discovery and uncover governing principles across reactions, materials, interfaces, and reactor design. By coupling large-scale experimental datasets with machine learning, we develop predictive models that guide synthesis, identify key descriptors, and enable autonomous optimization of complex electrochemical systems.

Our vision is to discover efficient catalysts, engineer dynamic interfaces, and design scalable devices for the electrochemical conversion of low-value feedstocks into high-value products. Central to this effort are materials discovery platforms, centimeter-scale systems that encode millions of materials with controlled compositions, sizes, and structures, combined with AI-driven frameworks that transform data into actionable insight, enabling rapid exploration and rational design across complex chemical spaces.

Our Integrated Research Ecosystem

Broader Impact:

Enables scalable, sustainable chemical technologies by linking atomic-scale catalyst design to system-level performance
Advances clean energy and climate solutions through efficient electrochemical transformations
Advance circular manufacturing by converting waste-derived feedstocks into value-added chemicals
Creates large experimental datasets that power AI-driven discovery and open data practices

Our Research Program

1. Catalytic Materials Discovery for Efficient C-N Coupling

Organonitrogen compounds are critical to pharmaceuticals, agrochemicals, polymers, and fine chemicals. Conventional methods often require multistep thermochemical processes with high temperatures, precious metals, and stoichiometric reagents, leading to high energy use and significant waste. Electrified processes such as electrocatalysis offer a sustainable alternative by using renewable electricity and waste-derived feedstocks, such as CO₂ from flue gas or nitrate from wastewater, to form C–N bonds under mild conditions.

Goals. We aim to discover efficient catalysts and establish general design principles by integrating high-throughput synthesis, screening, and characterization with AI-assisted analysis and optimization. These insights will guide the rational design of catalysts for producing valuable organonitrogen compounds such as urea, amides, and amines from waste-derived feedstocks (e.g., CO₂, nitrate, nitrite). This research will lay the foundation for advancing key catalytic reactions, including C–C, C–S, C–P coupling, nitrogen chemistry that are central to sustainable chemical manufacturing.

Related Publication
Huang, J.†; Wang, Z.†; Liang, J.†; Li, X.; Pietryga, J.; Ye, Z.; Smith, P. T.; Kulaksizoglu, A.;McCormick, C. M.; Kim, J.; Peng, B.; Liu, Z.; Xie, K.; Torrisi, S. B.; Montoya, J. H.; Wu, G.; Sargent, E. H.*; Mirkin, C. A.* Accelerating the pace of OER catalyst discovery through megalibraries. J. Am. Chem. Soc. 2025, 147, 34, 30956–30966.

Huang, J.; Liu, Y.; Xu, M.; Wan, C.; Liu, H.; Li, M.; Huang, Z.; Duan, X.; Pan, X.; Huang, Y.* PtCuNi Tetrahedra catalysts with Tailored Surface for efficient alcohol oxidation. Nano Lett. 2019, 19, 8, 5431-5436.

2. Sustainability-Enabling Interfaces for Plastic and Biomass Upcycling

Plastics are indispensable to modern society due to their durability and versatility, yet their reliance on petroleum feedstocks has created severe environmental challenges. Nearly 80% of plastics accumulate in landfills or the environment, with less than 10% effectively recycled, leading to widespread micro- and nanoplastic pollution with ecological and health risks. While polymers such as polyethylene terephthalate (PET) can undergo hydrolytic degradation, most commodity plastics, including polyethylene (PE), polypropylene (PP), polystyrene (PS), and polyvinyl chloride (PVC), have inert C–C backbones that resist depolymerization. Current recycling relies on energy-intensive thermochemical processes (e.g., pyrolysis >500 °C), producing complex mixtures and significant greenhouse gas emissions. Achieving true plastic circularity requires not only efficient depolymerization but also selective conversion of products into value-added chemicals. Electrochemical and photoelectrochemical approaches powered by renewable energy offer promising alternatives, but are limited by low activity, poor selectivity, and catalyst instability. Addressing these challenges requires strategies that couple efficient catalytic conversion with dynamic control of interfacial environments.

Goals. Our goal is to enable efficient and selective plastic degradation and upcycling by engineering electrochemical and photoelectrochemical interfaces. By integrating interfacial design with operando characterization techniques, including ATR-SEIRAS and Raman spectroscopy, we probe local reaction environments, track intermediate dynamics, and establish structure–function relationships at interfaces. These insights guide the development of catalytic systems and scalable pathways for plastic upcycling, with broader implications for the valorization of complex feedstocks such as biomass.

Related Publication
Huang, J.†; Peng, B.†; Zhu, C.†; Xu, M.; Liu, Y.; Liu, Z.; Zhou, J.; Wang, S.; Duan, X.; Heinz, H.*; Huang, Y.* Surface molecular pump enables ultrahigh catalyst activity. Sci. Adv. 2024, 10, eado3942

3. Energy-Efficient Device Development and Seamless Catalyst–Reactor Integration

Electrochemical reactors are central to electrified chemical manufacturing, bridging catalyst innovation with scalable production. Despite advances in catalytic materials, their translation to practical reactor environments remains limited, and the efficiency, selectivity, and durability required for industrial deployment are not yet achieved. Key challenges including mass transport limitations, poorly controlled reaction environments, and insufficient integration of catalysts with electrodes and electrolytes hinder performance and scalability. At the same time, the vast reactor design space, spanning flow geometries, electrode architectures, and operating conditions, remains largely unexplored due to reliance on slow, trial-and-error optimization. Addressing these challenges requires new strategies that accelerate reactor prototyping, establish predictive relationships between design parameters and performance, and integrate catalyst and reactor development within a unified framework. Data-driven, high-throughput approaches enabled by advances in computation and AI will be critical to transforming electrochemical reactors into rationally engineered platforms for scalable and sustainable manufacturing.

Goals. Our goal is to design and optimize high-throughput electrochemical reactors for scalable bond formation (e.g., C–N coupling) and to establish a closed-loop, data-driven framework that integrates high-throughput experimentation with AI-guided optimization. This approach will uncover design principles, enable systematic exploration of reactor design space, and achieve seamless catalyst–reactor integration for enhanced performance and scalability.

Related Publication
Huang, J.; Sementa, L.; Liu, Z.; Barcaro, G.; Feng, M.; Liu, E.; Jiao, L.; Xu, M.; Leshchev, D.; Lee, S.-J.; Li, M.; Wan, C.; Zhu, E.; Liu, Y.; Peng, B.; Duan, X.; Goddard, W. A.*; Fortunelli, A.*; Jia, Q.*; Huang, Y.* Experimental Sabatier plot for predictive design of active and stable Pt-alloy oxygen reduction reaction catalysts. Nat. Catal. 2022, 5, 513-523.

Huang, J.†; Tsai, Y.-H.†; Zheng, S.; Zhang, A.; Wang, S.; Pu, H.; Peng, B.; Liu, Z.; Hsiao, T.; Ma, C.; Li, B.; Wang, M.; Huang, Y.* Synthesis of PtCo nanotwinned catalysts via laser ablation. Nano Res., 2025, 18(12): 94908136

4. Heterogeneous Electrochemical Cross-Coupling Reaction Platform

Cross-coupling reactions are foundational for forming C–C and C–X bonds in pharmaceuticals, agrochemicals, and polymers. Conventional methods rely on homogeneous catalysts that require transition metals, complex ligands, and stoichiometric oxidants or reductants, leading to energy-intensive, multistep processes with significant waste and limited catalyst recyclability. Electrochemistry offers a compelling alternative for redox-driven synthesis, enabling high local concentrations of reactive intermediates and selective activation under mild conditions through precise potential control. While homogeneous electrocatalytic systems demonstrate feasibility, they typically operate within narrow potential windows, at low current densities, and face challenges in stability and recycling, limiting scalability. Heterogeneous electrocatalysis using inorganic materials provides a promising path forward, offering robust stability, recyclability, and tunability in composition, structure, and morphology. These systems enable enhanced control over charge transfer, access to higher current densities and potentials, and new reaction pathways governed by adsorption–desorption equilibria and interfacial proton and electron transfer. Despite these advantages, systematic approaches to discover and optimize heterogeneous electrocatalysts remain underdeveloped, limiting mechanistic understanding and the establishment of general design principles.

Goals. Our goal is to develop heterogeneous electrochemical cross-coupling methodologies and elucidate their mechanisms using megalibrary platforms. By integrating high-throughput experimentation with data-driven analysis, we aim to identify active catalyst motifs, uncover governing principles, and enable scalable, sustainable synthesis of value-added organic molecules, advancing the electrification of chemical manufacturing.