About

Tao Gao is an Assistant Professor in the Department of Chemical Engineering at the University of Utah. His research interests include batteries, electrochemistry, energy storage, energy storage systems, renewable energy, and transport phenomena. He has received several awards and honors, including the 2016 Dean’s Dissertation Fellowship, the 2015 Future Faculty Fellow at the University of Maryland, and the 2015 Outstanding Graduate Assistant Award. His work involves studying the interplay of lithium intercalation and plating on graphite particles, small-scale seawater desalination via shock electrodialysis, phase morphologies during ion intercalation, and modeling phase transitions in energy storage materials. Tao Gao has contributed to advancing understanding in electrochemical energy storage technologies and has been recognized for his research excellence.

Research topics

• Metallurgy
• Organic chemistry
• Waste management
• Chemistry
• Inorganic chemistry
• Engineering
• Environmental economics
• Business
• Economics
• Automotive engineering
• Chemical physics
• Materials science
• Physics
• Marketing
• Reliability engineering
• Physical chemistry
• Chemical engineering

Selected publications

• Optimal sizing of battery energy storage systems for peak shaving and demand response using a degradation-aware Bayesian Optimization-Mixed-Integer Linear Programming framework

  Energy Conversion and Management · 2025-12-19

  articleOpen access

  • Degradation-aware framework co-optimizes energy storage systems’ size and dispatch. • Electrochemical model captures calendar and cycling aging impacts. • Stacked peak-shaving with demand response shift optimal system’s size. • Sensitivity sweeps reveal economic no-storage thresholds and sizing design charts. The increasing integration of renewable energy and rising electricity demand highlight the importance of battery energy storage systems for peak shaving and demand response. Unlike prior approaches that overlook operational impacts on degradation, this study proposes a Bayesian Optimization–Mixed Integer Linear Programming framework for optimal battery energy storage system sizing. In this framework, Mixed Integer Linear Programming determines short-term scheduling while a calibrated electrochemical model iteratively evaluates degradation. The central hypothesis is that the framework can efficiently identify optimal sizes that yield realistic and economically robust outcomes. The method is tested across three scenarios: peak shaving, peak shaving with energy-reduction demand response, and peak shaving with power-reduction demand response. Results show that the framework converge to the optimum within 20 iterations out of 150 possible sizes. Under baseline conditions, the framework consistently selects the smallest feasible system, minimizing unnecessary degradation costs from oversized storage. Sensitivity analyses reveal that larger systems are favored as demand rates or incentives increase. Comparisons of demand response programs indicate that power-reduction demand response offers greater economic benefits than energy-reduction demand response, although demand savings from peak shaving remain the dominant contributor to overall performance. This study demonstrates that the proposed framework balances computational tractability with degradation fidelity, identifies critical economic thresholds for investment, and offers a practical, flexible tool to guide industrial stakeholders in cost-effective battery energy storage system deployment.

  PublisherDOI

• Optimal Sizing of Battery Energy Storage Systems for Peak Shaving and Demand Response Using a Degradation-Aware Bo-Milp Framework

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• Tribological Behavior and Wear Mechanism of Heavy-Load Woven Self-Lubricating Liners Under a Wide Temperature Range

  Journal of Tribology · 2025-10-13

  article

  Abstract Self-lubricating spherical plain bearings are widely employed in aerospace, electronics, and other demanding applications. The performance of fabric self-lubricating liners directly impacts the characteristics of these bearings, making their tribological behavior and wear mechanisms highly significant. This paper presents service-life experiments on polytetrafluoroethylene (PTFE)/Kevlar woven self-lubricating liners tested from −50 °C to 160 °C under high contact loads. During the friction process, the characteristics of the transfer film are emphasized. The results indicate that at low temperatures, the PTFE surface is rough, transfer-film formation is sparse, and the coefficient of friction is high. Conversely, elevated temperatures promote uniform transfer films and markedly lower friction. Scanning electron microscopic images and energy-dispersive X-ray spectroscopy results reveal temperature-dependent crazing and wear patterns. The crack networks (shish–kebab structures) around crazes enhance load-bearing capacity and reduce wear. X-ray diffraction indicates increased molecular ordering and a more perfect crystalline structure of PTFE at higher temperatures. The study suggests that a PTFE lubricating film consists of four distinct structural layers. This paper describes a new wear mechanism and transfer-film mechanism under a wide-temperature range and high-load friction conditions, which provides a theoretical basis for future applications.

  PublisherDOI

• The effect of precipitates and alloying elements on γ-Fe (111) surface dissolution corrosion in liquid lead-bismuth eutectic by first-principles study

  Journal of Nuclear Materials · 2025-02-26 · 2 citations

  articleCorresponding
  PublisherDOI

• Unsupervised arbitrary-scale point cloud upsampling by learning neural gradient function

  Multimedia Systems · 2025-06-08

  article1st authorCorresponding
  PublisherDOI

• Lithium-ion intercalation by coupled ion-electron transfer

  Science · 2025-10-02 · 37 citations

  articleCorresponding

  The underlying reaction mechanism in lithium-ion batteries remains poorly understood. We provide experimental and theoretical evidence that lithium intercalation occurs by coupled ion-electron transfer, where ion transfer across the electrode-electrolyte interface is facilitated by electron transfer to a neighboring redox site. Electrochemical measurements for a variety of common electrode and electrolyte materials reveal a universal dependence of the (de-)intercalation rate on Li + vacancy fraction, as well as temperature and electrolyte effects consistent with the theory, which could be used to guide the molecular design of lithium-ion battery interfaces.

  PublisherDOI

• Experiments and Theory of Metal-Anion Complexation and Its Effect on the Thermodynamics and Transport Properties of Aqueous Electrolytes

  ECS Meeting Abstracts · 2025-11-24

  article1st authorCorresponding

  Electrolyte is a key component in an aqueous battery and it is responsible for ion conduction, interface stabilizing and dissolving the active materials in the context of flow batteries. In the past decade, concentrated electrolytes have emerged as a new family of electrolyte due to their unique properties, which unleashed unprecedented performance for aqueous batteries. A fundamental understanding of the structure of concentrated electrolytes and how it regulates the thermodynamic, kinetic and transport properties of aqueous electrolyte is critical to design the next-generation aqueous electrolytes. In concentrated electrolytes, the strong cation-anion interaction leads to iron pairing, aggregation, clustering and networking. For metal batteries using transition metal working ions, such as Fe2+, Zn2+, and etc., metal-ligand complexation forms due to such cation-anion interaction. In this talk, we will share our fundamental study that combines experiments and theory to understand how metal-anion complexation affects the thermodynamics of electrode reaction and transport properties of aqueous electrolytes.

  PublisherDOI

• High-Efficiency Low-Temperature Electrolytic Ironmaking in Acidic Environment Enabled by Novel Electrolyte Design

  ECS Meeting Abstracts · 2025-11-24

  article1st authorCorresponding

  Iron and its alloy is the second most-produced material by human society and is a pillar of modern society. However, the current ironmaking process is not sustainable due to the heavy use of fossil fuel as the reductant and energy source for reducing iron ore. Two routes have emerged to address this challenge. One is direct hydrogen reduction, which uses hydrogen sourced from renewable energy to reduce iron ore. Another is direct electrolytic reduction using renewable electrons. Depending on the electrolytes, various electrolytic routes are possible. Molten-oxide electrolysis enables high current operation, but suffers from challenges such as low efficiency, corrosion, heat loss, etc. Low-temperature electrolysis can avoid some of these challenges. Alkaline electrolysis has been studied for over a decade and has been demonstrated in several projects in European Union and in US. However, acidic electrolysis has received much less attention. In this talk, we will discuss the opportunities and challenges of acidic electrolysis, and present our results in addressing one of the critical challenges of acidic electrolysis, the low faradaic efficiency due to the competing hydrogen evolution reactions. We will share our results in high-efficiency electrowinning of iron metal, discuss the fundamental science underlying the unprecedented efficiency, and opportunities and gaps of designing practical ironmaking process based on acidic electrolysis.

  PublisherDOI

• Maximizing the Benefit of Industrial Battery Energy Storage Through Incentive Stacking and Optimal Dispatch

  SSRN Electronic Journal · 2025-01-01 · 1 citations

  preprintOpen access
  PublisherDOI

• Sustainable and highly efficient production of high-purity iron from oxide ores by acidic electrowinning in anion-rich electrolytes

  Electrochimica Acta · 2025-09-10 · 2 citations

  articleSenior authorCorresponding
  PublisherDOI

Recent grants

• Collaborative Research: Catholyte Molecular Design For Non-aqueous Mg-organic Hybrid Redox Flow Batteries

  NSF · $340k · 2023–2026

Frequent coauthors

• Chunsheng Wang

  University of Maryland, College Park

  79 shared

• Xiulin Fan

  Zhejiang University

  60 shared

• Fei Wang

  Anhui University

  42 shared

• Fudong Han

  Rensselaer Polytechnic Institute

  36 shared

• Chao Luo

  George Mason University

  33 shared

• Zhidan Sun

  Hefei Institutes of Physical Science

  33 shared

• Kang Xu

  DEVCOM Army Research Laboratory

  32 shared

• Liumin Suo

  31 shared

Awards & honors

• 2016 Dean’s Dissertation Fellowship
• 2015 Future Faculty Fellow, University of Maryland
• 2015 Poster Award at CREB Annual Meeting
• 2015 Outstanding Graduate Assistant Award
• 2009 National Fellowship