About

Bai Gao is a Professor of Sociology at Duke University, holding this position since 2003 within the Trinity College of Arts & Sciences. His research projects include studying the rise of electric vehicles in China with a focus on the impact of state industrial policy on industry development, and examining how three mega historical trends—globalization, hegemonic cycles, and technological revolutions such as artificial intelligence and robotics—are shaping the international political economy. Gao has published works including a book titled "High-Speed Rail: An Analysis of the Chinese Innovation System" and various articles on industrial policy, globalization, and China's economic transformation. His academic background includes a Ph.D. from Princeton University, and his work has been supported by multiple grants, notably from the Josiah Charles Trent Memorial Foundation.

Research topics

• Chemistry
• Geology
• Environmental chemistry
• Environmental science
• Geochemistry
• Ecology
• Chemical engineering
• Nanotechnology
• Materials science
• Composite material
• Waste management
• Organic chemistry
• Environmental engineering
• Biology
• Mineralogy

Selected publications

• Conclusion: Comparative Analysis of China-Europe Railway Express

  China and globalization 2.0 · 2026-01-01

  book-chapter1st authorCorresponding
  PublisherDOI

• A novel application of Limonite: chromium(VI) bioreduction and sulfide management for sustainable groundwater cleanup

  Journal of Cleaner Production · 2025-05-21 · 3 citations

  article
  PublisherDOI

• Sustainable Soil Phosphorus Management Using Sewage-Derived Phosphorus-Recycling Ceramics (Pc): Enhanced Spinach Growth and Metabolomic Insights

  SSRN Electronic Journal · 2025-01-01

  preprintOpen accessSenior author
  PublisherDOI

• Dual ²²²Rn Models for Tracing Groundwater–Lake Water Exchange in a Flow‐Through Lake

  Water Resources Research · 2025-03-01 · 1 citations

  articleOpen access

  Abstract Groundwater–lake water exchange in flow‐through lakes which includes both groundwater discharge into the lake and lake water seepage into the aquifer, is crucial for sustaining lake wetland ecosystems; however, these two processes are rarely addressed simultaneously by tracer methods. In this study, radon ( 222 Rn) is used as a tracer to estimate both groundwater inflow and outflow in flow‐through lakes in the Poyang Lake area, using a combination of a 222 Rn mass‐balance model and a 222 Rn production‐decay model. The results reveal that the 222 Rn flux from lake water seepage into the aquifer cannot be neglected in the 222 Rn mass‐balance model for flow‐through lakes. The velocity of groundwater discharging into the flow‐through lake was determined to be 23 ± 13 cm/d based on the 222 Rn mass‐balance model, while the velocity of the lake water seepage into the ground was estimated to be 22 ± 14 cm/d using the 222 Rn production‐decay model. A valid point dilution test was used to estimate the groundwater Darcy velocity near the flow‐through lake as 24 cm/d, which closely matches to the results obtained using the 222 Rn method. The results from 222 Rn production‐decay model enhance the accuracy of groundwater discharge estimation derived from the 222 Rn mass‐balance model. This study demonstrates both processes of groundwater–lake water exchange (groundwater discharge into the lake and lake water seepage into the ground) in a flow‐through lake can be estimated using only 222 Rn (dual 222 Rn models: mass‐balance model and production‐decay model).

  PublisherOA PDFDOI

• The migration characteristics and change in speciation of nuclides U and Th in the downstream river of the uranium tailings pond

  Journal of Radioanalytical and Nuclear Chemistry · 2025-10-29

  article
  PublisherDOI

• Enhanced Remediation of Uranium-Contaminated Soil Through Synergistic Action of Indigenous Uranium-Tolerant Bacteria and Plants

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• BBX32a and BBX32b Regulate Flowering Time in Soybean Under Long‐Day Conditions

  Plant Cell & Environment · 2025-11-21

  article

  ABSTRACT Photoperiod regulates flowering time and maturity in soybean, thereby determining yield performance and latitudinal adaptation. However, the molecular network through which photoperiod regulates flowering remains incompletely elucidated. Here, we identify two BBX family transcription factors, BBX32a and BBX32b, that act as positively regulators flowering under long‐day (LD) conditions in soybean. We demonstrate that BBX32a and BBX32b can form both homologous and heterologous dimers. The bbx32a and bbx32b mutants exhibit significantly delayed flowering compared to wild‐type W82. However, the bbx32a bbx32b double mutants flower at a similar time to the single mutants, suggesting that the BBX32a‐BBX32b heterodimer plays a central role in regulating soybean flowering. E3 and E4 upregulate the transcription of BBX32a and BBX32b , which repress E1 transcription to promote flowering under LD conditions. Genetic evidence demonstrates that BBX32a and BBX32b regulate flowering time, completely dependent on functional E3 , E4 and E1 family genes. Four haplotypes of BBX32a were identified in 1295 soybean accessions; BBX32a Hap3 exhibits significantly reduced nuclear accumulation relative to BBX32a Hap1 . The BBX32a Hap1 allele is predominantly fixed in cultivated soybeans, whereas BBX32a Hap2 and BBX32a Hap3 alleles remain largely unexploited. Collectively, our findings identify novel genetic targets for developing novel soybean cultivars adapted to high‐latitude regions, thereby maximising yield potential.

  PublisherDOI

• The overexpression of ascorbate peroxidase 2 (APX2) gene improves drought tolerance in maize

  Molecular Breeding · 2025-02-01 · 6 citations

  articleOpen access1st authorCorresponding
  PublisherOA PDFDOI

• Effects and differences of various concentration techniques on the evolution of therapeutic components in Lushan geothermal water

  Scientific Reports · 2025-07-01

  articleOpen access

  .This study provides green, diversified, and value-enhancing technological support for the sustainable development of geothermal resources in Lushan.

  PublisherDOI

• Overexpression of the late embryonic genesis abundant protein MGL3 improves the drought tolerance of maize ( <i>Zea mays</i> L.)

  Crop Science · 2024-04-21 · 2 citations

  article

  Abstract With the increasing severity of climate change, drought has become a global issue that seriously restricts the development and production of crops. Maize ( Zea mays L.) is one of the major food crops in the world. Therefore, the demand for drought‐tolerant maize varieties has been rapidly increasing in the market. Recent studies have found that late embryogenesis abundant (LEA) proteins are involved in plant responses to various osmotic stresses such as drought and salt stress. Thus, we hypothesized that LEA genes may provide similar stress tolerance abilities in maize. We isolated ZmMGL3 of the LEA gene family and developed transgenic maize plants overexpressing ZmMGL3 using Agrobacterium‐mediated transformation. Then, we conducted physiological and biochemical evaluations of the transgenic maize plants exposed to drought stress. Under drought stress (10% polyethylene glycol 6000), the transgenic maize plants showed improved germination rate, seed vigor, radicle length, root length at the seedling stage, and wilting degree after drought and rewatering compared to the wild‐type plants. The transgenic plants also accumulated more catalase, superoxide dismutase, peroxidase, hydrogen peroxide, and superoxide radicals compared to the wild‐type plants. These results indicate that ZmMGL3 enhances drought resistance in maize plants by reducing the content of reactive oxygen species in the leaves and can be used as a candidate gene for the development of drought‐tolerant maize varieties.

  PublisherDOI

Frequent coauthors

• Yadan Guo

  13 shared

• Wenjie Ma

  East China University of Technology

  10 shared

• Zhanxue Sun

  East China University of Technology

  9 shared

• С. Л. Шварцев

  7 shared

• E.V. Zippa

  7 shared

• Siyan Liu

  5 shared

• Huanhuan Qin

  Xi'an University of Technology

  5 shared

• Shuyan Guan

  Jilin Agricultural University

  5 shared

Awards & honors

• Josiah Charles Trent Memorial Foundation Research Grant (200…
• Josiah Charles Trent Memorial Foundation Research Grant (200…
• Josiah Charles Trent Memorial Foundation Research Grant (199…