学术成果

期刊论文

  1. Gong, W., et al. (2024). “Deep Learning Assisted Bandgap Prediction in 2D Materials”. Nature Computational Science 4(3): 210-218
  2. Li, M., Gong, W., et al. (2023). “Quantum Transport in MoS2/WSe2 Heterostructures”. Physical Review B 107(15): 155412
  3. Gong, W., et al. (2022). “Machine Learning Potential for MXene Materials”. npj Computational Materials 8: 45

会议报告

展示会议报告时间线

library(ggplot2) library(lubridate)

conferences <- data.frame( event = c(“MRS Fall Meeting”, “APS March Meeting”, “ICMAT”), date = ymd(c(“2023-12-01”, “2024-03-15”, “2024-06-20”)), location = c(“Boston, USA”, “Los Angeles, USA”, “Singapore”) )

ggplot(conferences, aes(x = date, y = event)) + geom_point(size = 3, color = “#2c3e50”) + geom_segment(aes(xend = date, yend = event), x = min(conferences$date), linetype = “dashed”, color = “grey70”) + theme_minimal() + labs(x = “日期”, y = ““) + scale_x_date(date_labels =”%Y-%m”)