The journal published "Data-driven and probabilistic learning of the process-structure-property relationship in solution-grown tellurene for optimized nanomanufacturing of high-performance nanoelectronics" by Wu Group PhD students Yixiu Wang and Ruoxing Wang. Wenzhuo Wu, the Ravi and Eleanor Talwar Rising Star Assistant Professor of Industrial Engineering, and Arman Sabbaghi, Assistant Professor of Statistics, are corresponding authors.

This work aligns with Purdue’s "Giant Leaps" in Artificial Intelligence & Sustainability as part of Purdue's 150^th anniversary.

ABSTRACT
Two-dimensional (2-D) semiconductors have been intensely explored as alternative channel materials for future generation ultra-scaled transistor technology. However, significant roadblocks (e.g., poor carrier mobilities, instability, and vague potential in scaling-up) exist that prevent the realization of the current state-of-the-art 2-D materials' potential for energy-efficient electronics. The emergent solution-grown tellurene exhibits attractive attributes, e.g., high room-temperature mobility, large on-state current density, air-stability, and tunable material properties through a low-cost, scalable process, to tackle these challenges. Nevertheless, the fundamental manufacturing science of the hydrothermal processing for tellurene remains elusive. Here, we report on the first systematic, data-driven learning of the process-structure-property relationship in solution-grown tellurene, revealing the process factors' effects on tellurene's production yield, dimensions, and transistor-relevant properties, through a holistic approach integrating both the experimental explorations and data analytics. We further demonstrate the application of such fundamental knowledge for developing tellurene transistors with optimized and reliable performance, which can enable the cost-effective realization of high-speed, energy-efficient electronics.

Nano Energy is a multidisciplinary, rapid-publication forum of original peer-reviewed contributions on the science and engineering of nanomaterials and nanodevices used in all forms of energy harvesting, conversion, storage, utilization and policy.