Our primary goal of research is to combine computational and experimental approaches to explore the electronic, electrochemical, and mechanical properties of novel materials, to develop cost-effective routes to manufacturing advanced materials for biomedical, electronics, energy regeneration and storage applications.

A. Autonomous Manufacturing

A.1 Material Processing

Developing advanced materials by cost-effective routes is the key step for the various applications in electronics, energy conversion and storage. We have initiated or participated in the synthesis AND PROCESSINGof various nanomaterials such as graphene (Z. Yan, J. Lin et al. ACS Nano 2012 6(10), 9110-9117;  Z. Yan, Y. Liu, J. Lin et al.  JACS 2013, 135 (29), 10755–10762) and graphene-CNTs (R.K. Paul,  Small 2010 6(20), 2309-2313), graphene-ZnO (J. Lin et al. Small ,2010 6(21), 2448-2452), vertically aligned graphene nanoribbons (C. Zhang, Z. Peng, J. Lin, et al., ACS Nano, 2013, 7 (6), 5151–5159), graphene quantum dots (R. Ye, C. Xiang, J. Lin et al., Nat. Commun. 2013, 4, 2943), VO2 nanowires (J. Lin et al.,  Nano Lett.20149, 5445-5451) and WS2 nanoribbons (J. Lin et al.,  Adv. Energy Mater. 2014, 4 (10), 1301875). Furthermore, nanomaterials can be produced in large scale, which extends their applications in additive manufacturing. The techniques involved in these projects are listed in the following. Currently, the group gears toward development of high throughput and close-loop experimental setup for fully autonomous material synthesis and processing.

  • 3D, 4D printing
  • Laser processing
  • Colloidal Solution Synthesis
  • Chemical Vapor Deposition Synthesis (Vapor-Solid and Vapor-Liquid-Solid)


                         Z. Yan, J. Lin et al. ACS Nano 2012 6(10), 9110-9117       J. Lin, et al. Small 2010 6(21), 2448-2452

A.2 Materials Discovery Augmented with Artificial Intelligence

Enabled by the tremendous advances in computational capability by supercomputers, computational materials science goes to a new stage of opening an unprecedented opportunity to design new materials with targeted properties. It breaks the traditional trial-error materials development loop of synthesis, processing, and characterizations. The opportunity is to provide a real-time feedback to this loop. By this way it will reduce the time from discovery to deployment of new materials by a factor of two, as projected by Materials Genome Initiative for Global Competitiveness (MGI) announced by white house in 2011. It is also strongly tied to advancement of American manufacturing capability. We will utilize and extend current theory and models of materials towards a paradigm shift, in which computational hardware and software, coupled with experimental data, enable to design, discover, and develop new advanced materials and structures. In turn, we will create new advanced, innovative technologies. Our recent publication on MD simulation of graphene materials synthesis from polymers without metal catalysts was a good starting point (Y. Dong, et al. Carbon, 2016). Currently, we focus on developing models for autonomous material discovery and design augmented by artificial intelligence (AI).

B. Soft Materials

B.1 Integrated Programmable Materials and Devices for Biological Applications

Biological systems, such as the nastic plants, possess adaptive and predictable functions when exposed to various environmental stimuli (humidity, light, and touch), which results in dynamic morphology transformations governed by their compositions and anisotropic microstructures. The bio-mimicked shape-programmable systems have aroused interests in areas of smart textiles, micro-robotics, and metamaterials et al. Our research interest in this area is to synthesize and process novel materials to build a responsive and integrative systems. The goal is to understand their synthesis-processing-structure performance for application in biomedical areas.

B.2 Electronics and Optoelectronics

Electronics behavior differently when they are confined in low dimensions (1D and 2D) compared with the 3D bulk counterparts. Studying the electronics in the nanoscale paves the new route of developing next-generation electronics for applications in bioelectronics, photodetectors, transparent touch scree, memories and so on. Motivated by these applications we have studied the  interactions of DNA and graphene (J. Lin et al, Small2010, 6 (10), 1150-1155), demonstrated the potential applications of graphene for DNA biosensors (S. Guo, J. Lin et al., J.N.N. 2011 (6), 5258-5263). We have developed the transparent resistive switching memory based on SiOx and graphene (J. Yao*, J. Lin* et al., Nat. Commun., 2012, 3, 1101). This work has offered the possibility of providing the new functionality to the glass as it becomes the fundamental construction elements in modern buildings. We have reported addressable SiOx memory with 1D-1R architecture to solve the crosstalk problem in the crossbar devices (G. Wang, A. Lauchner, J. Lin et al., Adv. Mater. 2013, 25 (34), 4789-4793). We have studied the hydrogen diffusion in strong correlated VO2 nanowires ( J. Lin et al.,Nano Lett. 2014, 9, 5445-5451). Currently, we are working in the twoimensional layer transition metal dichalcogenides (LTMDs) such as MoS2, WSe2, SnS2, and SnSe2.

                                                                                J. Yao*, J. Lin*, et al. Nat. Commun. 2012, 3, 1101