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2019 Featured Research: Advanced Materials

Spontaneous super-alignment of nano-objects

Innovation:   In an international collaborative effort, 
the Lin group and collaborators identified a unique mechanism, offered in nature, to spontaneously super-align nano-objects.

Impact:  Potential applications for the novel method include visible-UV photonics, nanolithography, and nanorobotics.

Electrostatic potential optimized molecular models

Innovation:  The Lin group also developed a set of molecular models - so-called electrostatic potential optimized molecular models (ESP-MMs) - to enable accurate predictions made by molecular simulations.

Impact:  This set of molecular models can be utilized by researchers in the computational materials community to facilitate the exploration of promising material candidates for gas separations.

Research Highlights:

  • Publications:  
    • Phys. Rev. Lett., 123, 238002, (2019).
    • J. Chem. Theory Comput., 15 (11), 6323-6332, (2019).
  • Recognition:
    • International Adsorption Society, Triennial Award for Excellence in Publications by a Young Member of the Society
    • Named the inaugural holder of the Umit S. Ozkan Professorship.

Development of a machine learning-based method for designing high-performance controllers

Innovation:   Joel Paulson created a method for executing advanced control algorithms at a rate faster than the millisecond scale. Inspired from recent advances in machine learning and control theory, the method uses deep learning to efficiently approximate the behavior of complex optimization-based control schemes, while still providing strong theoretical guarantees in the presence of constraints and uncertainty.



Impact:  The proposed approach provides a path toward achieving high-performance in emerging safety-critical control applications including those that have traditionally been treated as “too challenging” to solve using state-of-the-art control methods. Examples include the control of certain biomedical systems, unmanned vehicles, quadcopters, and humanoid robots. The method was recently demonstrated experimentally on an atmospheric pressure plasma device that can be used for biomedical purposes such as combating antibiotic-resistant bacteria, shrinking cancerous tumors, and accelerating the healing rate in chronic wounds.

Research Highlights:


  •  IEEE Control Systems Letters, 4:719-724, 2020.

  •  IFAC World Congress, 2020 (Accepted).

Cochlea-inspired interfacial nanowire structure-enabled design of stretchable electronics

Innovation:  Nature's method of detecting sound waves via the microscopic hairs in the ear inspired William Xiaoguang Wang to develop a material that helps reduce mechanical cracks in stretchable electronics. 

With the ultra-stretchability and ultra-sensitivity of these nanowire-structured surfaces, potential applications include the fabrication of wearable electronic devices for motion and sound detection and health monitoring. 


Impact:  This design improves the maximum detection range of stretchable electronic devices from 30% to 130% uniaxial elongation.


Highly efficient yolk-shell structured catalysts

Innovation:  Another innovation from Professor Wang was created by hyper cross-linking polymers for synthesis of hollow porous polymeric nanosphere frameworks (HPPNFS).

This approach involves encapsulation of ligand-free metal nanoparticles within the hyper-cross-linked HPPNFs, giving rise to remarkable catalytic activity as well as outstanding reusability toward hydrogenation. 

Impact:  This work informs the design of a class of responsive and functional soft materials for use in catalysis technology. It was featured on the cover of ACS Macro Letters.

Research Highlights:


  • Nature Communications, 10, 3862, (2019).
  • ACS Macro Letters8, 1263-1267, (2019). Cover feature.
  • Soft Matter, 16, 1463-1472. (2020).