Research
Near-field deposition with atom-scale resolution

The goal of nanoscale scanning near-field deposition is to emulate CVD with a patterning resolution of 20~50nm. The project utilizes an STM with a tip capable of both delivering precursor and imaging the deposited substrate. The proposed tip architecture, currently in development, will carry a source chamber with a nanoscale nozzle and a current sensing tip fabricated from a silicon die. The precision deposition facilitated by this technology will allow the manufacture of custom nanoscale devices, including features such as precise placement of dopants or defects of various shapes. Furthermore, the ability to directly image during the deposition process aids understanding of surface diffusivity, migration length and adatom lifetimes during and after the manufacture of such custom devices.

Participants: Vamsi Nittala, Kyaw Zin Latt

Collaborators: Dr. Subramanian Sankaranarayanan, Dr. Saw Wai Hla, Dr. Nathan Guisinger — Argonne National Lab

Materials and devices for information processing — Microelectronics

Information processing involves energy conversion, energy transport, and energy storage. Microelectronics technology is widely applied in modern information processing, wherein electrons and holes are the fundamental carriers of energy. By manipulating the electrons and holes inside semiconductor materials, information may be efficiently stored, transferred, and exchanged. We are interested in developing information processing technologies with higher speeds and greater energy efficiency. To do this, we are studying the smart processing of information through use of novel material and device architectures. For example, nanosecond-level rapid single-photon detection can be realized by suitable integration of photodetectors and smart processing devices. To get to this point, this project explores aspects of bandgap engineering, material growth, material characterization, device fabrication, and device characterization.

Participants: Jiyuan Zheng

Collaborators: Prof. Joe C. Campbell, Dr. Xingjun Xue, Mr. Yuan Yuan, Dr. Keye Sun — The University of Virginia; Mr. Daniel Rosenmann — Argonne National Lab

Materials and devices for information processing — Quantum memory

Getting to the next generation of quantum technology will involve creating and characterizing new materials, developing new ways to interact with atoms, and engineering methods to fabricate devices to achieve such goals. Our lab works on all related aspects of this development cycle, with our strength in materials. One of our key interests is the development of quantum memory. This is a key piece of technology for future quantum communication networks. It's an exciting new area that we are collaborating on with many of our UChicago and Argonne colleagues.

Participants: Abhinav Prakash, Manish Kumar Singh, Gregory Grant

Collaborators: Dr. Gary Wolfowicz, Dr. Alan Dibos, Dr. F. Joseph Heremans — Argonne National Lab; Prof. David Awschalom, Prof. Tian Zhong, Prof. Peter Maurer — UChicago

Thoreau: Cyberphysical sensor networks and sensor technologies for water and soil

There is enormous need for monitoring and mapping soil and water quality at high spatial and temporal resolution, with consequences for soil and plant science and substiantial impact on globally relevant issues such as environmental management, food security, and human health. The geochemical and microbial cycling of soils, for example, are not well understood and there is need for more and better data in order to develop more accurate models of soil. Similarily, river and lake pollution, the prediction of pollution spread, compliance enforcement, and the effect of water quality on human health and socio-economic conditions can be much better understood with better data. Our research constitutes two parts: (i) the development of fully buried wireless underground cyberphysical sensor networks for soil monitoring and the development of mobile sensing platform based sensor networks for river and lake monitoring; and (ii), the development of better sensors using silicon photonics platforms and functionalization chemistry for difficult to measure parameters such as e. coli, total colliform and heavy metals in water, and dissolved nitrates in soil.

This research is conducted in collaboration with the AIFARMS Institute. See the link below for more details.

Particpants: Zhongbo Zhang, Manish Kumar Singh, Gregory Grant, Srinivasa Balivada

Collaborators: Dr. M. Ghosh, UChicago; Prof. A. Malani, UChicago; Dr. S. Chary, Administrative Staff College of India; Prof. S. Sarkar, Ambedkar U, India; Prof. T. Dutta, IIT-BHU, India; Prof. A. Gupta, IIEST Shibpur, India; Dr. P. Jamiwal, ATREE, India; Dr. X. Zhang and Dr. B. Dirroll, Argonne; Dr. S. Randhawa, IBM Research; SigFox

Lab Resources for Group Members

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