A Large-Area RFID Reader Array Using Large-Area Electronics

Web Published:

Docket# Princeton 18-3454-1


A broad range of technologies and applications are being considered for IoT. RFID holds great promise in this regard due to its potential scale of deployment. However, short wireless range in passive HF RFID and the need for battery powering in active UHF RFID pose major limitations.


Researchers at Princeton University have invented a novel large-area RFID reader array technology using large-area electronics, employing zinc oxide (ZnO) thin-film transistors (TFTs). The device enables RFID readers to be fabricated scalably as large arrays on thin flexible sheets. The large and thin sheets could be used for lining everyday surfaces, thereby enabling detection and localization of objects bearing RFID tags.


The above large-area RFID reader array technology is based on low-temperature processed thin-film transistors. This novel TFT topology enables high frequency operation and power transfer at RFID frequencies. Operation of this device was demonstrated with commercial ISO14443 13.56MHz tags, employing a tag-talks-first (TTF) protocol, to maximize readout speed. Using in-house fabricated TFTs, the 25-element array operated from a VDD of 4.7V, with readout speed of 5.5ms per element (set by the tag), and total power consumption of <70mW. Researchers have implement an RFID element and RFID array, using Princeton cleanroom facility. Full RFID reader operation is demonstrated.


The device can be employed, inter alia, to enable IoT systems. It can enable smart interactive spaces, wherein human activities can be inferred from the placement of objects in the environment, which holds great promise due to the value it brings to machine learning algorithms. It could be integrated in everyday surfaces directly or as a liner, to unobtrusively detect/localize objects bearing passive tags, over large areas.



•       Enables the detection and localization of objects bearing RFID tags, placed on everyday surfaces

•       Enable smart interactive spaces, wherein human activities can be inferred from the placement of objects in the environment



•       Unobtrusive

•       RFID reader can be fabricated scalably as large arrays on thin, possibly flexible sheets

•       Can be integrated into everyday surfaces or as a liner

•       Can be retrofit onto existing surfaces

•       Uses a TTF protocol for maximum readout speed


Stage of Development

The researchers have implemented an RFID reader element and RFID reader array, using Princeton cleanroom facility. Full RFID reader operation is demonstrated.






Jonathan Mehlman is a Francis Robbins Upton Fellow at Princeton University and is pursuing a PhD in electrical engineering. He graduated from Yeshiva University in 2014, suma cum laude, as part of the Jay and Jeanie Schottenstein Honors Program, with a double B.A. in physics and math, and received his M.A in electrical engineering in 2016 from Princeton University. His research focuses on advancements in metal-oxide thin film transistor technology for large-area electronics applications.


Prakhar Kumar received his B.E. (Hons) in Electrical and Electronics Engineering from BITS Pilani, Pilani Campus, India in 2016. He is currently pursuing a PhD in electrical engineering. Prakhar’s research focuses on developing hybrid sensing systems by bringing together Large Area Electronics (LAE) and CMOS VLSI technologies. More specifically, he is interested in designing technology platforms that can enable machine learning algorithms to carry out inference and state estimation tasks effectively.


Naveen Verma received the B.A.Sc. degree in Electrical and Computer Engineering from the UBC, Vancouver, Canada in 2003, and the M.S. and Ph.D. degrees in Electrical Engineering from MIT in 2005 and 2009, respectively. Since July 2009 he has been with the Department of Electrical Engineering at Princeton University, where he is currently an Associate Professor. His research focuses on advanced sensing systems, exploring how systems for learning, inference, and action planning can be enhanced by algorithms that exploit new sensing and computing technologies. This includes research on large-area, flexible sensors, energy-efficient statistical-computing architectures and circuits, and machine-learning and statistical-signal-processing algorithms. Prof. Verma has served as a Distinguished Lecturer of the IEEE Solid-State Circuits Society, and currently serves on the technical program committees for ISSCC, VLSI Symp., DATE, and IEEE Signal-Processing Society (DISPS). Prof. Verma is recipient or co-recipient of the 2006 DAC/ISSCC Student Design Contest Award, 2008 ISSCC Jack Kilby Paper Award, 2012 Alfred Rheinstein Junior Faculty Award, 2013 NSF CAREER Award, 2013 Intel Early Career Award, 2013 Walter C. Johnson Prize for Teaching Excellence, 2013 VLSI Symp. Best Student Paper Award, 2014 AFOSR Young Investigator Award, 2015 Princeton Engineering Council Excellence in Teaching Award, and 2015 IEEE Trans. CPMT Best Paper Award.


James C. Sturm is the Stephen R. Forrest Professor of Electrical Engineering at Princeton University. He received his B.S.E. in Electrical Engineering (engineering physics) from Princeton University in 1979, and an M.S.E.E and PhD in Electrical Engineering from Stanford University in 1981 and 1985, respectively. Prof. Sturm’s research interests include electronic devices and materials, large-area/flexible electronics and systems, photovoltaics, quantum computing, biological/medical applications of microfabrication, silicon-based hetero- and nanostructures and devices, manufacturing science for VLSI, chemical vapor deposition, thin film transistors, organic semiconductors and LED’s, and engineering education. He was the Founding Director of the Princeton Institute for the Science and Technology of Materials, and currently serves as the Co-Founder of Space-Touch Inc. and Co-Director of the Princeton Program in Plasma Science and Technology (PPST). Prof. Sturm is the recipient of the 1987 NSF Presidential Young Investigator Award, the 1990 Walter Curtis Johnson Award, the 1993 Lifetime Achievement Award for Teaching, the 1994 W.M. Keck Foundation Award for Engineering Teaching Excellence, the 1999 Princeton University SEAS Dean’s Distinguished Teaching Award, and the 2004 President’s Distinguished Teaching Award. He served as the General Chair of the International Silicon-Germanium Technology and Device meeting in 2006, was elected to Board of Directors of Materials Research Society for 2007-2009, and was elected to the New Jersey High Tech Hall of Fame in 2008.


Intellectual Property Status

Patent protection is pending.


Princeton University is currently looking for industry collaborators to further develop and commercialize this technology.



Chris Wright

Princeton University Office of Technology Licensing • (609) 258-5579• cw20@princeton.edu


Tania DasBanerjee

Princeton University Office of Technology Licensing • (609) 258-3798• taniab@princeton.edu



Patent Information:
For Information, Contact:
Chris Wright
Licensing Associate
Princeton University
Jonathan (Yoni) Mehlman
Prakhar Kumar
Naveen Verma
James Sturm