Ali Javey (Advisor)

Research Advised by Professor Ali Javey

Javey Group:  List of Projects | List of Researchers

BPNX1022: Multimodal Gas Sensor Chip

Carla Bassil
Kichul Lee
2026

Gas sensing has long been an area of academic and industrial interest. However, state of the art sensors still lack selectivity and sensitivity when it comes to differentiating gases of similar compositions. In this work, we explore methods to create multiplexed gas sensors that can differentiate these mixtures with high accuracy and long-term stability.

Project is currently funded by: Federal

BPNX1051: Multifunctional Smart Contact Lens Sensing Platform

Yifei Zhan
2026

The evolution of contact lens technology is rapidly transforming these simple vision-correcting devices into advanced, multifunctional platforms. By embedding innovative sensor technologies onto contact lenses, it becomes possible to continuously monitor a person’s own well-being in a comfortable and non-invasive way. In this work, we explore the possibility of creating a multifunctional smart contact lens sensing platform that can one day help people easily track important health information, offering new ways to stay connected with their bodies without interrupting daily life.

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BPNX1028: Scalable Low-Temperature Processing of Chalcogen and Chalcogenide for Infrared Luminescence

Shu Wang
Naoki Higashitarumizu
2026

Scalable growth and processing of high-quality semiconductors, the active component of devices, is the foundation of modern electronics. We are interested in chalcogen and chalcogenide, with their appealing optical properties in infrared and potential low-temperature wafer-scale production, as promising material for optoelectronics. In this project, we develop new methods for controlled and scalable production of optically active tellurium, telluride, and other chalcogenide.

Project is currently funded by: Federal

BPNX1045: Scalable Bipolar Photodiodes for In-Sensor Spectral Computation

Jamie Geng
Dehui Zhang
Tyler Ferraro
Simon Starbuck
Dorottya Urmossy
2026

Machine learning enabled spectrometry has the potential to revolutionize fields like agriculture, field biology, and chemical metrology by allowing the identification of different targets in space via a spectral fingerprint. For example, fields of diseased crops requiring pesticides may show different reflectance spectra compared to healthy plants. However, current methods using a standard spectrometer and off-chip computer must acquire, transmit, then process complete reflectance or transmittance spectra, known as a hypercube, for every point of interest in space. This is costly in terms...

BPNX1044: Exploring Tellurium Compound‐Based p‐Type Channels for Various Functionalities

Taehoon Kim
I K M Reaz Rahman
Naoki Higashitarumizu
Inha Kim
Hyong Min Kim
Shu Wang
Robert Tseng
2026

​Tellurium-based materials (tellurides) are promising materials for p-channel transistors due to their compatibility with various elements and deposition methods. This versatility facilitates integration into diverse device architectures and enables the implementation of tailored electrical, thermal, optical, and structural properties. We investigate tellurium-based materials and their deposition techniques to optimize these multifaceted characteristics for advanced electronic applications.

Project is currently funded by: Federal

BPNX1011: Nanoscale Electronics with Tellurium

I K M Reaz Rahman
Naoki Higashitarumizu
Taehoon Kim
2026

Tellurium has a one-dimensional atomic structure that favors anisotropic electronic properties. Thermally evaporated tellurium has intrigued renewed interest in nanoscale electronics due to its near ambient crystallization, featuring single crystal orientation in micro-sized domain. Here we aim to study the performance limits of tellurium thin film transistors as we scale them to single grain domains. This will allow us to test the performance limits of tellurium transistors and pave the way for its viability for integration with standard silicon processes.

Project...

BPNX1060: Wearable On-Skin Chemical Sensing

Seung-Rok Kim
2026

We present a wearable platform for on-skin chemical sensing that enables continuous and real-time monitoring of metabolic activity. The device is designed to operate robustly during physical activities and under varying skin conditions, providing reliable measurements that may be useful for personalized health assessment.

Project is currently funded by: Industry Sponsored Research

BPNX1024: Reusable Sweat Rate Sensor

Seung-Rok Kim
Yifei Zhan
Noelle Davis
Suhrith Bellamkonda
2026

Sweat rate can provide the precautious signal of hyperhidrosis, hypohidrosis, and autonomic dysfunction. Currently, microfluidic and hygrometer-based sweat rate sensors are two types of available real-time sweat rate sensors. However, microfluidic device has issues of low temporal resolution, limited volume capacity, and surrounding artifact dependencies, while hygrometer-based devices also has overfilling and environmental artifact issues. In this work, we present reusable sweat rate sensor for continuous monitoring of sweat rate with novel sensor design.

Project...

BPN999: Wearable Sweat Sensors with High-Throughput Fabrication

Seung-Rok Kim
Noelle Davis
Pooja Mehta
Amanda King
Yullim Lee
Nicole Qing
2025

We have been developing sweat sensors to analyze physiological and metabolic health information, such as sweat rate, glucose levels, pH, and various electrolytes, from any surface on the body surface where sweat glands are present. However, the stiff sweat sensors developed so far struggle to detect subtle signal changes, especially on soft skin. This is due to a mechanical mismatch between the rigid sweat sensor and the pliable skin, which can lead to motion artifacts and delamination of the patch from skin. Specifically, the stiff sensor cannot easily stretch along with the...

BPNX1031: Scalable Infrared Photodetectors based on Large-Grain Tellurium Film

Hyong Min Kim
Naoki Higashitarumizu
Theodorus Jonathan Wijaya
2026

Infrared detection and imaging have a wide range of applications in thermal imaging, optical communication, gas sensing, and night vision. Currently, detection in the short-wave infrared (SWIR, 1 – 3 um) predominantly utilizes semiconducting materials such as single-crystalline germanium (Ge) and III-V semiconductors such as indium gallium arsenide phosphide (InGaAsP). The epitaxial growth of these materials often entails sophisticated methods that require high process temperatures and careful lattice matching with the substrate, making device fabrication costly and often poorly scaled....