[paper] Junctionless pH Sensing BioFET

Nawaz Shafi, Aasif Mohamad Bhat, Jaydeep, Singh Parmar, Chitrakant Sahu, C. Periasamy

Effect of geometry and temperature variations on sensitivity and linearity 

of junctionless pH sensing FET: An experimental study

Superlattices and Microstructures, p. 107186, Mar. 2022,

doi: 10.1016/j.spmi.2022.107186

   
* Malaviya National Institute of Technology Jaipur, India

Abstract: Here-in this work, boron doped poly-silicon based dimensional variants of thin film planar junctionless field effect transistors are fabricated through CMOS compatible process for pH detection. The dimensional variants are classified into two sets as set-1 (channel length, L = 100 μm) and set-2 (channel length, L = 120 μm) with widths of 3 μm, 5 μm, 10 μm, and 20 μm. Sensitivity of the fabricated devices is analyzed using phosphate buffer saline solutions of pH 3.1, 5.2, 7, 9 and 11.2 and is computed in terms of relative shift in threshold voltage (VTh) and maximum drain current (IDS). The reference VTh and IDS are taken at neutral pH 7. Here we have experimentally analyzed the effect on pH sensitivity by varying the device widths and temperatures from 30 °C to 50 °C. It is observed that varying the device width from 3 μm to 20 μm, VTh sensitivity reduces from 19.08% to 9.17% and from 16.03% to 8.5% for set-1 and set-2 devices respectively. Increasing temperature from 30 °C to 50 °C causes reduction of VTh sensitivity from 18.68% to 13.52% for device with W/L = 3μm/100 μm and 16.78%–10.99% for device with W/L = 3μm/120 μm. The reduction in width causes average VTh sensitivity to roll-off by 0.49%/μm and 0.26%/μm for L = 100 μm and L = 120 μm respectively. Also the increase in operating temperature from 30 °C to 50 °C leads VTh sensitivity to roll-off by 0.17%/°C and 0.2%/°C for W/L = 3μm/100 μm and W/L = 3μm/120 μm respectively.

Fig: Junctionless pH sensing BioFET

Acknowledgment: This work was supported by Center of Nano Science and Engineering, Indian Institute of Science, Bangalore under Indian Nanoelectronic Users Program. Authors express gratitude to Materials Research Center MNIT-Jaipur for characterization support.

[paper] Ion-Gated Transistors

Ion-Gated Transistor: An Enabler for Sensing and Computing Integration

Xianbao Bu, Han Xu, Dashan Shang, Yue Li, Hangbing Lv, and Qi Liu

Advanced Intelligent Systems, p.2000156.

DOI: 10.1002/aisy.202000156

Abstract: With the rapid development of the Internet of Things, the amount of data we involved in our daily life is growing exponentially, which poses significant challenges for data processing and transmission to the conventional terminal sensors that passively acquire external data. Inspired by biological sensory nervous systems, building artificial intelligent sensory systems with both sensing and computing capability is regarded as a promising way to address these challenges, by which the acquired data can be preprocessed locally and timely before transmitting them to the remote server for further processing. Ion-gated transistors (IGTs), which have been widely used in sensors and have been recently investigated for neuromorphic computing, exhibit great potential in this domain. Herein, the essential operation principles, device structures, and electrical characteristics of IGT are introduced, and the recent developments in biosensors, neuromorphic computing, and intelligent sensors with near-sensor computing and in-sensor computing modes are summarized. To conclude, the current challenges and future development of IGT for intelligent sensory systems are presented.

Fig: (a) Optical micrograph displaying the top view of an individual IGT (top right) and IGT array conforming to the surface of a human hand (bottom left). (b) Sample traces of in vivo signals acquired by IGTs, reflecting the wide span of frequency and amplitude characteristics.  

Acknowledgements: X.B. and H.X. contributed equally to this work. This work was supported by the National Key R&D Program of China under grant no. 2018YFA0701500; the National Natural Science Foundation of China under grant nos. 61874138, 61821091, 61825404, 61732020, and 61851402; the Strategic Priority Research Program of the Chinese Academy of Sciences under grant no. XDB44000000; Major Scientific Research Project of Zhejiang Lab (grant no. 2019KC0AD02); and Beijing Academy of Artificial Intelligence (BAAI).