{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T15:13:47Z","timestamp":1778598827906,"version":"3.51.4"},"reference-count":20,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2024,10,2]],"date-time":"2024-10-02T00:00:00Z","timestamp":1727827200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The National Natural Science Foundation of China","award":["62004160"],"award-info":[{"award-number":["62004160"]}]},{"name":"The National Natural Science Foundation of China","award":["62201450"],"award-info":[{"award-number":["62201450"]}]},{"name":"The National Natural Science Foundation of China","award":["2023-YBGY-351"],"award-info":[{"award-number":["2023-YBGY-351"]}]},{"name":"The National Natural Science Foundation of China","award":["2023JH-GXRC-0024"],"award-info":[{"award-number":["2023JH-GXRC-0024"]}]},{"name":"The National Natural Science Foundation of China","award":["62004160"],"award-info":[{"award-number":["62004160"]}]},{"name":"The National Natural Science Foundation of China","award":["62201450"],"award-info":[{"award-number":["62201450"]}]},{"name":"The National Natural Science Foundation of China","award":["2023-YBGY-351"],"award-info":[{"award-number":["2023-YBGY-351"]}]},{"name":"The National Natural Science Foundation of China","award":["2023JH-GXRC-0024"],"award-info":[{"award-number":["2023JH-GXRC-0024"]}]},{"name":"The Key Research and Development Program of Shaanxi","award":["62004160"],"award-info":[{"award-number":["62004160"]}]},{"name":"The Key Research and Development Program of Shaanxi","award":["62201450"],"award-info":[{"award-number":["62201450"]}]},{"name":"The Key Research and Development Program of Shaanxi","award":["2023-YBGY-351"],"award-info":[{"award-number":["2023-YBGY-351"]}]},{"name":"The Key Research and Development Program of Shaanxi","award":["2023JH-GXRC-0024"],"award-info":[{"award-number":["2023JH-GXRC-0024"]}]},{"name":"Xi\u2019an Science and Technology Program","award":["62004160"],"award-info":[{"award-number":["62004160"]}]},{"name":"Xi\u2019an Science and Technology Program","award":["62201450"],"award-info":[{"award-number":["62201450"]}]},{"name":"Xi\u2019an Science and Technology Program","award":["2023-YBGY-351"],"award-info":[{"award-number":["2023-YBGY-351"]}]},{"name":"Xi\u2019an Science and Technology Program","award":["2023JH-GXRC-0024"],"award-info":[{"award-number":["2023JH-GXRC-0024"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper presents a thorough robust Class-AB power amplifier design and its application in pressure-mode sensor-on-chip nonlinearity correction. Considering its use in piezoresistive sensing applications, a gain-boosting-aided folded cascode structure is utilized to increase the amplifier\u2019s gain by a large amount as well as enhancing the power rejection ability, and a push\u2013pull structure with miller compensation, a floating gate technique, and an adaptive output driving limiting structures are adopted to achieve high-efficiency current driving capability, high stability, and electronic environmental compatibility. This amplifier is applied in a real sensor nonlinearity correction on-chip system. With the help of a self-designed 7-bit + sign DAC and a self-designed two-stage operational amplifier, this system is compatible with nonlinear correction at different signal conditioning output values. It can also drive resistive sensors as small as 300 ohms and as high as tens of thousands of ohms. The designed two-stage operational amplifier utilizes the TSMC 0.18 um process, resulting in a final circuit power consumption of 0.183 mW. The amplifier exhibits a gain greater than 140 dB, a phase margin of 68\u00b0, and a unit gain bandwidth exceeding 199.76 kHz. The output voltage range spans from 0 to 4.6 V. The final simulation results indicate that the nonlinear correction system designed in this paper can correct piezoresistive sensors with a nonlinearity of up to \u00b12.5% under various PVT (Process\u2013Voltage\u2013Temperature) conditions. After calibration by this system, the maximum error in the output voltage is 4 mV, effectively reducing the nonlinearity to 4% of its original value in the worst-case scenario.<\/jats:p>","DOI":"10.3390\/s24196395","type":"journal-article","created":{"date-parts":[[2024,10,2]],"date-time":"2024-10-02T06:27:31Z","timestamp":1727850451000},"page":"6395","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Piezoresistive-Sensor Nonlinearity Correction on-Chip Method with Highly Robust Class-AB Driving Capability"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9471-6904","authenticated-orcid":false,"given":"Kai","family":"Jing","sequence":"first","affiliation":[{"name":"School of Automation and Information Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China"},{"name":"Xi\u2019an Drawing Chips Corporation, Xi\u2019an 710048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-3111-3478","authenticated-orcid":false,"given":"Yuhang","family":"Han","sequence":"additional","affiliation":[{"name":"School of Automation and Information Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaoxiong","family":"Yuan","sequence":"additional","affiliation":[{"name":"School of Automation and Information Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rong","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Automation and Information Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiabo","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Automation and Information Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"765","DOI":"10.1007\/s11431-023-2456-1","article-title":"Ferroelectric-controlled graphene plasmonic surfaces for all-optical neuromorphic vision","volume":"76","author":"Chen","year":"2024","journal-title":"Sci. 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