A MAPbBr
Neuromorphic optoelectronic sensors with in-sensor computing architecture hold great promise for applications that require processing large amounts of redundant data, such as the Internet of Things, robotics, and environmental sciences, due to their advantages of low time latency and energy efficien...
Ausführliche Beschreibung
Autor*in: |
Zhang, Jingni [verfasserIn] Feng, Xianfeng [verfasserIn] Mei, Luyao [verfasserIn] Yu, Wenzhi [verfasserIn] Song, Han [verfasserIn] Cui, Nan [verfasserIn] Yun, Tinghe [verfasserIn] Mu, Haoran [verfasserIn] Lin, Shenghuang [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2023 |
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Schlagwörter: |
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Übergeordnetes Werk: |
Enthalten in: Materials and design - Amsterdam [u.a.] : Elsevier Science, 1980, 234 |
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Übergeordnetes Werk: |
volume:234 |
DOI / URN: |
10.1016/j.matdes.2023.112368 |
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Katalog-ID: |
ELV065308298 |
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520 | |a Neuromorphic optoelectronic sensors with in-sensor computing architecture hold great promise for applications that require processing large amounts of redundant data, such as the Internet of Things, robotics, and environmental sciences, due to their advantages of low time latency and energy efficiency. Halide perovskites, known for their extraordinary optoelectronic properties and stimuli-responsive characteristics, offer excellent opportunities for developing switchable visual sensors with high sensitivity, fast response, low energy consumption, and wide adaptive range. In this work, we successfully realized a MAPbBr3-PdSe2 heterojunction-based optoelectronic sensor, demonstrating a responsivity of 28 mA/W and a high specific detectivity of 5.2 × 1011 Jones. A fast response time of ∼ 25 μs has also been achieved. Additionally, we investigated the role of voltage-induced ion migration in actively adjusting the device's photoresponse capacity. Under 0 V bias, the device exhibited a wide switchable range of optical responsivity from 137.5% to 27000%, significantly surpassing pure perovskite-based devices in previous reports. Moreover, we demonstrated the device's adaptive learning capabilities and reproducible switching characteristics by simulating Pavlovian classical conditioned reflex experiments using electrical modulation. These findings open up exciting possibilities for next-generation artificial vision systems that are energy-efficient, adaptive, and capable of learning and effectively responding to varying visual conditions. | ||
650 | 4 | |a Vision sensor | |
650 | 4 | |a Halide perovskite | |
650 | 4 | |a Heterojunction | |
650 | 4 | |a Self-driven | |
700 | 1 | |a Feng, Xianfeng |e verfasserin |4 aut | |
700 | 1 | |a Mei, Luyao |e verfasserin |4 aut | |
700 | 1 | |a Yu, Wenzhi |e verfasserin |4 aut | |
700 | 1 | |a Song, Han |e verfasserin |4 aut | |
700 | 1 | |a Cui, Nan |e verfasserin |4 aut | |
700 | 1 | |a Yun, Tinghe |e verfasserin |4 aut | |
700 | 1 | |a Mu, Haoran |e verfasserin |4 aut | |
700 | 1 | |a Lin, Shenghuang |e verfasserin |0 (orcid)0000-0001-9552-4680 |4 aut | |
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773 | 1 | 8 | |g volume:234 |
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912 | |a GBV_ILN_4393 | ||
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2023 |
bklnumber |
51.00 51.32 |
publishDate |
2023 |
allfields |
10.1016/j.matdes.2023.112368 doi (DE-627)ELV065308298 (ELSEVIER)S0264-1275(23)00783-9 DE-627 ger DE-627 rda eng 600 690 VZ 51.00 bkl 51.32 bkl Zhang, Jingni verfasserin aut A MAPbBr 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Neuromorphic optoelectronic sensors with in-sensor computing architecture hold great promise for applications that require processing large amounts of redundant data, such as the Internet of Things, robotics, and environmental sciences, due to their advantages of low time latency and energy efficiency. Halide perovskites, known for their extraordinary optoelectronic properties and stimuli-responsive characteristics, offer excellent opportunities for developing switchable visual sensors with high sensitivity, fast response, low energy consumption, and wide adaptive range. In this work, we successfully realized a MAPbBr3-PdSe2 heterojunction-based optoelectronic sensor, demonstrating a responsivity of 28 mA/W and a high specific detectivity of 5.2 × 1011 Jones. A fast response time of ∼ 25 μs has also been achieved. Additionally, we investigated the role of voltage-induced ion migration in actively adjusting the device's photoresponse capacity. Under 0 V bias, the device exhibited a wide switchable range of optical responsivity from 137.5% to 27000%, significantly surpassing pure perovskite-based devices in previous reports. Moreover, we demonstrated the device's adaptive learning capabilities and reproducible switching characteristics by simulating Pavlovian classical conditioned reflex experiments using electrical modulation. These findings open up exciting possibilities for next-generation artificial vision systems that are energy-efficient, adaptive, and capable of learning and effectively responding to varying visual conditions. Vision sensor Halide perovskite Heterojunction Self-driven Feng, Xianfeng verfasserin aut Mei, Luyao verfasserin aut Yu, Wenzhi verfasserin aut Song, Han verfasserin aut Cui, Nan verfasserin aut Yun, Tinghe verfasserin aut Mu, Haoran verfasserin aut Lin, Shenghuang verfasserin (orcid)0000-0001-9552-4680 aut Enthalten in Materials and design Amsterdam [u.a.] : Elsevier Science, 1980 234 Online-Ressource (DE-627)32052857X (DE-600)2015480-X (DE-576)096806656 1873-4197 nnns volume:234 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 51.00 Werkstoffkunde: Allgemeines VZ 51.32 Werkstoffmechanik VZ AR 234 |
spelling |
10.1016/j.matdes.2023.112368 doi (DE-627)ELV065308298 (ELSEVIER)S0264-1275(23)00783-9 DE-627 ger DE-627 rda eng 600 690 VZ 51.00 bkl 51.32 bkl Zhang, Jingni verfasserin aut A MAPbBr 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Neuromorphic optoelectronic sensors with in-sensor computing architecture hold great promise for applications that require processing large amounts of redundant data, such as the Internet of Things, robotics, and environmental sciences, due to their advantages of low time latency and energy efficiency. Halide perovskites, known for their extraordinary optoelectronic properties and stimuli-responsive characteristics, offer excellent opportunities for developing switchable visual sensors with high sensitivity, fast response, low energy consumption, and wide adaptive range. In this work, we successfully realized a MAPbBr3-PdSe2 heterojunction-based optoelectronic sensor, demonstrating a responsivity of 28 mA/W and a high specific detectivity of 5.2 × 1011 Jones. A fast response time of ∼ 25 μs has also been achieved. Additionally, we investigated the role of voltage-induced ion migration in actively adjusting the device's photoresponse capacity. Under 0 V bias, the device exhibited a wide switchable range of optical responsivity from 137.5% to 27000%, significantly surpassing pure perovskite-based devices in previous reports. Moreover, we demonstrated the device's adaptive learning capabilities and reproducible switching characteristics by simulating Pavlovian classical conditioned reflex experiments using electrical modulation. These findings open up exciting possibilities for next-generation artificial vision systems that are energy-efficient, adaptive, and capable of learning and effectively responding to varying visual conditions. Vision sensor Halide perovskite Heterojunction Self-driven Feng, Xianfeng verfasserin aut Mei, Luyao verfasserin aut Yu, Wenzhi verfasserin aut Song, Han verfasserin aut Cui, Nan verfasserin aut Yun, Tinghe verfasserin aut Mu, Haoran verfasserin aut Lin, Shenghuang verfasserin (orcid)0000-0001-9552-4680 aut Enthalten in Materials and design Amsterdam [u.a.] : Elsevier Science, 1980 234 Online-Ressource (DE-627)32052857X (DE-600)2015480-X (DE-576)096806656 1873-4197 nnns volume:234 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 51.00 Werkstoffkunde: Allgemeines VZ 51.32 Werkstoffmechanik VZ AR 234 |
allfields_unstemmed |
10.1016/j.matdes.2023.112368 doi (DE-627)ELV065308298 (ELSEVIER)S0264-1275(23)00783-9 DE-627 ger DE-627 rda eng 600 690 VZ 51.00 bkl 51.32 bkl Zhang, Jingni verfasserin aut A MAPbBr 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Neuromorphic optoelectronic sensors with in-sensor computing architecture hold great promise for applications that require processing large amounts of redundant data, such as the Internet of Things, robotics, and environmental sciences, due to their advantages of low time latency and energy efficiency. Halide perovskites, known for their extraordinary optoelectronic properties and stimuli-responsive characteristics, offer excellent opportunities for developing switchable visual sensors with high sensitivity, fast response, low energy consumption, and wide adaptive range. In this work, we successfully realized a MAPbBr3-PdSe2 heterojunction-based optoelectronic sensor, demonstrating a responsivity of 28 mA/W and a high specific detectivity of 5.2 × 1011 Jones. A fast response time of ∼ 25 μs has also been achieved. Additionally, we investigated the role of voltage-induced ion migration in actively adjusting the device's photoresponse capacity. Under 0 V bias, the device exhibited a wide switchable range of optical responsivity from 137.5% to 27000%, significantly surpassing pure perovskite-based devices in previous reports. Moreover, we demonstrated the device's adaptive learning capabilities and reproducible switching characteristics by simulating Pavlovian classical conditioned reflex experiments using electrical modulation. These findings open up exciting possibilities for next-generation artificial vision systems that are energy-efficient, adaptive, and capable of learning and effectively responding to varying visual conditions. Vision sensor Halide perovskite Heterojunction Self-driven Feng, Xianfeng verfasserin aut Mei, Luyao verfasserin aut Yu, Wenzhi verfasserin aut Song, Han verfasserin aut Cui, Nan verfasserin aut Yun, Tinghe verfasserin aut Mu, Haoran verfasserin aut Lin, Shenghuang verfasserin (orcid)0000-0001-9552-4680 aut Enthalten in Materials and design Amsterdam [u.a.] : Elsevier Science, 1980 234 Online-Ressource (DE-627)32052857X (DE-600)2015480-X (DE-576)096806656 1873-4197 nnns volume:234 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 51.00 Werkstoffkunde: Allgemeines VZ 51.32 Werkstoffmechanik VZ AR 234 |
allfieldsGer |
10.1016/j.matdes.2023.112368 doi (DE-627)ELV065308298 (ELSEVIER)S0264-1275(23)00783-9 DE-627 ger DE-627 rda eng 600 690 VZ 51.00 bkl 51.32 bkl Zhang, Jingni verfasserin aut A MAPbBr 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Neuromorphic optoelectronic sensors with in-sensor computing architecture hold great promise for applications that require processing large amounts of redundant data, such as the Internet of Things, robotics, and environmental sciences, due to their advantages of low time latency and energy efficiency. Halide perovskites, known for their extraordinary optoelectronic properties and stimuli-responsive characteristics, offer excellent opportunities for developing switchable visual sensors with high sensitivity, fast response, low energy consumption, and wide adaptive range. In this work, we successfully realized a MAPbBr3-PdSe2 heterojunction-based optoelectronic sensor, demonstrating a responsivity of 28 mA/W and a high specific detectivity of 5.2 × 1011 Jones. A fast response time of ∼ 25 μs has also been achieved. Additionally, we investigated the role of voltage-induced ion migration in actively adjusting the device's photoresponse capacity. Under 0 V bias, the device exhibited a wide switchable range of optical responsivity from 137.5% to 27000%, significantly surpassing pure perovskite-based devices in previous reports. Moreover, we demonstrated the device's adaptive learning capabilities and reproducible switching characteristics by simulating Pavlovian classical conditioned reflex experiments using electrical modulation. These findings open up exciting possibilities for next-generation artificial vision systems that are energy-efficient, adaptive, and capable of learning and effectively responding to varying visual conditions. Vision sensor Halide perovskite Heterojunction Self-driven Feng, Xianfeng verfasserin aut Mei, Luyao verfasserin aut Yu, Wenzhi verfasserin aut Song, Han verfasserin aut Cui, Nan verfasserin aut Yun, Tinghe verfasserin aut Mu, Haoran verfasserin aut Lin, Shenghuang verfasserin (orcid)0000-0001-9552-4680 aut Enthalten in Materials and design Amsterdam [u.a.] : Elsevier Science, 1980 234 Online-Ressource (DE-627)32052857X (DE-600)2015480-X (DE-576)096806656 1873-4197 nnns volume:234 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 51.00 Werkstoffkunde: Allgemeines VZ 51.32 Werkstoffmechanik VZ AR 234 |
allfieldsSound |
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Zhang, Jingni @@aut@@ Feng, Xianfeng @@aut@@ Mei, Luyao @@aut@@ Yu, Wenzhi @@aut@@ Song, Han @@aut@@ Cui, Nan @@aut@@ Yun, Tinghe @@aut@@ Mu, Haoran @@aut@@ Lin, Shenghuang @@aut@@ |
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Zhang, Jingni |
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Neuromorphic optoelectronic sensors with in-sensor computing architecture hold great promise for applications that require processing large amounts of redundant data, such as the Internet of Things, robotics, and environmental sciences, due to their advantages of low time latency and energy efficiency. Halide perovskites, known for their extraordinary optoelectronic properties and stimuli-responsive characteristics, offer excellent opportunities for developing switchable visual sensors with high sensitivity, fast response, low energy consumption, and wide adaptive range. In this work, we successfully realized a MAPbBr3-PdSe2 heterojunction-based optoelectronic sensor, demonstrating a responsivity of 28 mA/W and a high specific detectivity of 5.2 × 1011 Jones. A fast response time of ∼ 25 μs has also been achieved. Additionally, we investigated the role of voltage-induced ion migration in actively adjusting the device's photoresponse capacity. Under 0 V bias, the device exhibited a wide switchable range of optical responsivity from 137.5% to 27000%, significantly surpassing pure perovskite-based devices in previous reports. Moreover, we demonstrated the device's adaptive learning capabilities and reproducible switching characteristics by simulating Pavlovian classical conditioned reflex experiments using electrical modulation. These findings open up exciting possibilities for next-generation artificial vision systems that are energy-efficient, adaptive, and capable of learning and effectively responding to varying visual conditions. |
abstractGer |
Neuromorphic optoelectronic sensors with in-sensor computing architecture hold great promise for applications that require processing large amounts of redundant data, such as the Internet of Things, robotics, and environmental sciences, due to their advantages of low time latency and energy efficiency. Halide perovskites, known for their extraordinary optoelectronic properties and stimuli-responsive characteristics, offer excellent opportunities for developing switchable visual sensors with high sensitivity, fast response, low energy consumption, and wide adaptive range. In this work, we successfully realized a MAPbBr3-PdSe2 heterojunction-based optoelectronic sensor, demonstrating a responsivity of 28 mA/W and a high specific detectivity of 5.2 × 1011 Jones. A fast response time of ∼ 25 μs has also been achieved. Additionally, we investigated the role of voltage-induced ion migration in actively adjusting the device's photoresponse capacity. Under 0 V bias, the device exhibited a wide switchable range of optical responsivity from 137.5% to 27000%, significantly surpassing pure perovskite-based devices in previous reports. Moreover, we demonstrated the device's adaptive learning capabilities and reproducible switching characteristics by simulating Pavlovian classical conditioned reflex experiments using electrical modulation. These findings open up exciting possibilities for next-generation artificial vision systems that are energy-efficient, adaptive, and capable of learning and effectively responding to varying visual conditions. |
abstract_unstemmed |
Neuromorphic optoelectronic sensors with in-sensor computing architecture hold great promise for applications that require processing large amounts of redundant data, such as the Internet of Things, robotics, and environmental sciences, due to their advantages of low time latency and energy efficiency. Halide perovskites, known for their extraordinary optoelectronic properties and stimuli-responsive characteristics, offer excellent opportunities for developing switchable visual sensors with high sensitivity, fast response, low energy consumption, and wide adaptive range. In this work, we successfully realized a MAPbBr3-PdSe2 heterojunction-based optoelectronic sensor, demonstrating a responsivity of 28 mA/W and a high specific detectivity of 5.2 × 1011 Jones. A fast response time of ∼ 25 μs has also been achieved. Additionally, we investigated the role of voltage-induced ion migration in actively adjusting the device's photoresponse capacity. Under 0 V bias, the device exhibited a wide switchable range of optical responsivity from 137.5% to 27000%, significantly surpassing pure perovskite-based devices in previous reports. Moreover, we demonstrated the device's adaptive learning capabilities and reproducible switching characteristics by simulating Pavlovian classical conditioned reflex experiments using electrical modulation. These findings open up exciting possibilities for next-generation artificial vision systems that are energy-efficient, adaptive, and capable of learning and effectively responding to varying visual conditions. |
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7.4010687 |