The explosive growth of artificial intelligence has intensified demands for new computing paradigms beyond conventional von Neumann architectures.In response,brain-inspired computing-in-memory technologies are emergin...The explosive growth of artificial intelligence has intensified demands for new computing paradigms beyond conventional von Neumann architectures.In response,brain-inspired computing-in-memory technologies are emerging as a promising path forward.Here,we designed a two-terminal optical synaptic device utilizing organic heterojunctions doped with gold nanorods(AuNRs),leveraging the electric field enhancement innate to the localized surface plasmon resonance(LSPR)effect.The device doped with 1 wt%AuNRs demonstrates a markedly enhanced light absorption capacity in the near-infrared(NIR)region of 808 nm.The generation rate of photogenerated excitons increases by 16.8%,while the probability of exciton dissociation rises by 8.4%.The paired-pulse facilitation(PPF)index reaches 114.6%(Δt=1 s),indicating heightened sensitivity to optical pulse parameters.Additionally,Hall effect measurements were performed to characterize the electrical properties of the PEDOT:PSS:AuNRs films.The carrier mobility of the doped films increased 20-fold compared to pristine PEDOT:PSS due to electron injection from AuNRs.This enhanced mobility contributes to faster synaptic response and higher conductance tunability in the synapse device,further supporting its performance in neuromorphic computing tasks.Furthermore,we successfully simulated the dynamic“learning-forgetting-relearning”processes associated with human visual memory.By exploiting the tunable conductance of the optimized synaptic device,we implemented both convolutional neural networks(CNNs)and convolutional spiking neural networks(CSNNs)for weight updates.After 100 and 150 training epochs,the system achieved recognition accuracies up to 98.57%for handwritten digits and 92.01%for dynamic gestures.This work presents an effective plasmon-doping approach to enhancing the performance of organic memristors and can be extended to other material systems.展开更多
The CBR(Case-Based Reasoning)usually is been used to accomplish customized products by variant design or reusable design.In the CBR,retrieve is very important.A simple case retrieval method is been brought forward to ...The CBR(Case-Based Reasoning)usually is been used to accomplish customized products by variant design or reusable design.In the CBR,retrieve is very important.A simple case retrieval method is been brought forward to retrieve a opti-mal prototype based on using inputted multi-parameters,it can be programmed easily.An example has been proved this method can find optimal prototype for new design task efficiently.展开更多
Tuning the conjugated bridges between the electron-donor and electron-acceptor moieties plays a crucial role in enhancing the memristive properties of organic materials,yet it is rarely reported.Herein,we designed and...Tuning the conjugated bridges between the electron-donor and electron-acceptor moieties plays a crucial role in enhancing the memristive properties of organic materials,yet it is rarely reported.Herein,we designed and synthesized four donor-acceptor(D-A)organic small molecules,namely 4,7-bis(4-((9H-fluoren-9-ylidene)(phenyl)methyl)phenyl)benzo[c][1,2,5]thiadiazole(DF-BT),4,7-bis((4-((9H-fluoren-9-ylidene)(phenyl)methyl)phenyl)ethynyl)benzo[c][1,2,5]thiadiazole(DF-ynl-BT),4,7-bis(5-(4-((9H-fluoren-9-ylidene)(phenyl)methyl)phenyl)thiophen-2-yl)benzo[c][1,2,5]thiadiazole(DF-Th-BT),and 4,7-bis((5-(4-((9H-fluoren-9-ylidene)(phenyl)methyl)phenyl)thiophen-2-yl)ethynyl)benzo[c][1,2,5]thiadiazole(DF-Th-ynl-BT),featuring unique conjugated bridges.These molecules were employed as active layers in resistive random-access memory(RRAM)devices to systematically investigate the influence of conjugation bridges on the electrical parameters.The results revealed that devices based on DF-BT,DF-ynl-BT,and DF-Th-BT exhibited write-once-read-many-times(WORM)characteristics,while the DF-Th-ynl-BT-based device demonstrated stable Flash-type switching behavior.Compared to DF-BT,memory devices utilizing DF-ynl-BT,DF-Th-BT,and DF-Th-ynl-BT,which incorporate additional conjugated bridges,exhibited nonvolatile memory properties with reduced threshold voltages,an improved ON/OFF current ratio,enhanced stability,and better uniformity.These findings demonstrated that tailoring the conjugated bridges in D-A molecules can effectively modulate resistive memory behavior and enhance device performance.Furthermore,the DF-Th-ynl-BT-based device was successfully integrated into logic gate circuits and display functions,highlighting its significant potential for applications in artificial intelligence(AI)neural networks.展开更多
基金support from National Natural Science Foundation of China(Grant Numbers:62174116,61774109,and 92477120).
文摘The explosive growth of artificial intelligence has intensified demands for new computing paradigms beyond conventional von Neumann architectures.In response,brain-inspired computing-in-memory technologies are emerging as a promising path forward.Here,we designed a two-terminal optical synaptic device utilizing organic heterojunctions doped with gold nanorods(AuNRs),leveraging the electric field enhancement innate to the localized surface plasmon resonance(LSPR)effect.The device doped with 1 wt%AuNRs demonstrates a markedly enhanced light absorption capacity in the near-infrared(NIR)region of 808 nm.The generation rate of photogenerated excitons increases by 16.8%,while the probability of exciton dissociation rises by 8.4%.The paired-pulse facilitation(PPF)index reaches 114.6%(Δt=1 s),indicating heightened sensitivity to optical pulse parameters.Additionally,Hall effect measurements were performed to characterize the electrical properties of the PEDOT:PSS:AuNRs films.The carrier mobility of the doped films increased 20-fold compared to pristine PEDOT:PSS due to electron injection from AuNRs.This enhanced mobility contributes to faster synaptic response and higher conductance tunability in the synapse device,further supporting its performance in neuromorphic computing tasks.Furthermore,we successfully simulated the dynamic“learning-forgetting-relearning”processes associated with human visual memory.By exploiting the tunable conductance of the optimized synaptic device,we implemented both convolutional neural networks(CNNs)and convolutional spiking neural networks(CSNNs)for weight updates.After 100 and 150 training epochs,the system achieved recognition accuracies up to 98.57%for handwritten digits and 92.01%for dynamic gestures.This work presents an effective plasmon-doping approach to enhancing the performance of organic memristors and can be extended to other material systems.
基金Funded by the Scientific Foundation of Shanghai Automobile Industry(No.0212).
文摘The CBR(Case-Based Reasoning)usually is been used to accomplish customized products by variant design or reusable design.In the CBR,retrieve is very important.A simple case retrieval method is been brought forward to retrieve a opti-mal prototype based on using inputted multi-parameters,it can be programmed easily.An example has been proved this method can find optimal prototype for new design task efficiently.
基金supported by the financial support from the National Natural Science Foundation of China(Grant Nos.:62174116 and 61774109)the start-up fund from Shanghai University.
文摘Tuning the conjugated bridges between the electron-donor and electron-acceptor moieties plays a crucial role in enhancing the memristive properties of organic materials,yet it is rarely reported.Herein,we designed and synthesized four donor-acceptor(D-A)organic small molecules,namely 4,7-bis(4-((9H-fluoren-9-ylidene)(phenyl)methyl)phenyl)benzo[c][1,2,5]thiadiazole(DF-BT),4,7-bis((4-((9H-fluoren-9-ylidene)(phenyl)methyl)phenyl)ethynyl)benzo[c][1,2,5]thiadiazole(DF-ynl-BT),4,7-bis(5-(4-((9H-fluoren-9-ylidene)(phenyl)methyl)phenyl)thiophen-2-yl)benzo[c][1,2,5]thiadiazole(DF-Th-BT),and 4,7-bis((5-(4-((9H-fluoren-9-ylidene)(phenyl)methyl)phenyl)thiophen-2-yl)ethynyl)benzo[c][1,2,5]thiadiazole(DF-Th-ynl-BT),featuring unique conjugated bridges.These molecules were employed as active layers in resistive random-access memory(RRAM)devices to systematically investigate the influence of conjugation bridges on the electrical parameters.The results revealed that devices based on DF-BT,DF-ynl-BT,and DF-Th-BT exhibited write-once-read-many-times(WORM)characteristics,while the DF-Th-ynl-BT-based device demonstrated stable Flash-type switching behavior.Compared to DF-BT,memory devices utilizing DF-ynl-BT,DF-Th-BT,and DF-Th-ynl-BT,which incorporate additional conjugated bridges,exhibited nonvolatile memory properties with reduced threshold voltages,an improved ON/OFF current ratio,enhanced stability,and better uniformity.These findings demonstrated that tailoring the conjugated bridges in D-A molecules can effectively modulate resistive memory behavior and enhance device performance.Furthermore,the DF-Th-ynl-BT-based device was successfully integrated into logic gate circuits and display functions,highlighting its significant potential for applications in artificial intelligence(AI)neural networks.
