Organic Synaptic Transistors with Environmentally Friendly Core/Shell Quantum Dots for Wavelength-Selective Memory and Neuromorphic Functions.

Organic transistors based on organic semiconductors together with quantum dots (QDs) are attracting more and more interest because both materials have excellent optoelectronic properties and solution processability. Electronics based on nontoxic QDs are highly desired considering the potential health risks but are limited by elevated surface defects, inadequate stability, and diminished luminescent efficiency. Herein, organic synaptic transistors based on environmentally friendly ZnSe/ZnS core/shell QDs with passivating surface defects are developed, exhibiting optically programmable and electrically erasable characteristics. The synaptic transistors feature linear multibit storage capability and wavelength-selective memory function with a retention time above 6000 s. Various neuromorphic applications, including memory enhancement, optical communication, and memory consolidation behaviors, are simulated. Utilizing an established neuromorphic model, accuracies of 92% and 91% are achieved in pattern recognition and complicated electrocardiogram signal processing, respectively. This research highlights the potential of environmentally friendly QDs in neuromorphic applications and health monitoring.

Cutoff values of axial length/corneal radius ratio for determining myopia vary with age among 3-18 years old children and adolescents.

PURPOSE: To investigate the effectiveness and cutoffs of axial length/corneal radius (AL/CR) ratio for myopia detection in children by age. METHODS: Totally, 21 kindergartens and schools were enrolled. Non-cycloplegic autorefraction (NCAR), axial length (AL), horizontal and vertical meridian of corneal radius (CR1, CR2), and cycloplegic autorefraction were measured. Receiver operating characteristic (ROC) curve was used to obtain the effectiveness and cutoff for myopia detection. RESULTS: Finally, 7803 participants aged 3-18 years with mean AL/CR ratio of 2.99 ± 0.16 were included. Area under the ROC curve (AUC) of AL/CR ratio for myopia detection (0.958 for AL/CR1, 0.956 for AL/CR2, 0.961 for AL/CR) was significantly larger than that of AL (0.919, all P < 0.001), while AUCs of the three were similar with different cutoffs (> 2.98, > 3.05, and > 3.02). When divided by age, the ROC curves of AL/CR ratio in 3- to 5-year-olds showed no significance or low accuracy (AUCs ≤ 0.823) in both genders. In ≥ 6-year-olds, the accuracies were promising (AUCs ≥ 0.883, all P < 0.001), the cutoffs basically increased with age (from > 2.93 in 6-year-olds to > 3.07 in 18-year-olds among girls, and from > 2.96 in 6-year-olds to > 3.07 in 18-year-olds among boys). In addition, boys presented slightly larger cutoffs than girls in all ages except for 16 and 18 years old. For children aged 3-5 years, AL/CR ratio or AL combined with NCAR increased AUC to > 0.900. CONCLUSION: AL/CR ratio provided the best prediction of myopia with age-dependent cutoff values for all but preschool children, and the cutoffs of boys were slightly larger than those of girls. For preschool children, AL/CR ratio or AL combined with NCAR is recommended to achieve satisfactory accuracy. AL/CR ratio calculated by two meridians showed similar predictive power but with different cutoffs.

Literature analysis of cutaneous adverse reactions induced by tislelizumab.

OBJECTIVE: Tislelizumab may induce immune-related adverse events, especially adverse skin events. Early detection and timely intervention of cutaneous adverse events are crucial to improve patients' quality of life and reduce the disruption of therapeutic regimens. This study aimed to determine the clinical characteristics of cutaneous adverse reactions to tislelizumab and offer a reference for its rational clinical use. METHODS: Case reports of cutaneous adverse reactions induced by tislelizumab were collected from the relevant databases (up to 31 March 2023). Patient age, sex, primary disease, medication use, occurrence of adverse skin conditions, treatment, and outcomes were recorded and descriptively analysed. RESULTS: A total of 13 patients were enrolled, including six males and seven females, aged 55-79 years, with a median age of 75 years and a mean age of 70.92 ± 8.84 years. The original disease was lung carcinoma in none patients, cervical carcinoma in two, and urothelial carcinoma and squamous cell carcinoma in one each. The time from the initiation of medication use to the occurrence of cutaneous adverse reactions ranged from 7 to 177 days. Among the 13 patients, 10 showed improvement after drug withdrawal or symptomatic treatment. Two patients died (one died of disease progression and multiorgan failure, one died of acute coronary syndrome), and one patient's adverse skin reactions persisted without treatment. CONCLUSIONS: Tislelizumab-related cutaneous adverse reactions mostly occur after several days to months of treatment. In clinical practice, evaluation and monitoring should be strengthened. More attention should be paid to erythema and rashes, which may be signs of serious adverse skin reactions. Early detection and intervention can ensure the safe use of drugs and provide greater clinical benefits to patients.

Retinal nerve fiber layer thinning as a novel fingerprint for cardiovascular events: results from the prospective cohorts in UK and China.

BACKGROUND: Retinal structural abnormalities have been found to serve as biomarkers for cardiovascular disease (CVD). However, the association between retinal nerve fiber layer (RNFL) thickness and the incidence of CVD events remains inconclusive, and relevant longitudinal studies are lacking. Therefore, we aimed to examine this link in two prospective cohort studies. METHODS: A total of 25,563 participants from UK Biobank who were initially free of CVD were included in the current study. Another 635 participants without retinopathy at baseline from the Chinese Guangzhou Diabetes Eye Study (GDES) were adopted as the validation set. Measurements of RNFL thickness in the macular (UK Biobank) and peripapillary (GDES) regions were obtained from optical coherence tomography (OCT). Adjusted hazard ratios (HRs), odd ratios (ORs), and 95% confidence intervals (CI) were calculated to quantify CVD risk. RESULTS: Over a median follow-up period of 7.67 years, 1281 (5.01%) participants in UK Biobank developed CVD events. Each 5-µm decrease in macular RNFL thickness was associated with an 8% increase in incident CVD risk (HR = 1.08, 95% CI: 1.01-1.17, p = 0.033). Compared with participants in the highest tertile of RNFL thickness, the risk of incident CVD was significantly increased in participants in the lowest thickness tertile (HR = 1.18, 95% CI: 1.01-1.38, p = 0.036). In GDES, 29 (4.57%) patients developed CVD events within 3 years. Lower average peripapillary RNFL thickness was also associated with a higher CVD risk (OR = 1.35, 95% CI: 1.11-1.65, p = 0.003). The additive net reclassification improvement (NRI) was 21.8%, and the absolute NRI was 2.0% by addition of RNFL thickness over the Framingham risk score. Of 29 patients with incident CVD, 7 were correctly reclassified to a higher risk category while 1 was reclassified to a lower category, and 21 high risk patients were not reclassified. CONCLUSIONS: RNFL thinning was independently associated with increased incident cardiovascular risk and improved reclassification capability, indicating RNFL thickness derived from the non-invasive OCT as a potential retinal fingerprint for CVD event across ethnicities and health conditions. TRIAL REGISTRATION: ISRCTN 15853192.

Central obesity and its association with retinal age gap: insights from the UK Biobank study.

BACKGROUND: Conflicting evidence exists on the association between ageing and obesity. Retinal age derived from fundus images has been validated as a novel biomarker of ageing. In this study, we aim to investigate the association between different anthropometric phenotypes based on body mass index (BMI) and waist circumference (WC) and the retinal age gap (retinal age minus chronological age). METHODS: A total of 35,550 participants with BMI, WC and qualified retinal imaging data available were included to investigate the association between anthropometric groups and retinal ageing. Participants were stratified into 7 different body composition groups based on BMI and WC (Normal-weight/Normal WC, Overweight/Normal WC, Mild obesity/Normal WC, Normal-weight/High WC, Overweight/High WC, Mild obesity/High WC, and Severe obesity/High WC). Linear regression and logistic regression models were fitted to investigate the association between the seven anthropometric groups and retinal age gap as continuous and categorical outcomes, respectively. RESULTS: A total of 35,550 participants (55.6% females) with a mean age 56.8 ± 8.04 years were included in the study. Individuals in the Overweight/High WC, Mild obesity/High WC and Severe obesity/High WC groups were associated with an increase in the retinal age gap, compared with those in the Normal Weight/Normal WC group (ß = 0.264, 95% CI: 0.105-0.424, P =0.001; ß = 0.226, 95% CI: 0.082-0.371, P = 0.002; ß = 0.273, 95% CI: 0.081-0.465, P = 0.005; respectively) in fully adjusted models. Similar findings were noted in the association between the anthropometric groups and retinal ageing process as a categorical outcome. CONCLUSION: A significant positive association exists between central obesity and accelerated ageing indexed by retinal age gaps, highlighting the significance of maintaining a healthy body shape.

Association of Retinal Age Gap and Risk of Kidney Failure: A UK Biobank Study.

RATIONALE & OBJECTIVE: The incidence of kidney failure is known to increase with age. We have previously developed and validated the use of retinal age based on fundus images as a biomarker of aging. However, the association of retinal age with kidney failure is not clear. We investigated the association of retinal age gap (the difference between retinal age and chronological age) with future risk of kidney failure. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: 11,052 UK Biobank study participants without any reported disease for characterizing retinal age in a deep learning algorithm. 35,864 other participants with retinal images and no kidney failure were followed to assess the association between retinal age gap and the risk of kidney failure. EXPOSURE: Retinal age gap, defined as the difference between model-based retinal age and chronological age. OUTCOME: Incident kidney failure. ANALYTICAL APPROACH: A deep learning prediction model used to characterize retinal age based on retinal images and chronological age, and Cox proportional hazards regression models to investigate the association of retinal age gap with incident kidney failure. RESULTS: After a median follow-up period of 11 (IQR, 10.89-11.14) years, 115 (0.32%) participants were diagnosed with incident kidney failure. Each 1-year greater retinal age gap at baseline was independently associated with a 10% increase in the risk of incident kidney failure (HR, 1.10 [95% CI, 1.03-1.17]; P=0.003). Participants with retinal age gaps in the fourth (highest) quartile had a significantly higher risk of incident kidney failure compared with those in the first quartile (HR, 2.77 [95% CI, 1.29-5.93]; P=0.009). LIMITATIONS: Limited generalizability related to the composition of participants in the UK Biobank study. CONCLUSIONS: Retinal age gap was significantly associated with incident kidney failure and may be a promising noninvasive predictive biomarker for incident kidney failure.

Brain and Cognition Signature Fingerprinting Vascular Health in Diabetic Individuals: An International Multi-Cohort Study.

OBJECTIVE: To evaluate the correlation between cognitive signatures and the risk of diabetic vascular complications and mortality, based on a multicountry prospective study. METHODS: The participants comprised 27,773 diabetics from the UK Biobank (UKB) and 1307 diabetics from the Guangzhou Diabetic Eye Study (GDES) cohort. The exposures were brain volume and cognitive screening tests for UKB participants, whilst the global cognitive score (GCS) measuring orientation to time and attention, episodic memory, and visuospatial abilities were determined for GDES participants. The outcomes for the UKB group were mortality, as well as macrovascular (myocardial infarction [MI] and stroke), microvascular (end-stage renal disease [ESRD], and diabetic retinopathy [DR]) events. The outcomes for the GDES group were retinal and renal microvascular damage. RESULTS: In the UKB group, a 1-SD reduction in brain gray matter volume was associated with 34%-77% higher risks of incident MI, ESRD, and DR. The presence of impaired memory was associated with 18%-73% higher risk of mortality and ESRD; impaired reaction was associated with 1.2-1.7-fold higher risks of mortality, stroke, ESRD, and DR. In the GDES group, the lowest GCS tertile exhibited 1.4-2.2-fold higher risk of developing referable DR and a twofold faster decline in renal function and retinal capillary density compared with the highest tertile. Restricting data analysis to individuals aged less than 65 years produced consistent results. CONCLUSION: Cognitive decline significantly elevates the risk of diabetic vascular complications and is correlated with retinal and renal microcirculation damage. Cognitive screening tests are strongly recommended as routine tools for management of diabetes.

Automatic and inverse design of broadband terahertz absorber based on optimization of genetic algorithm for dual metasurfaces.

In this study, we introduce a genetic algorithm (GA) into the catenary theory model to achieve automatic and inverse design for terahertz (THz) metasurface absorbers. The GA method was employed by seeking optimal dispersion distributions to achieve broadband impedance matching. A THz dual-metasurface absorber was designed using the proposed approach. The designed metasurface absorber exhibits an absorbance exceeding 88% at 0.21-5 THz. Compared to the traditional design method, the proposed method can reduce time consumption and find the optimal result to achieve high performance. The investigations provide important guidance and a promising approach for designing metasurface-based devices for practical applications.

Highly Sensitive Artificial Visual Array Using Transistors Based on Porphyrins and Semiconductors.

Artificial visual systems with image sensing and storage functions have considerable potential in the field of artificial intelligence. Light-stimulated synaptic devices can be applied for neuromorphic computing to build artificial visual systems. Here, optoelectronic synaptic transistors based on 5,15-(2-hydroxyphenyl)-10,20-(4-nitrophenyl)porphyrin (TPP) and dinaphtho[2,3-b:2',3'-f ]thieno[3,2-b]thiophene (DNTT) are demonstrated. By utilizing stable TPP with high light absorption, the number of photogenerated carriers in the transport layer can be increased significantly. The devices exhibit high photosensitivity and tunable synaptic plasticity. The synaptic weight can be effectively modulated by the intensity, width, and wavelength of the light signals. Due to the high light absorption of TPP, an ultrasensitive artificial visual array based on these devices is developed, which can detect weak light signals as low as 1 µW cm-2 . Low-voltage operation is further demonstrated. Even with applied voltages as low as -70 µV, the devices can still show obvious responses, leading to an ultralow energy consumption of 1.4 fJ. The devices successfully demonstrate image sensing and storage functions, which can accurately identify visual information. In addition, the devices can preprocess information and achieve noise reduction. The excellent synaptic behavior of the TPP-based electronics suggests their good potential in the development of new intelligent visual systems.

Degradable Photonic Synaptic Transistors Based on Natural Biomaterials and Carbon Nanotubes.

Artificial synaptic devices have potential for overcoming the bottleneck of von Neumann architecture and building artificial brain-like computers. Up to now, developing synaptic devices by utilizing biocompatible and biodegradable materials in electronic devices has been an interesting research direction due to the requirements of sustainable development. Here, a degradable photonic synaptic device is reported by combining biomaterials chlorophyll-a and single-walled carbon nanotubes (SWCNTs). Several basic synaptic functions, including excitatory postsynaptic current (EPSC), paired pulse facilitation (PPF), transition from short-term memory (STM) to long-term memory (LTM), and learning and forgetting behaviors, are successfully emulated through the chlorophyll-a/SWCNTs synaptic device. Furthermore, decent synaptic behaviors can still be achieved at a low drain voltage of -0.0001 V, which results in quite low energy consumption of 17.5 fJ per pulse. Finally, the degradability of this chlorophyll-a/SWCNTs transistor array is demonstrated, indicating that the device can be environmentally friendly. This work provides a new guide to the development of next-generation green and degradable neuromorphic computing electronics.

Correlations between the ECD spectra and absolute configuration of bridged-ring lactones: revisiting Beecham's rule.

Bridged lactones frequently appear as structural fragments in natural products. To elucidate their stereochemistry using electronic circular dichroism (ECD) spectra, Beecham correlated the sign of the Cotton effect (CE) from the n → π* transition of lactones at approximately 220 nm with the skeleton of bridged lactones. By combining experimental and theoretical ECD analyses of various bridged lactones using time-dependent density functional theory calculations and a methodology for extracting core structures, Beecham's rule was revisited and revised to define the scope of application. Both the position of the ß-C atom in the larger lactone system and the additive contribution of groups at ß-C exerted effects on the sign of the CE. The revised rule provides an alternative way to interpret experimental ECD data in addition to quantum-chemical calculation for various bridged lactones.

Nattokinase crude extract enhances oral mucositis healing.

BACKGROUND: Nattokinase (NK) is a promising alternative in the prevention and treatment of cardiovascular diseases due to its potent fibrinolytic activity. In this study, we investigated the effect of crude nattokinase extract on the healing of acetic acid-induced oral mucositis in mice. METHODS: Bacillus subtilis culture media (BSCM) was isolated into the supernatant, named nattokinase crude extract (NCE), and the pellet was named Bacillus subtilis mass (BSM). An oral mucositis model was established in mice by applying 50% glacial acetic acid to the buccal mucosa. According to the treatment conditions, the mice were divided into BSCM, NCE, BSM and phosphate buffered saline (PBS) groups. The weight of the mice, oral mucositis healing score and histopathological examination were used to evaluate the treatment. RESULTS: Fibrinolytic activities of BSCM, NCE and BSM were approximately 8069, 10,800 and 80 U/ml, respectively. The weight gain of mice in the NCE group was significantly different from the PBS group after three days' treatment (p < 0.05). The oral mucositis score of NCE group was significantly higher than other groups (p < 0.05). The differences in histopathology scores between the NCE and other groups were statistically significant (p < 0.01). CONCLUSIONS: NCE could possess remarkable potential to reduce pain and promote oral mucositis healing with minimal safety concerns. In this study, we first report that NCE from the supernatant of Bacillus subtilis can promote the healing of oral mucositis, which extends the application scope of NK.

Base-promoted domino radical cyclization of 1,6-enynes.

A good regioselective, high atom-economical and transition-metal-free method for the synthesis of α-functionalized ether derivatives via the domino radical cyclization of 1,6-enynes is described. A series of α-functionalized ether derivatives could be easily obtained in good yields with wide functional group tolerance by using less toxic and inexpensive Cs2CO3 as the base. The control experiment results show that the reaction involves a radical process. This strategy provides a regioselective way toward the formation of dual C-C bonds in one step.

Influence of Surface Functional Groups on Deposition and Release of TiO2 Nanoparticles.

A clear understanding of the factors governing the deposition and release behaviors of engineered nanoparticles (NPs), such as TiO2 NPs, is necessary for predicting their transport and fate in both natural and engineered aquatic environments. In this study, impacts of specific chemistries on TiO2 NP deposition, as a function of TiO2 NP concentration and ionic strength/valence, were investigated using self-assembled monolayers (SAMs) with five different ending chemical functionalities (-CH3, -OH, -COOH, -NH2, and -CONH2). The fastest deposition and maximum deposition mass were observed on -NH2, followed by -COOH, -CONH2, -CH3, and -OH, showing that contact angle and zeta potential of surfaces were not good indicators for predicting the deposition. Specific interactions, for instance, between -COOH and -CONH2 and TiO2, significantly affected their deposition. Deposition rate increased linearly with TiO2 NP concentration; however, specific deposition rate was dependent on the type of SAMs. The increase of monovalent (Na+) and divalent (Ca2+) led to different changes in deposition rates for the SAMs due to different functionalities. Results also showed that favorable SAM (e.g., -NH2) had lowered release of NPs compared to unfavorable surface (e.g., -OH). The obtained deposition and release behaviors will support more accurate prediction of the environmental fate of nanoparticles.

Retinal age gap as a predictive biomarker for future risk of clinically significant diabetic retinopathy.

AIMS: Retinal age derived from fundus images has been verified as a novel ageing biomarker. We aim to explore the association between retinal age gap (retinal age minus chronological age) and incident diabetic retinopathy (DR). METHODS: Retinal age prediction was performed by a deep learning model, trained and validated based on 19,200 fundus images of 11,052 disease-free participants. Retinal age gaps were determined for 2311 patients with diabetes who had no history of diabetic retinopathy at baseline. DR events were ascertained by data linkage to hospital admissions. Cox proportional hazards regression models were performed to evaluate the association between retinal age gaps and incident DR. RESULTS: During the median follow-up period of 11.0 (interquartile range: 10.8-11.1) years, 183 of 2311 participants with diabetes developed incident DR. Each additional year of the retinal age gap was associated with a 7% increase in the risk of incident DR (hazard ratio [HR] = 1.07, 95% confidence interval [CI] 1.02-1.12, P = 0.004), after adjusting for confounding factors. Participants with retinal age gaps in the fourth quartile had a significantly higher DR risk compared to participants with retinal age gaps in the lowest quartile (HR = 2.88, 95% CI 1.61-5.15, P < 0.001). CONCLUSIONS: We found that higher retinal age gap was associated with an increased risk of incident DR. As an easy and non-invasive biomarker, the retinal age gap may serve as an informative tool to facilitate the individualized risk assessment and personalized screening protocol for DR.

Stretchable and neuromorphic transistors for pain perception and sensitization emulation.

Pain perception nociceptors (PPN), an important type of sensory neuron, are capable of sending out alarm signals when the human body is exposed to destructive stimuli. Simulating the human ability to perceive the external environment and spontaneously avoid injury is a critical function of neural sensing of artificial intelligence devices. The demand for developing artificial PPN has subsequently increased. However, due to the application scenarios of bionic electronic devices such as human skin, electronic prostheses, and robot bodies, where a certain degree of surface deformation constantly occurs, the ideal artificial PPN should have the stretchability to adapt to real scenarios. Here, an organic semiconductor nanofiber artificial pain perception nociceptor (NAPPN) based on a pre-stretching strategy is demonstrated to achieve key pain aspects such as threshold, sensitization, and desensitization. Remarkably, while stretching up to 50%, the synaptic behaviors and injury warning ability of NAPPN can be retained. To verify the wearability of the device, NAPPN was attached to a curved human finger joint, on which PPN behaviors were successfully mimicked. This provides a promising strategy for realizing neural sensing function on either deformed or mobile electronic devices.

Humidity/Oxygen-Insensitive Organic Synaptic Transistors Based on Optical Radical Effect.

For most organic synaptic transistors based on the charge trapping effect, different atmosphere conditions lead to significantly different device performance. Some devices even lose the synaptic responses under vacuum or inert atmosphere. The stable device performance of these organic synaptic transistors under varied working environments with different humidity and oxygen levels can be a challenge. Herein, a moisture- and oxygen-insensitive organic synaptic device based on the organic semiconductor and photoinitiator molecules is reported. Unlike the widely reported charge trapping effect, the photoinduced free radical is utilized to realize the photosynaptic performance. The resulting synaptic transistor displays typical excitatory postsynaptic current, paired-pulse facilitation, learning, and forgetting behaviors. Furthermore, the device exhibits decent and stable photosynaptic performances under high humidity and vacuum conditions. This type of organic synaptic device also demonstrates high potential in ultraviolet B perception based on its environmental stability and broad ultraviolet detection capability. Finally, the contrast-enhanced capability of the device is successfully validated by the single-layer-perceptron/double-layer network based Modified National Institute of Standards and Technology pattern recognition. This work could have important implications for the development of next-generation environment-stable organic synaptic devices and systems.

Development and validation of a smartwatch algorithm for differentiating physical activity intensity in health monitoring.

To develop and validate a machine learning based algorithm to estimate physical activity (PA) intensity using the smartwatch with the capacity to record PA and determine outdoor state. Two groups of participants, including 24 adults (13 males) and 18 children (9 boys), completed a sequential activity trial. During each trial, participants wore a smartwatch, and energy expenditure was measured using indirect calorimetry as gold standard. The support vector machine algorithm and the least squares regression model were applied for the metabolic equivalent (MET) estimation using raw data derived from the smartwatch. Exercise intensity was categorized based on MET values into sedentary activity (SED), light activity (LPA), moderate activity (MPA), and vigorous activity (VPA). The classification accuracy was evaluated using area under the ROC curve (AUC). The METs estimation accuracy were assessed via the mean absolute error (MAE), the correlation coefficient, Bland-Altman plots, and intraclass correlation (ICC). A total of 24 adults aged 21-34 years and 18 children aged 9-13 years participated in the study, yielding 1790 and 1246 data points for adults and children respectively for model building and validation. For adults, the AUC for classifying SED, MVPA, and VPA were 0.96, 0.88, and 0.86, respectively. The MAE between true METs and estimated METs was 0.75 METs. The correlation coefficient and ICC were 0.87 (p < 0.001) and 0.89, respectively. For children, comparable levels of accuracy were demonstrated, with the AUC for SED, MVPA, and VPA being 0.98, 0.89, and 0.85, respectively. The MAE between true METs and estimated METs was 0.80 METs. The correlation coefficient and ICC were 0.79 (p < 0.001) and 0.84, respectively. The developed model successfully estimated PA intensity with high accuracy in both adults and children. The application of this model enables independent investigation of PA intensity, facilitating research in health monitoring and potentially in areas such as myopia prevention and control.

Organic High-Temperature Synaptic Phototransistors for Energy-Efficient Neuromorphic Computing.

Organic optoelectronic synaptic devices that can reliably operate in high-temperature environments (i.e., beyond 121°C) or remain stable after high-temperature treatments have significant potential in biomedical electronics and bionic robotic engineering. However, it is challenging to acquire this type of organic devices considering the thermal instability of conventional organic materials and the degradation of photoresponse mechanisms at high temperatures. Here, high-temperature synaptic phototransistors (HTSPs) based on thermally stable semiconductor polymer blends as the photosensitive layer are developed, successfully simulating fundamental optical-modulated synaptic characteristics at a wide operating temperature range from room temperature to 220°C. Robust optoelectronic performance can be observed in HTSPs even after experiencing 750 h of the double 85 testing due to the enhanced operational reliability. Using HTSPs, Morse-code optical decoding scheme and the visual object recognition capability are also verified at elevated temperatures. Furthermore, flexible HTSPs are fabricated, demonstrating an ultralow power consumption of 12.3 aJ per synaptic event at a low operating voltage of -0.05 mV. Overall, the conundrum of achieving reliable optical-modulated neuromorphic applications while balancing low power consumption can be effectively addressed. This research opens up a simple but effective avenue for the development of high-temperature and energy-efficient wearable optoelectronic devices in neuromorphic computing applications.

All-Photolithography Fabrication of Ion-Gated Flexible Organic Transistor Array for Multimode Neuromorphic Computing.

Organic ion-gated transistors (OIGTs) demonstrate commendable performance for versatile neuromorphic systems. However, due to the fragility of organic materials to organic solvents, efficient and reliable all-photolithography methods for scalable manufacturing of high-density OIGT arrays with multimode neuromorphic functions are still missing, especially when all active layers are patterned in high-density. Here, a flexible high-density (9662 devices per cm2) OIGT array with high yield and minimal device-to-device variation is fabricated by a modified all-photolithography method. The unencapsulated flexible array can withstand 1000 times' bending at a radius of 1 mm, and 3 months' storage test in air, without obvious performance degradation. More interesting, the OIGTs can be configured between volatile and nonvolatile modes, suitable for constructing reservoir computing systems to achieve high accuracy in classifying handwritten digits with low training costs. This work proposes a promising design of organic and flexible electronics for affordable neuromorphic systems, encompassing both array and algorithm aspects.