This PDF file contains the front matter associated with SPIE Proceedings Volume 12661, including the Title Page, Copyright information, Table of Contents and Conference Committee lists.

With the increasing demand in using electronic noses (e-noses) for various medical, industrial, and military applications, the technology of such devices is still struggling with the limitations in the gas sensors. Particularly, a limitation is in the relatively poor sensitivity and selectivity of the commercially available sensors for measuring the concentrations of various gases and volatile organic compounds (VOCs). The shortcoming has been addressed by employing machine learning (ML) methods to analyze signals from an array of gas sensors. However, with different ML models, it is required to study the effect of different models on data interpretation. In this study, we have designed a microcontroller-based system equipped with eight different gas/VOC sensors, designed for detecting CO₂, O₂, CO, NO, NO₂, NH₃, alcohol, and acetone. The sensors were tested with streams of air mixed with various VOCs including methanol, ethanol, and isopropanol at different flow rates. The collected data from the sensors were analyzed using PCA, LDA, and CNN methods for not only recognizing the signatures of different gases, but also differentiating between them and recognizing their ratio in a mixture. The results of the studies are promising for designing more effective hardware equipped with an ML modeling system to analyze the concentration of various gases and VOCs in a mixed situation.

Mapping neurons in the brain is important to understand the neuronal circuits involved in cognitive functions such as learning and memory formation. More importantly, understanding their dysfunction in neurological disorders and diseases could benefit patients that rely on better therapy interventions and techniques. To this aim, optogenetic tools, where light is used to control neuronal activity, and ultimately behavior, have revolutionized the field of neuroscience over the last 20 years. Current optogenetic approaches to investigate brain function involve the use of commercially available lasers and LEDs coupled to large implants, optical fibers or camera systems. Their use is usually associated with high cost, invasiveness and low spatial resolution. To address these limitations, organic electronic devices have been emerging as an alternative candidate for biocompatible, small-footprint, and high-resolution neural probes. In our own contribution to the field, we have demonstrated the successful detection of neuronal activity using organic photodetectors (OPDs) based on rubrene/C60, as well as direct optogenetic stimulation of neuronal activity using OLEDs based on Super Yellow. In this paper, we extend our previous work by demonstrating the stability and reliability of OPDs and OLEDs in optogenetics, and the effect of oxygen and encapsulation on the OPD/OLED performance. We also discuss the requirements for successful long-term neural recordings and determine the detection threshold for OPDs, (i.e. the required sensitivity to detect activity in a single neuron), as well as the minimum performance requirements in OLEDs to evoke neuronal activity.

Artificial photonic synapses, designed for emerging photo-interactive neuro-computing technologies, have been developed with area-density-tunable perovskite nano-cone arrays within a self-assembled block copolymer (BCP). These arrays, part of a field effect transistor with a floating gate of photoreceptive perovskite crystals, can trap and release electric charges, exhibiting functions like paired-pulse facilitation and long-term potentiation. Crafted using an off centered spin coating process, the perovskite floating gate emulates the human retina's position-dependent spatial distribution of cones. Arranged in 60 × 12 arrays, the synapse devices serve dual functions as receptors and synapses, demonstrating AI capabilities with pattern recognition accuracy up to 90%, as tested with the Modified National Institute of Standards and Technology handwritten digit pattern recognition test.

Despite the expected high demands in the agricultural industry, the application of health monitoring systems for plants is still at the research level. While imaging methods are often used for monitoring the health status of the shoot part of a plant, there are limited parameters that can be measured for assessing the health status of a plant root. Studies show that roots need oxygen for aerobic respiration. Higher dissolved oxygen near the root zone may result in a more massive root and a healthier plant. Conventional oxygen sensors are designed to measure the oxygen level in a gaseous environment. Due to their bulky structure, their application for monitoring oxygen in the soil is challenging. In this study, we have used A10 zinc-air batteries as oxygen sensors to monitor the oxygen level at the root zone of four garden plants: sweet pepper, basil, tomato, and cherry tomato. Using a microcontroller system, the electric current from the batteries was recorded as a signal related to the oxygen level. The measurements indicate a variation of ~1% in the oxygen level every 24 hours when the plants were exposed to a controlled light for 12 hours and kept in dark for 12 hours. The simplicity of the application of Zn-air batteries allows us to monitor the oxygen level at several locations around the root of a plant to study their breathing through their roots.

Photobiomodulation therapy (PBMT), including wound healing, is the treatment that promotes biochemical reactions on the site by irradiating light to the skin. The devices using point light sources, such as light-emitting diodes (LEDs) and lasers have been used for treatment so far, but they have various disadvantages such as low flexibility, relatively heavy, and uneven effects. Recently, OLED, a next-generation light source, has the inherent advantages of uniform irradiation, flexible shape, and low heat generation, which is ideal for wearable PBMT light sources. In this paper, a wearable device using red OLED was developed, and the OLED light source observed and confirmed wound healing and inflammatory response through animal experiments and cell proliferation experiments. Our findings suggest that the OLED based this technology, which has been applied in the display, combined with the field of skin therapy may promise advances in PBMT and other medical fields.

Organic photodetectors (OPDs) hold great promise for use in flexible electronics as they can be designed on substrates featuring various shapes and using cost-effective solution-processed methods. Organic conjugated materials offering two or more distinct optoelectronic functions are especially appealing here as they provide multifunctionality while also retaining the ease of fabrication and low-cost advantage. One such material is TPA-azaBODIPY-TPA that has been shown to feature ideal charge transfer properties and excitation energy levels. In our recent work, we demonstrated the versatile nature of this material acting as either a charge transport interlayer in perovskite solar cells, or as a light-absorbing layer in OPDs. TPA-azaBODIPY-TPA-based solar cellsshowed a 60 % increase in power conversion efficiency when compared to a control device using a conventional interlayer PEDOT:PSS. Having also demonstrated the successful utilization of TPA-azaBODIPY-TPA in OPDs manufactured on glass substrates, we further explore its applications in the design and fabrication of flexible OPDs for near-infrared sensing. Fabricated devices on flexible substrates show a near-infrared spectral responsivity of 49 mA W-1 at 730 nm, a high linear dynamic range of 110 dB and fast temporal responses below 100 μs. With robust thermal stability as well as excellent solubility and processability, TPA-azaBODIPY-TPA is found to be perfect candidate for the next-generation of smart optoelectronic flexible devices.

Nowadays the prevention of dementia is a challenge for humanity. There are some preventive intervention programs for dementia, which are mainly based in the modification of multicomponent lifestyles such as: physical and cognitive activity, weight control, metabolic-comorbidity control and social support. Recently, Mind and Movement Program to have Cognitive Health is a collaborative methodological proposal between the countries Mexico, Japan and Canada, which consists of three components: aerobic exercise; aerobic and cognitive exercises, as well as a motivation program. For performing aerobic and cognitive exercises, the monitoring of vital signs in real time is necessary through a statistical analysis of the data of each patient, in such a way that the doctor knows the state of health of the patient. As a consequence of the COVID-19 pandemic, the original program to acquire experimental data underwent modifications. Since the older adults were isolated, they were required to do their physical exercises at home, implementing a remote monitoring system based on a wearable smart band, which was properly developed to monitor the vital signs for each patient. Hence, a personalized quantification of the oxygen saturation and cardiac pressure based on light sensors and pressure sensors, respectively, was measured and monitored in real time. On the other hand, predefined programming based on Artificial intelligence, provides certain advantages for easy handling by the older adults. Currently, we are working along with a hospital, where doctors involved in the program are testing the prototype for the validation of the wearable smart bands.

Portable and wearable sensing devices are growing increasingly essential to people's lives as a result of the seriousness of air pollution and the rapid advancement of nanotechnology. The rGO/WO3/PVDF tertiary nanocomposite is employed as a monitoring device and boasts benefits like remarkable selectivity for ammonia hazardous gas, good responsiveness (Rg/Ra = 4.72, 50 ppm), and excellent linear sensitivity (10-500 ppm). Most crucially, the self-powered rGO/WO3/PVDF monitoring unit has a substantially quicker response/recovery time than the typical room-temperature semiconductor gas sensor. The viability of the tertiary nanocomposite for applications requiring self-powered ammonia gas sensing is demonstrated through a proof of concept demonstration.

high-sensitivity volatile organic gas sensor was fabricated with nano scale carbon black as the active material. Due to the polarity of gas molecules and the influence of surface energy, carbon black will produce different intermolecular distances after adsorbing different gases, resulted in different electron transfer ability. In addition, the conductivity of carbon black will also be changed in different oxidizing and reducing gases, coupled with the conductivity of gas molecules themselves, resulting in different electrical response of the sensor under various volatile organic gases with various concentrations.

Among different conducting polymers, PEDOT:PSS has been used for making organic electrochemical transistors (OECTs) due to the remarkable stability and the electrochemical properties of the polymer. With the fast-growing market for wearable electronics, the application of OECTs has been proposed for wearable sensors. However, the majority of OECTs have a planar design. Recently, we have demonstrated the feasibility of fabricating OECTs on sewing threads. This work has focused on studying the effect of thread materials on the performance of fiber-based OECTs made for wearable pH sensors. Such sensors can be used to collect metabolic information from the body of a patient by analyzing the pH of perspiration. The three most commercially common different kinds of threads were used to make OECTs with polyvinyl alcohol (PVA) gel as the electrolyte. Using 100% cotton, 25% cotton-75% polyester, and 32% cotton-68% polyester threads were used to fabricate and then characterize the transistor. Threads were coated with PEDOT:PSS polymer to use as a channel then use a Silver coated thread as a gate and a PVA gel electrolyte. Devices were tested by applying different voltages to the transistor terminals and monitoring the current through the PEDOT:PSS. The best signal was obtained from the device made on 25% cotton-75% polyester thread. The experimental results showed a promising approach that can lead to a good wearable pH sensor on human perspiration.

Antibiotic exposure can cause the development of antibiotic resistant bacteria and can induce allergic reactions in humans. A source of high antibiotic exposure is contaminated dairy milk. To prevent contaminated dairy milk, development of antibiotic biosensors for on-site detection is required. This is particularly important for dairy farmers as fines and suspension of license are consequences of shipping contaminated milk to processing plants, where antibiotic tests are currently performed. There are also environmental and economic consequences when whole dairy tanks are contaminated and go to waste. Our work addresses this problem by developing an antibiotic biosensor for farmers to test their milk on-site for ciprofloxacin prior to sending to processing plants. Ciprofloxacin is frequently used to treat common bacterial infections in cattle. Our work provides the following contributions. We introduce an antibiotic biosensor that integrates fluorescence spectroscopy, microfluidic processing, and lock-in amplification to improve the limit-of-detection of ciprofloxacin below the regulatory limit for milk. We also perform traditional fluorescence detection for comparison. Our antibiotic biosensor has a signal-flow starting with an ultraviolet light emitting diode for illumination of ciprofloxacin, and moving through a microfluidic platform, a photodiode for detection of the fluorescent wavelength, and a lock-in amplifier. Our antibiotic biosensor is well-suited for fast on-site analyses and is designed for ease-of-use. Overall, our work shows promise for the integration of real-time on-site antibiotic detection of antibiotics in dairy.