Cognizant Fiber-Reinforced Polymer Composites Incorporating Seamlessly Integrated Sensing and Computing Circuitry

Structural fiber-reinforced polymer (FRP) composite materials consisting of a polymer matrix reinforced with layers of high-strength fibers are used in numerous applications, including but not limited to spacecraft, vehicles, buildings, and bridges. Researchers in the past few decades have suggested the necessary integration of sensors (e.g., fiber optic sensors) in polymer composites to enable health monitoring of composites' performance over their service lives. This work introduces an innovative cognizant composite that can self-sense, compute, and implement decisions based on sensed values. It is a critical step towards smart, resilient infrastructure. We describe a method to fabricate textile sensors with flexible circuitry and a microcontroller within the polymer composite, enabling computational operations to take place in the composite without impacting its integrity. A microstructural investigation of the sensors showed that the amount of oxidative agent and soaking time of the fabric play a major role in the adsorption of polypyrrole (PPy) on fiberglass (FG). XPS results showed that the 10 g ferric chloride solution with 6 h of soaking time had the highest degree of protonation (28%) and, therefore, higher adsorption of PPy on FG. A strain range of 30% was achieved by examining different circuitry and sensor designs for their resistance and strain resolution under mechanical loading. A microcontroller was added to the circuit and then embedded within a composite material. This composite system was tested under flexural loading to demonstrate its self-sensing, computing, and actuation capabilities. The resulting cognizant composite demonstrated the ability to read resistance values and measure strain using the embedded microcontroller and autonomously actuate an LED light when the strain exceeds a predefined limit of 2000 µε. The application of the proposed FRP system would provide in situ monitoring of structural composite components with autonomous response capabilities, as well as reduce manufacturing, production, and maintenance costs.

Estimating the contributions of mobile sources of PAH to urban air using real-time PAH monitoring

Motor vehicles are a significant source of airborne polycyclic aromatic hydrocarbons (PAH) in many urban areas. Traditional approaches used in determining the relative contributions of individual vehicle types to the total amount of PAH in air have been based on the analysis of integrated samples of airborne particles and gases for the presence of chemical tracers indicative of the vehicles from which the chemicals derived. As an alternative, we have used a photoelectric aerosol sensor (PAS) capable of measuring PAH levels in real-time in the emissions plumes from motor vehicles. We placed the PAS near a traffic-light in Kenmore Square, a busy crossroads in downtown Boston (MA, USA). A video camera co-located at the site recorded the vehicles passing the sensor, and this record was correlated with the PAS data. During a 5-day monitoring period (approximately 59 h) in the summer of 1998, over 34,000 motor vehicles were counted and classified and over 24,000 PAS readings were recorded (frequency = 1/8.6 s). The composition of the vehicle population was 94% passenger vehicles, 1.4% buses, 2.6% small trucks, 1.3% medium trucks, 0.35% large trucks, and 0.45% garbage and construction trucks. In analyzing the PAS data, it was assumed that the highest PAS measurements--those that exceeded the 95% critical level of the 5-min moving average of all the PAS measurements--were indicative of primary vehicular emissions. We found that approximately 46% of the mass of particle-bound PAH (i.e. approximately 46% of the integrated area under the PAS signal vs. time plots) was attributable to primary emissions from motor vehicles passing the sensor. Of this, 35-61% was attributable to passenger vehicles (cars, pickup trucks, and sports utility vehicles) and 39-65% was attributable to non-passenger vehicles [buses (14-23%), small trucks (12-20%), medium trucks (8.4-14%), large trucks (2.9-4.8%) and garbage and construction trucks (1.9-3.2%)]. Our results suggest that on a per vehicle basis, buses and trucks--the majority of which run on diesel fuel--emitted greater amounts of particle-bound PAH than passenger vehicles. Overall, we found that real-time photoelectric aerosol sensing (in combination with video photography) is useful for estimating the contributions of airborne PAB from different vehicle types. Due to the physical constraints of our monitoring site and the high volumes of traffic, however, it was not possible to uniquely attribute PAS signals to individual vehicles.

Cocaine-induced cardiovascular dysfunction: a case study

This article focuses on the authors' experience with a 25-year-old female patient exhibiting cocaine-induced cardiovascular dysfunction. A care plan is provided that emphasizes the patient's need for assistance with individual coping.