When consumers buy a dairy or any temperature-sensitive product, little is known about its temperature history. One can only assume that the product has been maintained within its safe temperature range. The frequent cuts in electricity in Lebanon are affecting refrigeration and other aspects of the “cold” supply and distribution chains. If the cold chain is broken, bacteria will multiply easily and can spread rapidly and become infectious. Even before the recent severe crisis in the electricity shortage, the Laboratory of Food Safety and Microbiology at AUB, found 300 samples that were not fit for human consumption. There were another approximately 30 samples that were contaminated with harmful pathogens including Salmonella and Listeria when the cold chain was supposedly intact. Today's consumers live in a rapidly digital world that is seamlessly integrating into everyday life and expectations are evolving. In this project, we are proposing the development of a smart, cheap, and compact label capable of tracking both the exposure time and temperature changes during the transportation and the storage of dairy products. To track temperature changes of products throughout the distribution and storage chain, two main technologies exist: temperature data loggers and temperature-sensitive labels. The most advanced data logger is the TT Sensor Plus, a data recording device the size of a credit card. The price tag on this logger is around $15. While they provide high temporal resolutions, they are cumbersome and expensive to be used on individual food packages. As such, this technology is more suitable to track the temperature of food containers or large packages. Temperature-sensitive labels, on the other hand, are cheap, compact, and when exposed to the minimum temperature threshold, they change color. This leads, however, to many false readings since the response is not correlated with the duration of exposure and the maximum temperature. For example, a label with a trigger temperature of 20C, will still change color even if the product was exposed for only a few minutes which would not pose any risk. It is also not possible to know if the temperature exceeded the trigger temperature by only a few degrees or reached extremely high temperatures. As such, these labels were not widely adopted. Our technology combines the advantages of the two previous products: accurate tracking of temperature changes while being small and cheap. The smart temperature-memory material that we have developed can inform the consumer about the exact exposure time and the highest temperature to which the product was exposed. The operational scheme of the sensor will be similar in design to the commonly used “shock Label” but filled with the temperature-sensitive solution. The consumer, using an AI algorithm and a smartphone app, will be able to translate changes in the solution color to an accurate record of the temperature history of the dairy product. We believe this product will give our partners a competitive advantage by allowing their customers to test the safety of their products. Our laboratory has developed a new material with temperature memory properties by complexing phenylene-based conjugated polyelectrolytes (PPE-CO2) with polyvinylpyrrolidone (PVP), an amphiphilic macromolecule that destabilizes the conjugated polyelectrolytes 𝝅-𝝅 stacking. This makes it possible to shift between the less emissive aggregated state of the CPE (520 nm) and its more emissive single chains (450 nm) (Figure 1). We believe that as the solution temperature increases, the PPE-CO2 chains are destabilized, their emissions shifts to 450 nm and increase in intensity. Subsequently, the PVP polymer traps the polymer in this enhanced state leading to the observed temperature memory effect. Therefore, the solution intensity is dependent on the exposure time and the temperature. In this project, we aim to transform the fundamental scientific discovery in temperature memory from our laboratory into a product that can potentially save the lives of many consumers, especially in Lebanon where the electricity shortage poses a serious risk to dairy product safety. To achieve this objective, we will set three main goals: Goal 1: Tune and align the temperature memory with the needs of the dairy industry In collaboration with our partner, Dairy Khoury, we will develop a set of specific temperature conditions considered dangerous for different dairy products (raw milk, pasteurized milk, cheeses, yogurt, etc.). For example, raw milk will have a different triggering temperature profile than cheese which can tolerate higher temperatures for a longer exposure time. The polymer-based temperature memory material sensitivity is tunable by changing PVP molecular weights and its ratio to PPE-CO2. By the end of this objective, we will have a series of temperature memory materials tailored for specific products. Goal 2: Develop an app to extract the temperature record In this goal, we will explore two options for analyzing the images of the temperature-memory solution; The first one is a simple approach where we analyze the change in intensity and the shift in colors between the RGB channels.2 In the second one, we will use AI to analyze 100s of images imaged under different conditions to train the AI to recognize the temperature-memory pattern. A variety of models will be tested and the one with the highest accuracy and f1 score will be adopted. The AI component will be developed by Mr. Majd Al Kawaas, a computer science student, who has worked on many projects in AI at the AUB. By the end of this project, we will have the ability to precisely predict the history of temperature exposure of a specific sample. Goal 3: Build an optoelectronic prototype for a controlled in-store label reading The long-term objective of this project is for the consumer to be able to scan the label while holding the dairy product. However, we acknowledge the complexity of this task especially when it comes to the potential interference from ambient light in this proposed preliminary design. As such, we feel a more realistic objective within the grant time window is to develop a small optoelectronic device. The device will allow a homogenous excitation of the temperature-memory sample with a well-positioned LEDs excitation light. The user through the app will be able to scan the label and confirms that the product has been safely handled.