This work claims that VO 2 , of interest currently for its metal-insulator phase transition properties, is also a ferroelectric material. Using a VO 2 film sandwiched between two silicon dioxide layers, memory transistor structures with substantial and useful properties have been fabricated. Threshold voltage shifts are opposite of charge trapping phenomena and consistent with ferroelectric polarization switching phenomena. Hysteresis memory window of ~1 V is obtained in-4 to 4 V gate voltage cycling. We argue that the effects observed are due to the ferroelectricity of VO 2. Its remnant polarization of ~0.53 μC/cm 2 and coercive field of ~450 kV/cm are extracted from the saturation behavior of threshold voltage shift. Similar to other ferroelectric memory structures, depolarization effects are observed. The state of memory devices decays gradually and retention times of approximately 15 minutes are obtained at room temperature. These ferroelectric properties do not vanish above metal-insulator phase transition temperature.

A mathematical model for a spatially distributed mechanical property such as Young's modulus and texture inside solid food during the cooking process was developed by combining a numerical conduction heat transfer model with the kinetics of property changes. Using the distributed mechanical property obtained from the thermokinetic model, linear elastic stress analysis was performed to determine the effective material property and how it changes during cooking. Spatial variation in the mechanical property is found to be significant for commonly used food sizes in potato. When property varies spatially, volume average property, which is easier to compute than an effective property obtained from mechanical stress analysis, can be a substitute for the effective property. Cooking time based on volume average Young's modulus varies less strongly with size than how temperature varies with size. When activation energy for the property change kinetics is lower, cooking time varies less with size. The scaling of cooking time with size and kinetics and the extent of property variation in a sample during cooking should provide useful guidelines in automating cooking processes.