Search Results - physical+science

 This invention demonstrates the synthesis of cyclic allyl sulfide small molecule that incorporates into acrylates and styrenic polymer and fosters robust reprocess-ability through radically initiated scission and extension. 

Neuromorphic computing, systems designed to mimic the biological nervous system, require far less power than current computer processors. The increased efficiency makes feasible artificial intelligence applications for smaller, hand-held devices (e.g. smartphones, tablets).  To this end, UMass inventors have designed hardware components that mimic neuronal synapses (Figure A). Specifically, diffusive Ag-in-oxide memristors show a temporal response during and after stimulation similar to that of a biological synapse. The novel diffusive memristor and its synapse-like dynamics enable a direct emulation of both short- and long-term plasticity of biological synapses and represent a major advancement in a hardware implementation for neuromorphic computing.

This invention provides a novel method for the formation of graphene films, high-quality graphene films made thereby, and applications thereof.

As industry 4.0 pushes the limits of micro and nano-scale technologies, semiconductor, GPU, and robotics manufacturers are searching for ways to optimize their production lines while still maintaining the highest level of quality. Visual inspection of these advanced micro and nano-scale technologies requires remarkably high levels of precision and control. The piezoelectric actuators used for metrology are currently burdened by non-linearities that require slow and expensive internal closed-loop controllers to deliver sufficient precision to the imaging system. A UMass Amherst research team has developed a new control method that reduces the cost and complexity of high-precision imaging systems while still delivering rapid acquisition of clear and crisp images. The new method integrates the focus measurement and the troublesome non-linear effects in a single learning-based model. The method involves evaluating the focus from a short sequence of images in a deep learning-based control model to determine the optimal position for the lens. The technology leverages Long Short-Term Memory (LSTM) because of its superior ability to draw inferences from learned time sequence data. This novel method also utilizes an optimized backpropagation algorithm for efficiency, as well as a unique S-curve control input profile to minimize motor and image jerks. This method supports both rapid and stable dynamic lens transitions for a wide variety of imaging applications. Compared with the leading autofocus technologies, this method demonstrates significant advantages regarding autofocus time.  

This invention provides a nature-inspired, multilayer photothermal textile and personal heated wearables, such as clothing, comprising such textile for highly efficient thermoregulation and personal thermal management.

This invention provides a nature-inspired, multilayer photothermal textile and personal heated wearables, such as clothing, comprising such textile for highly efficient thermoregulation and personal thermal management.

This invention provides polymer-coated supercapacitors for energy storage applications.

This invention provides novel, deoxybenzoin-based anti-flammable polymers and cured epoxy resins for a variety of end-use applications.

This invention provides novel ammonium and sulfonium sulfonate zwitterions and polymers derived therefrom for a variety of end-use applications.