Channel-Boosted Electrochemical RAM With a-IGZO TFT for Highly Accurate and Energy-Efficient Neural Network Computation

We present a channel-boosted electrochemical random-access memory (CB-ECRAM), composed of an amorphous indium-gallium–zinc oxide thin-film transistor (a-IGZO TFT) and an electrochemical random-access memory (ECRAM) connected in series, which demonstrates significantly enhanced performance. With an eightfold increase in programming characteristics and a 483-fold improvement in update energy efficiency compared to standard ECRAM, the CB-ECRAM effectively reduces noise in vector-matrix multiplication (VMM) and achieves exceptional half-bias (HB) selectivity in the vector-vector outer product (VVOP) for neural network computation. Moreover, training simulations on the Modified National Institute of Standards and Technology (MNIST) dataset indicated a test accuracy of 97.39%, which is comparable to the floating-point (FP) baseline.