Jiang-Jing Wang

Fitting the resistance fluctuation data with a hidden Markov model helps uncover the complex free energy landscape and understand the glass relaxation dynamics of a phase-change material, GeTe. This is a preview of subscription content, access via your institution Access options Access Nature and 54 other Nature Portfolio journals Get Nature+, our best-value online-access subscription $32.99 / 30 days cancel any time Subscribe to this journal Receive 12 print issues and online access $259.00...

1 Introduction To deal with the drastically increased demands in data storage and processing, massive research efforts have been undertaken to develop non-volatile memory and neuromorphic computing technologies.[1-5] Phase-change materials (PCMs) are a leading material candidate for these applications.[3, 6-11] The basic principle is to exploit the large change in electrical and optical properties associated with the rapid and reversible phase transition between the amorphous and crystalline...

Abstract Spontaneous structural relaxation is intrinsic to glassy materials due to their metastable nature. For phase-change materials, the resultant temporal change in electrical resistance seriously hampers neuromorphic computing applications. Here we report an ab-initio-calculation-informed design of amorphous phase-change materials composed of robust ‘molecule-like’ motifs, depriving the amorphous alloy of critical structural ingredients responsible for relaxation and, hence, resistance drift.