Park Tae Joon, Selcuk Kemal, Zhang Hai-Tian, Manna Sukriti, Batra Rohit, Wang Qi, Yu Haoming, Aadit Navid Anjum, Sankaranarayanan Subramanian K R S, Zhou Hua, Camsari Kerem Y, Ramanathan Shriram
School of Materials Engineering, Purdue University, West Lafayette, Indiana47907, United States.
Department of Electrical and Computer Engineering, University of California, Santa Barbara, Santa Barbara, California93106, United States.
Nano Lett. 2022 Nov 9;22(21):8654-8661. doi: 10.1021/acs.nanolett.2c03223. Epub 2022 Oct 31.
Probabilistic computing has emerged as a viable approach to solve hard optimization problems. Devices with inherent stochasticity can greatly simplify their implementation in electronic hardware. Here, we demonstrate intrinsic stochastic resistance switching controlled via electric fields in perovskite nickelates doped with hydrogen. The ability of hydrogen ions to reside in various metastable configurations in the lattice leads to a distribution of transport gaps. With experimentally characterized p-bits, a shared-synapse p-bit architecture demonstrates highly parallelized and energy-efficient solutions to optimization problems such as integer factorization and Boolean satisfiability. The results introduce perovskite nickelates as scalable potential candidates for probabilistic computing and showcase the potential of light-element dopants in next-generation correlated semiconductors.
概率计算已成为解决硬优化问题的一种可行方法。具有固有随机性的器件可以极大地简化其在电子硬件中的实现。在此，我们展示了在掺杂氢的钙钛矿镍酸盐中通过电场控制的本征随机电阻开关。氢离子在晶格中驻留在各种亚稳态构型的能力导致了传输间隙的分布。利用实验表征的p比特，一种共享突触p比特架构展示了针对诸如整数分解和布尔可满足性等优化问题的高度并行化且节能的解决方案。这些结果将钙钛矿镍酸盐引入为概率计算的可扩展潜在候选材料，并展示了轻元素掺杂剂在下一代相关半导体中的潜力。
