Probabilistic computing is an emerging computational paradigm that uses probabilistic circuits to efficiently solve optimization problems such as invertible logic, where traditional digital computations are difficult to solve. This paper proposes a true random number generator (TRNG) based on resistive random-access memory (RRAM), which is combined with an activation function implemented by a piecewise linear function to form a standard p-bit cell, one of the most important parts of a p-circuit. A p-bit multiplexing strategy is also applied to reduce the number of p-bits and improve resource utilization. To verify the superiority of the proposed probabilistic circuit, we implement the invertible p-circuit on a field-programmable gate array (FPGA), including AND gates, full adders, multi-bit adders, and multipliers. The results of the FPGA implementation show that our approach can significantly save the consumption of hardware resources.

Resistive random access memory (RRAM) is one of the most promising new nonvolatile memories because of its excellent properties. Moreover, due to fast read speed and low work voltage, it is suitable for seldom-write frequent-read applications. However, as technology nodes shrink, RRAM faces many issues, which can significantly degrade RRAM performance. Therefore, it is necessary to optimize the sensing schemes to improve the application range of RRAM. In this paper, the issues faced by RRAM in advanced technology nodes are summarized. Then, the advantages and weaknesses in the novel design and optimization methodologies of sensing schemes are introduced in detail from three aspects, the reference schemes, sensing amplifier schemes, and bit line (BL)-enhancing schemes, according to the development of technology in especially recent years, which can be the reference for designing the sensing schemes. Moreover, the waveforms and results of each method are illustrated to make the design easy to understand. With the development of technology, the sensing schemes of RRAM become higher speed and resolution, low power consumption, and are applied at advanced technology nodes and low working voltage. Now, the most advanced nodes the RRAM applied is 14 nm node, the lowest working voltage can reach 0.32 V, and the shortest access time can be only a few nanoseconds.

Ferroelectric capacitors (FeCAPs) with high process compatibility, high reliability, ultra-low programming current and fast operation speed are promising candidates to traditional volatile and nonvolatile memory. In addition, they have great potential in the fields of storage, computing, and memory logic. Nevertheless, effective methods to realize logic and memory in FeCAP devices are still lacking. This study proposes a 1T2C FeCAP-based in situ bitwise X(N)OR logic based on a charge-sharing function. First, using the 1T2C structure and a two-step write-back circuit, the nondestructive reading is realized with less complexity than the previous work. Second, a method of two-line activation is used during the operation of X(N)OR. The verification results show that the speed, area and power consumption of the proposed 1T2C FeCAP-based bitwise logic operations are significantly improved.

Hf_0.5Zr_0.5O₂-based multi-level cell (MLC) ferroelectric random-access memory (FeRAM) has great potential for high-density storage applications. However, it is usually limited by the issues of a small operation margin and a large input offset. The study of circuit design and optimization for MLC FeRAM is necessary to solve these problems. In this work, we propose and simulate a configuration for a Hf_0.5Zr_0.5O₂-based 3TnC MLC FeRAM macro circuit, which also presents a high area efficiency of 12F² for each bit. Eight polarization states can be distinguished in a single fabricated Hf_0.5Zr_0.5O₂-based memory device for potential MLC application, which is also simulated by a SPICE model for the subsequent circuit design. Therein, a nondestructive readout approach is adopted to expand the reading margin to 450 mV between adjacent storage levels, while a capacitorless offset-canceled sense amplifier (SA) is designed to reduce the offset voltage to 20 mV, which improves the readout reliability of multi-level states. Finally, a 4 Mb MLC FeRAM macro is simulated and verified using a GSMC 130 nm CMOS process. This study provides the foundation of circuit design for the practical fabrication of a Hf_0.5Zr_0.5O₂-based MLC FeRAM chip in the future, which also suggests its potential for high-density storage applications.

Hafnium-based ferroelectric memories are a promising approach to enhancing integrated circuit performance, offering advantages such as miniaturization, compatibility with CMOS technology, fast read and write speeds, non-volatility, and low power consumption. However, FeRAM (Ferroelectric Random Access Memory) still faces challenges related to endurance and retention susceptibility to process variations. Hence, testing and obtaining the core parameters of ferroelectric capacitors continuously is essential to investigate these phenomena and explore the potential solution. The traditional method for measuring ferroelectric capacitors has limitations in timing generation capability, introduces parasitic capacitance, and lacks accuracy for small-area capacitors. In this study, we analyzed the working principle of ferroelectric capacitors and designed a method to detect the remnant polarization, saturation polarization, and imprint offset of ferroelectric capacitors. Further, we further proposed a circuit implementation method. The proposed test circuit conquers these limitations and enables high-precision testing of ferroelectric capacitors, contributing to developing hafnium-based ferroelectric memories. The circuit includes a flip-readout circuit, a capacitance calibration circuit, and a voltage-to-time converter and time-to-digital converter (VTC&TDC) readout circuit. According to simulation results, the capacitance calibration circuit reduces the deviation of the capacitance by 84%, and the accuracy of the readout circuit is 5.91 bits, with a readout time of 150 ns and a power consumption of 1 mW. This circuit enables low-cost acquisition of array-level small-area ferroelectric capacitance data, which can guide subsequent device optimization and circuit design.