Ferroelectric FET-based context-switching FPGA enabling dynamic reconfiguration for adaptive deep learning machines.

Field programmable gate array (FPGA) is widely used in the acceleration of deep learning applications because of its reconfigurability, flexibility, and fast time-to-market. However, conventional FPGA suffers from the trade-off between chip area and reconfiguration latency, making efficient FPGA accelerations that require switching between multiple configurations still elusive. Here, we propose a ferroelectric field-effect transistor (FeFET)-based context-switching FPGA supporting dynamic reconfiguration to break this trade-off, enabling loading of arbitrary configuration without interrupting the active configuration execution. Leveraging the intrinsic structure and nonvolatility of FeFETs, compact FPGA primitives are proposed and experimentally verified. The evaluation results show our design shows a 63.0%/74.7% reduction in a look-up table (LUT)/connection block (CB) area and 82.7%/53.6% reduction in CB/switch box power consumption with a minimal penalty in the critical path delay (9.6%). Besides, our design yields significant time savings by 78.7 and 20.3% on average for context-switching and dynamic reconfiguration applications, respectively.

Powering Disturb-Free Reconfigurable Computing and Tunable Analog Electronics with Dual-Port Ferroelectric FET.

Single-port ferroelectric FET (FeFET) that performs write and read operations on the same electrical gate prevents its wide application in tunable analog electronics and suffers from read disturb, especially in the high-threshold voltage (VTH) state as the retention energy barrier is reduced by the applied read bias. To address both issues, we propose to adopt a read disturb-free dual-port FeFET where the write is performed on the gate featuring a ferroelectric layer and the read is done on a separate gate featuring a nonferroelectric dielectric. Combining the unique structure and the separate read gate, read disturb is eliminated as the applied field is aligned with polarization in the high-VTH state, thus improving its stability, while it is screened by the channel inversion charge and exerts no negative impact on the low-VTH state stability. Comprehensive theoretical and experimental validation has been performed on fully depleted silicon-on-insulator (FDSOI) FeFETs integrated on a 22 nm platform, which intrinsically has dual ports with its buried oxide layer acting as the nonferroelectric dielectric. Novel applications that can exploit the proposed dual-port FeFET are proposed and experimentally demonstrated for the first time, including FPGA that harnesses its read disturb-free feature and tunable analog electronics (e.g., frequency tunable ring oscillator in this work) leveraging the separated write and read paths.

Sub-Nanosecond Switching of Si:HfO2 Ferroelectric Field-Effect Transistor.

The discovery of ferroelectric doped HfO2 enabled the emergence of scalable and CMOS-compatible ferroelectric field-effect transistor (FeFET) technology which has the potential to meet the growing need for fast, low-power, low-cost, and high-density nonvolatile memory, and neuromorphic devices. Although HfO2 FeFETs have been widely studied in the past few years, their fundamental switching speed is yet to be explored. Importantly, the shortest polarization time demonstrated to date in HfO2-based FeFET was ∼10 ns. Here, we report that a single subnanosecond pulse can fully switch HfO2-based FeFET. We also study the polarization switching kinetics across 11 orders of magnitude in time (300 ps to 8 s) and find a remarkably steep time-voltage relation, which is captured by the classical nucleation theory across this wide range of pulse widths. These results demonstrate the high-speed capabilities of FeFETs and help better understand their fundamental polarization switching speed limits and switching kinetics.

Three-to-one analog signal modulation with a single back-bias-controlled reconfigurable transistor.

Reconfigurable field effect transistors are an emerging class of electronic devices, which exploit a structure with multiple independent gates to selectively adjust the charge carrier transport. Here, we propose a new device variant, where not only p-type and n-type operation modes, but also an ambipolar mode can be selected solely by adjusting a single program voltage. It is demonstrated how the unique device reconfigurability of the new variant can be exploited for analog circuit design. The non-linearity of the ambipolar mode can be used for frequency doubling without the generation of additional harmonics. Further, phase shifter and follower circuits are enabled by the n- and p-type modes, respectively. All three functions can be combined to create a 3-to-1 reconfigurable analog signal modulation circuit on a single device enabling wireless communication schemes. Both, the concept as well as the application have been experimentally demonstrated on industrial-scale fully-depleted SOI platform. The special transport physics in those structures has been analyzed by TCAD simulations as well as temperature dependent measurements.

Ferroelectric transistors with asymmetric double gate for memory window exceeding 12 V and disturb-free read.

Ferroelectric field-effect transistors (FeFETs) with a single gate structure and using the newly discovered ferroelectric hafnium oxide as an active material are attracting considerable interest for nonvolatile memory devices. However, such FeFETs struggle to achieve a large separation between the two logic states (memory window, MW) because of the thickness limitations of the ferroelectric film. Moreover, they are affected by detrimental disturbs coming from the read operation because of the shared write and read paths. Therefore, significant performance improvements are needed for the device to compete with established memory technologies like flash. Here, we present an asymmetric double-gate FeFET structure, where only one gate stack comprises the ferroelectric layer. We propose a novel read operation at the non-ferroelectric gate and demonstrate an amplified MW exceeding 12 V thanks to the enhanced body effect factor and the increased sensitivity of the transfer characteristics to the ferroelectric polarization. As a result, the above physical limitation is circumvented, thus by far outperforming the MW values reported in the literature. Based on this, we implement the multi-level cell storage featuring 4 bits per cell and stable data retention. Finally, an essential benefit originating from the separated write and read paths in our structure is exploited to demonstrate the fully disturb-free read operation. Besides memory, this could be particularly favorable for those neuromorphic and in-memory computing concepts with an occasional update of the stored variable but a very frequent read.

Ferroelectric field-effect transistors based on HfO2: a review.

In this article, we review the recent progress of ferroelectric field-effect transistors (FeFETs) based on ferroelectric hafnium oxide (HfO2), ten years after the first report on such a device. With a focus on the use of FeFET for nonvolatile memory application, we discuss its basic operation principles, switching mechanisms, device types, material properties and array structures. Key device performance metrics such as cycling endurance, retention, memory window, multi-level operation and scaling capability are analyzed. We also briefly survey recent developments in alternative applications for FeFETs including neuromorphic and in-memory computing as well as radiofrequency devices.

Frequency Mixing with HfO2-Based Ferroelectric Transistors.

Second harmonic generation (SHG) and frequency mixing of electrical signals are fundamental for a wide range of radiofrequency applications. Recently, ferroelectric field-effect transistors (FeFETs), made from ferroelectric hafnium oxide (HfO2), have demonstrated promising SHG capabilities because of their unique symmetric transfer curves. In this paper, we illustrate how this symmetry is highly sensitive to material properties by varying the thickness of the ferroelectric layer and the doping of the silicon substrate. We show that the SHG conversion gain and the spectral purity are greatly increased (up to 96%) by precisely tuning the ferroelectric polarization reversal and the quantum tunneling currents. Based on this, we propose and experimentally demonstrate the generation of the difference and of the sum of two input frequencies (frequency mixing) with a single FeFET, which we attribute to the inherently strong quadratic component of the symmetric transfer characteristics. Because of the reversible and continuous ferroelectric switching in HfO2, our approach allows for an electrical control of the energy distribution of spectral components, thus opening up new and very promising paths for frequency manipulations with simple ferroelectric devices.

Mimicking biological neurons with a nanoscale ferroelectric transistor.

Neuron is the basic computing unit in brain-inspired neural networks. Although a multitude of excellent artificial neurons realized with conventional transistors have been proposed, they might not be energy and area efficient in large-scale networks. The recent discovery of ferroelectricity in hafnium oxide (HfO2) and the related switching phenomena at the nanoscale might provide a solution. This study employs the newly reported accumulative polarization reversal in nanoscale HfO2-based ferroelectric field-effect transistors (FeFETs) to implement two key neuronal dynamics: the integration of action potentials and the subsequent firing according to the biologically plausible all-or-nothing law. We show that by carefully shaping electrical excitations based on the particular nucleation-limited switching kinetics of the ferroelectric layer further neuronal behaviors can be emulated, such as firing activity tuning, arbitrary refractory period and the leaky effect. Finally, we discuss the advantages of an FeFET-based neuron, highlighting its transferability to advanced scaling technologies and the beneficial impact it may have in reducing the complexity of neuromorphic circuits.

Accumulative Polarization Reversal in Nanoscale Ferroelectric Transistors.

The electric-field-driven and reversible polarization switching in ferroelectric materials provides a promising approach for nonvolatile information storage. With the advent of ferroelectricity in hafnium oxide, it has become possible to fabricate ultrathin ferroelectric films suitable for nanoscale electronic devices. Among them, ferroelectric field-effect transistors (FeFETs) emerge as attractive memory elements. While the binary switching between the two logic states, accomplished through a single voltage pulse, is mainly being investigated in FeFETs, additional and unusual switching mechanisms remain largely unexplored. In this work, we report the natural property of ferroelectric hafnium oxide, embedded within a nanoscale FeFET, to accumulate electrical excitation, followed by a sudden and complete switching. The accumulation is attributed to the progressive polarization reversal through localized ferroelectric nucleation. The electrical experiments reveal a strong field and time dependence of the phenomenon. These results not only offer novel insights that could prove critical for memory applications but also might inspire to exploit FeFETs for unconventional computing.

Switching Kinetics in Nanoscale Hafnium Oxide Based Ferroelectric Field-Effect Transistors.

The recent discovery of ferroelectricity in thin hafnium oxide films has led to a resurgence of interest in ferroelectric memory devices. Although both experimental and theoretical studies on this new ferroelectric system have been undertaken, much remains to be unveiled regarding its domain landscape and switching kinetics. Here we demonstrate that the switching of single domains can be directly observed in ultrascaled ferroelectric field effect transistors. Using models of ferroelectric domain nucleation we explain the time, field and temperature dependence of polarization reversal. A simple stochastic model is proposed as well, relating nucleation processes to the observed statistical switching behavior. Our results suggest novel opportunities for hafnium oxide based ferroelectrics in nonvolatile memory devices.