Deep random forest with ferroelectric analog content addressable memory.

Deep random forest (DRF), which combines deep learning and random forest, exhibits comparable accuracy, interpretability, low memory and computational overhead to deep neural networks (DNNs) in edge intelligence tasks. However, efficient DRF accelerator is lagging behind its DNN counterparts. The key to DRF acceleration lies in realizing the branch-split operation at decision nodes. In this work, we propose implementing DRF through associative searches realized with ferroelectric analog content addressable memory (ACAM). Utilizing only two ferroelectric field effect transistors (FeFETs), the ultra-compact ACAM cell performs energy-efficient branch-split operations by storing decision boundaries as analog polarization states in FeFETs. The DRF accelerator architecture and its model mapping to ACAM arrays are presented. The functionality, characteristics, and scalability of the FeFET ACAM DRF and its robustness against FeFET device non-idealities are validated in experiments and simulations. Evaluations show that the FeFET ACAM DRF accelerator achieves ∼106×/10× and ∼106×/2.5× improvements in energy and latency, respectively, compared to other DRF hardware implementations on state-of-the-art CPU/ReRAM.

Ferroelectric compute-in-memory annealer for combinatorial optimization problems.

Computationally hard combinatorial optimization problems (COPs) are ubiquitous in many applications. Various digital annealers, dynamical Ising machines, and quantum/photonic systems have been developed for solving COPs, but they still suffer from the memory access issue, scalability, restricted applicability to certain types of COPs, and VLSI-incompatibility, respectively. Here we report a ferroelectric field effect transistor (FeFET) based compute-in-memory (CiM) annealer for solving larger-scale COPs efficiently. Our CiM annealer converts COPs into quadratic unconstrained binary optimization (QUBO) formulations, and uniquely accelerates in-situ the core vector-matrix-vector (VMV) multiplication operations of QUBO formulations in a single step. Specifically, the three-terminal FeFET structure allows for lossless compression of the stored QUBO matrix, achieving a remarkably 75% chip size saving when solving Max-Cut problems. A multi-epoch simulated annealing (MESA) algorithm is proposed for efficient annealing, achieving up to 27% better solution and ~ 2X speedup than conventional simulated annealing. Experimental validation is performed using the first integrated FeFET chip on 28nm HKMG CMOS technology, indicating great promise of FeFET CiM array in solving general COPs.

Embedding security into ferroelectric FET array via in situ memory operation.

Non-volatile memories (NVMs) have the potential to reshape next-generation memory systems because of their promising properties of near-zero leakage power consumption, high density and non-volatility. However, NVMs also face critical security threats that exploit the non-volatile property. Compared to volatile memory, the capability of retaining data even after power down makes NVM more vulnerable. Existing solutions to address the security issues of NVMs are mainly based on Advanced Encryption Standard (AES), which incurs significant performance and power overhead. In this paper, we propose a lightweight memory encryption/decryption scheme by exploiting in-situ memory operations with negligible overhead. To validate the feasibility of the encryption/decryption scheme, device-level and array-level experiments are performed using ferroelectric field effect transistor (FeFET) as an example NVM without loss of generality. Besides, a comprehensive evaluation is performed on a 128 × 128 FeFET AND-type memory array in terms of area, latency, power and throughput. Compared with the AES-based scheme, our scheme shows ~22.6×/~14.1× increase in encryption/decryption throughput with negligible power penalty. Furthermore, we evaluate the performance of our scheme over the AES-based scheme when deploying different neural network workloads. Our scheme yields significant latency reduction by 90% on average for encryption and decryption processes.

First demonstration of in-memory computing crossbar using multi-level Cell FeFET.

Advancements in AI led to the emergence of in-memory-computing architectures as a promising solution for the associated computing and memory challenges. This study introduces a novel in-memory-computing (IMC) crossbar macro utilizing a multi-level ferroelectric field-effect transistor (FeFET) cell for multi-bit multiply and accumulate (MAC) operations. The proposed 1FeFET-1R cell design stores multi-bit information while minimizing device variability effects on accuracy. Experimental validation was performed using 28 nm HKMG technology-based FeFET devices. Unlike traditional resistive memory-based analog computing, our approach leverages the electrical characteristics of stored data within the memory cell to derive MAC operation results encoded in activation time and accumulated current. Remarkably, our design achieves 96.6% accuracy for handwriting recognition and 91.5% accuracy for image classification without extra training. Furthermore, it demonstrates exceptional performance, achieving 885.4 TOPS/W-nearly double that of existing designs. This study represents the first successful implementation of an in-memory macro using a multi-state FeFET cell for complete MAC operations, preserving crossbar density without additional structural overhead.

Ferroelectric Content-Addressable Memory Cells with IGZO Channel: Impact of Retention Degradation on the Multibit Operation.

Indium gallium zinc oxide (IGZO)-based ferroelectric thin-film transistors (FeTFTs) are being vigorously investigated for being deployed in computing-in-memory (CIM) applications. Content-addressable memories (CAMs) are the quintessential example of CIM, which conduct a parallel search over a queue or stack to obtain the matched entries for a given input data. CAM cells offer the ability for massively parallel searches in a single clock cycle throughout an entire CAM array for the input query, thereby enabling pattern matching and searching functionality. Therefore, CAM cells are used extensively for pattern matching or search operations in data-centric computing. This paper investigates the impact of retention degradation on IGZO-based FeTFT on the multibit operation in content CAM cell applications. We propose a scalable multibit 1FeTFT-1T-based CAM cell composed of only one FeTFT and one transistor, thus significantly improving the density and energy efficiency compared with conventional complementary metal-oxide-semiconductor (CMOS)-based CAM. We successfully demonstrate the operations of our proposed CAM with storage and search by exploiting the multilevel states of the experimentally calibrated IGZO-based FeTFT devices. We also investigate the impact of retention degradation on the search operation. Our proposed IGZO-based 3-bit and 2-bit CAM cell shows 104 s and 106 s retention, respectively. The single-bit CAM cell shows lifelong (10 years) retention.

THz Thin Film Varactor Based on Integrated Ferroelectric HfZrO2.

In this paper, we present a broadband microwave characterization of ferroelectric hafnium zirconium oxide (Hf0.5Zr0.5O2) metal-ferroelectric-metal (MFM) thin film varactor from 1 kHz up to 0.11 THz. The varactor is integrated into the back-end-of-line (BEoL) of 180 nm CMOS technology as a shunting capacitor for the coplanar waveguide (CPW) transmission line. At low frequencies, the varactor shows a slight imprint behavior, with a maximum tunability of 15% after the wake-up. In the radio- and mmWave frequency range, the varactor's maximum tunability decreases slightly from 13% at 30 MHz to 10% at 110 GHz. Ferroelectric varactors were known for their frequency-independent, linear tunability as well as low loss. However, this potential was never fully realized due to limitations in integration. Here, we show that ferroelectric HfO2 thin films with good back-end-of-line compatibility support very large scale integration. This opens up a broad range of possible applications in the mmWave and THz frequency range such as 6G communications, imaging radar, or THz imaging.

Synergistic Approach of Interfacial Layer Engineering and READ-Voltage Optimization in HfO2-Based FeFETs for In-Memory-Computing Applications.

This article reports an improvement in the performance of the hafnium oxide-based (HfO2) ferroelectric field-effect transistors (FeFET) achieved by a synergistic approach of interfacial layer (IL) engineering and READ-voltage optimization. FeFET devices with silicon dioxide (SiO2) and silicon oxynitride (SiON) as IL were fabricated and characterized. Although the FeFETs with SiO2 interfaces demonstrated better low-frequency characteristics compared to the FeFETs with SiON interfaces, the latter demonstrated better WRITE endurance and retention. Finally, the neuromorphic simulation was conducted to evaluate the performance of FeFETs with SiO2 and SiON IL as synaptic devices. We observed that the WRITE endurance in both types of FeFETs was insufficient to carry out online neural network training. Therefore, we consider an inference-only operation with offline neural network training. The system-level simulation reveals that the impact of systematic degradation via retention degradation is much more significant for inference-only operation than low-frequency noise. The neural network with FeFETs based on SiON IL in the synaptic core shows 96% accuracy for the inference operation on the handwritten digit from the Modified National Institute of Standards and Technology (MNIST) data set in the presence of flicker noise and retention degradation, which is only a 2.5% deviation from the software baseline.

Achieving software-equivalent accuracy for hyperdimensional computing with ferroelectric-based in-memory computing.

Hyperdimensional computing (HDC) is a brain-inspired computational framework that relies on long hypervectors (HVs) for learning. In HDC, computational operations consist of simple manipulations of hypervectors and can be incredibly memory-intensive. In-memory computing (IMC) can greatly improve the efficiency of HDC by reducing data movement in the system. Most existing IMC implementations of HDC are limited to binary precision which inhibits the ability to match software-equivalent accuracies. Moreover, memory arrays used in IMC are restricted in size and cannot immediately support the direct associative search of large binary HVs (a ubiquitous operation, often over 10,000+ dimensions) required to achieve acceptable accuracies. We present a multi-bit IMC system for HDC using ferroelectric field-effect transistors (FeFETs) that simultaneously achieves software-equivalent-accuracies, reduces the dimensionality of the HDC system, and improves energy consumption by 826x and latency by 30x when compared to a GPU baseline. Furthermore, for the first time, we experimentally demonstrate multi-bit, array-level content-addressable memory (CAM) operations with FeFETs. We also present a scalable and efficient architecture based on CAMs which supports the associative search of large HVs. Furthermore, we study the effects of device, circuit, and architectural-level non-idealities on application-level accuracy with HDC.

Structural and Electrical Response of Emerging Memories Exposed to Heavy Ion Radiation.

Hafnium oxide- and GeSbTe-based functional layers are promising candidates in material systems for emerging memory technologies. They are also discussed as contenders for radiation-harsh environment applications. Testing the resilience against ion radiation is of high importance to identify materials that are feasible for future applications of emerging memory technologies like oxide-based, ferroelectric, and phase-change random-access memory. Induced changes of the crystalline and microscopic structure have to be considered as they are directly related to the memory states and failure mechanisms of the emerging memory technologies. Therefore, we present heavy ion irradiation-induced effects in emerging memories based on different memory materials, in particular, HfO2-, HfZrO2-, as well as GeSbTe-based thin films. This study reveals that the initial crystallinity, composition, and microstructure of the memory materials have a fundamental influence on their interaction with Au swift heavy ions. With this, we provide a test protocol for irradiation experiments of hafnium oxide- and GeSbTe-based emerging memories, combining structural investigations by X-ray diffraction on a macroscopic, scanning transmission electron microscopy on a microscopic scale, and electrical characterization of real devices. Such fundamental studies can be also of importance for future applications, considering the transition of digital to analog memories with a multitude of resistance states.

Electric field-induced crystallization of ferroelectric hafnium zirconium oxide.

Ferroelectricity in crystalline hafnium oxide thin films is strongly investigated for the application in non-volatile memories, sensors and other applications. Especially for back-end-of-line (BEoL) integration the decrease of crystallization temperature is of major importance. However, an alternative method for inducing ferroelectricity in amorphous or semi-crystalline hafnium zirconium oxide films is presented here, using the newly discovered effect of electric field-induced crystallization in hafnium oxide films. When applying this method, an outstanding remanent polarization value of 2P[Formula: see text] = 47 [Formula: see text]C/cm[Formula: see text] is achieved for a 5 nm thin film. Besides the influence of Zr content on the film crystallinity, the reliability of films crystallized with this effect is explored, highlighting the controlled crystallization, excellent endurance and long-term retention.

A FeFET with a novel MFMFIS gate stack: towards energy-efficient and ultrafast NVMs for neuromorphic computing.

The discovery of ferroelectricity in the fluorite structure based hafnium oxide (HfO2) material sparked major efforts for reviving the ferroelectric field effect transistor (FeFET) memory concept. A Novel metal-ferroelectric-metal-ferroelectric-insulator-semiconductor (MFMFIS) FeFET memory is reported based on dual ferroelectric integration as an MFM and MFIS in a single gate stack using Si-doped Hafnium oxide (HSO) ferroelectric (FE) material. The MFMFIS top and bottom electrode contacts, dual HSO based ferroelectric layers, and tailored MFM to MFIS area ratio (AR-TB) provide a flexible stack structure tuning for improving the FeFET performance. The AR-TB tuning shows a tradeoff between the MFM voltage increase and the weaker FET Si channel inversion, particularly notable in the drain saturation currentID(sat)when the AR-TB ratio decreases. Dual HSO ferroelectric layer integration enables a maximized memory window (MW) and dynamic control of its size by tuning the MFM to MFIS switching contribution through the AR-TB change. The stack structure control via the AR-TB tuning shows further merits in terms of a low voltage switching for a saturated MW size, an extremely linear at wide dynamic range of the current update, as well as high symmetry in the long term synaptic potentiation and depression. The MFMFIS stack reliability is reported in terms of the switching variability, temperature dependence, endurance, and retention. The MFMFIS concept is thoroughly discussed revealing profound insights on the optimal MFMFIS stack structure control for enhancing the FeFET memory performance.

Compensation of disorder for extraordinary optical transmission effect in nanopore arrays fabricated by nanosphere photolithography.

The work considers the effect of extraordinary optical transmission (EOT) in polycrystalline arrays of nanopores fabricated via nanosphere photolithography (NPL). The use of samples with different qualities of polycrystalline structure allows us to reveal the role of disorder for EOT. We propose a phenomenological model which takes the disorder into account in numerical simulations and validate it using experimental data. Due to the NPL flexibility for the structure geometry control, we demonstrate the possiblity to partially compensate the disorder influence on EOT by the nanopore depth adjustments. The proposed experimental and theoretical results are promising to reveal the NPL limits for EOT-based devices and stimulate systematic studies of disorder compensation designs.

Structural and Electrical Comparison of Si and Zr Doped Hafnium Oxide Thin Films and Integrated FeFETs Utilizing Transmission Kikuchi Diffraction.

The microstructure of ferroelectric hafnium oxide plays a vital role for its application, e.g., non-volatile memories. In this study, transmission Kikuchi diffraction and scanning transmission electron microscopy STEM techniques are used to compare the crystallographic phase and orientation of Si and Zr doped HfO2 thin films as well as integrated in a 22 nm fully-depleted silicon-on-insulator (FDSOI) ferroelectric field effect transistor (FeFET). Both HfO2 films showed a predominately orthorhombic phase in accordance with electrical measurements and X-ray diffraction XRD data. Furthermore, a stronger texture is found for the microstructure of the Si doped HfO2 (HSO) thin film, which is attributed to stress conditions inside the film stack during crystallization. For the HSO thin film fabricated in a metal-oxide-semiconductor (MOS) like structure, a different microstructure, with no apparent texture as well as a different fraction of orthorhombic phase is observed. The 22 nm FDSOI FeFET showed an orthorhombic phase for the HSO layer, as well as an out-of-plane texture of the [111]-axis, which is preferable for the application as non-volatile memory.

Systematic study of resonant transmission effects in visible band using variable depth gratings.

The article focuses on depth-dependent visible band transmission effects in a symmetrical "insulator-metal-insulator" diffraction system based on a variable depth grating. These effects were studied both experimentally and theoretically in TM and TE polarizations. In particular, the existence of an optimized grating depth for plasmon-mediated resonant transmission was confirmed experimentally, and differences in TE and TM transmission behavior are discussed. We utilize a simple and flexible fabrication approach for rapid synthesis of apodized structures with adiabatically varying depth based on a beat pattern of two interferential lithography exposures. The present study can be useful in the fields of transmission-based optical security elements and biosensors.

Surface Plasmon Resonance Based Temperature Sensors in Liquid Environment.

The aim of this work is to measure the temperature variations by analyzing the plasmon signature on a metallic surface that is periodically structured and immersed in a liquid. A change in the temperature of the sample surface induces a modification of the local refractive index leading to a shift of the surface plasmon resonance (SPR) frequency due to the strong interaction between the evanescent electric field and the metallic surface. The experimental set-up used in this study to detect the refractive index changes is based on a metallic grating permitting a direct excitation of a plasmon wave, leading to a high sensibility, high-temperature range and contactless sensor within a very compact and simple device. The experimental set-up demonstrated that SPR could be used as a non-invasive, high-resolution temperature measurement method for metallic surfaces.

Direct S-matrix calculation for diffractive structures and metasurfaces.

The paper presents a derivation of analytical components of S matrices for arbitrary planar diffractive structures and metasurfaces in the Fourier domain. The attained general formulas for S-matrix components can be applied within both formulations in the Cartesian and curvilinear metric. A numerical method based on these results can benefit from all previous improvements of the Fourier domain methods. In addition, we provide expressions for S-matrix calculation in the case of periodically corrugated layers of two-dimensional materials, which are valid for arbitrary corrugation depth-to-period ratios. As an example, the derived equations are used to simulate resonant grating excitation of graphene plasmons and the impact of a silica interlayer on corresponding reflection curves.

Periodic TiO2 Nanostructures with Improved Aspect and Line/Space Ratio Realized by Colloidal Photolithography Technique.

This paper presents substantial improvements of the colloidal photolithography technique (also called microsphere lithography) with the goal of better controlling the geometry of the fabricated nano-scale structures-in this case, hexagonally arranged nanopillars-printed in a layer of directly photopatternable sol-gel TiO2. Firstly, to increase the achievable structure height the photosensitive layer underneath the microspheres is deposited on a reflective layer instead of the usual transparent substrate. Secondly, an increased width of the pillars is achieved by tilting the incident wave and using multiple exposures or substrate rotation, additionally allowing to better control the shape of the pillar's cross section. The theoretical analysis is carried out by rigorous modelling of the photonics nanojet underneath the microspheres and by optimizing the experimental conditions. Aspect ratios (structure height/lateral structure size) greater than 2 are predicted and demonstrated experimentally for structure dimensions in the sub micrometer range, as well as line/space ratios (lateral pillar size/distance between pillars) greater than 1. These nanostructures could lead for example to materials exhibiting efficient light trapping in the visible and near-infrared range, as well as improved hydrophobic or photocatalytic properties for numerous applications in environmental and photovoltaic systems.

Microstructuring of Mesoporous Titania Films Loaded with Silver Salts to Enhance the Photocatalytic Degradation of Methyl Blue under Visible Light.

The microstructuring of the distribution of silver nanoparticles (NPs) in mesoporous titania films loaded with silver salts, using two-beam interference lithography leading to 1 Dimension (1D) grating, induces variations in the photocatalytic efficiency. The influence of the structuration was tested on the degradation of methyl blue (MB) under ultraviolet (UV) and visible illumination, giving rise to a significant improvement of the photocatalytic efficiency. The periodic distribution of the NPs was characterized by transmission electron microscopy (TEM), high-angle annular dark field scanning transmission electron microscopy (HAADF-STEM) and scanning electron microscopy (SEM).

Enhancing the Domain Wall Conductivity in Lithium Niobate Single Crystals.

Domain walls (DWs) in ferroelectric/ferroic materials have been a central research focus for the last 50 years; DWs bear a multitude of extraordinary physical parameters within a unit-cell-sized lateral confinement. Especially, one outstanding feature has recently attracted a lot of attention for room-temperature applications, which is the potential to use DWs as two-dimensional (2D) conducting channels that completely penetrate bulk compounds. Domain wall currents in lithium niobate (LNO) so far lie in the lower pA regime. In this work, we report on an easy-to-use and reliable protocol that allows enhancing domain wall conductivity (DWC) in single-crystalline LNO (sc-LNO) by 3 to 4 orders of magnitude. sc-LNO thus has become one of the most prospective candidates to engineer DWC applications, notably for domain wall transport both with and without photoexcitation. DWs were investigated here for several days to weeks, both before and after DWC enhancement. 2D local-scale inspections were carried out using adequate local-probe techniques, i.e., piezoresponse force microscopy and conductive atomic force microscopy, while Cerenkov second-harmonic generation was applied for mapping the DW constitution in three-dimensional space across the full LNO single crystal. The comparison between these nano- and microscale inspections allows us to unambiguously correlate the DW inclination angle α close to the sample surface to the measured domain wall current distribution. Moreover, ohmic or diode-like electronic transport characteristics along such DWs can be readily interpreted when analyzing the DW inclination profile.

Bottom-Up Assembly of Molecular Nanostructures by Means of Ferroelectric Lithography.

Here, we report on the photochemical deposition of Rhodamine 6G (Rh6G) and Alexa647 molecules from aqueous and methanolic solution along 180° ferroelectric (FE) domain walls (DWs) of z-cut lithium niobate (LNO) single crystals. Molecules and FE domains were investigated by means of dynamic-mode AFM, piezoresponse force microscopy (PFM), and confocal scanning fluorescence microscopy. A high deposition affinity for 180° DWs on the LNO surface is observed, leading to the formation of molecular nanowires. Additionally, a more complex deposition pattern for Rh6G adsorbed to the domain areas of freshly poled samples was equally observed, being associated with the DW dynamics. These results are explained by considering contributions from screening-charge-dependent photochemistry as confined to the DWs, UV-induced DW motion, and transient electrostatic fields arising from the metastable defect distribution shortly after poling. Hence, tuning these effects offers the possibility for accurately controlling the complex bottom-up assembly of functional molecular nanostructures through domain-structured ferroelectric templates.