Random Logic Research Articles

Swift heavy ion irradiation-induced enhancement of spin–orbit torque efficiency in Pt/Co/Ta trilayers

Increasing the efficiency of spin–orbit torque (SOT) is of great interest in applications for magnetic random access memory and logic devices due to decreased energy consumption. Here, we present that the SOT efficiency of Pt/Co/Ta films with perpendicular magnetic anisotropy can be improved by swift high-energy heavy Fe11+ ion irradiation, which is an effective method to alter crystallinity, interface roughness, and defects in ferromagnet/heavy metal heterostructures. Specifically, the Pt/Co/Ta films show an optimal SOT efficiency at ion fluence around 1.0 × 1013 ions/cm2 with the largest spin Hall angles reaching 0.59, which is the largest improvement of spin Hall angle by ion irradiation compared to previous studies using light ions. We demonstrate that the increase in SOT efficiency arises from structural changes in the Pt layer due to ion irradiation-induced damage effects at proper fluence, while the decrease in SOT efficiency is mainly attributed to the restoration of Pt crystallinity induced by beam-heating effects at high fluence. This work demonstrates that an appropriate ion irradiation process could improve the SOT efficiency and the spin Hall angle, thereby providing a way to develop future SOT-based spintronic devices.

Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network

This study introduced a novel ant colony optimization algorithm that implements the population selection strategy of the Estimation of Distribution Algorithm and a new pheromone updating formula. It aimed to optimize the performance of G-type random high-order satisfiability logic structures embedded in Discrete Hopfield Neural Networks, thereby enhancing the efficiency of the Hopfield Neural Network learning algorithm. Through comparative analysis with other metaheuristic algorithms, our model demonstrated superior performance in terms of global convergence, time complexity, and algorithm complexity. Additionally, we evaluated the learning phase, retrieval phase, and similarity analysis using various ratios of literals and clauses. It was shown that our proposed model exhibits stronger search ability compared to other metaheuristic algorithms and Exhaustive Search. Our model enhanced the efficiency of the learning phase, resulting in the number of global solutions accounting for 100 %, and significantly improved the global solution diversity. These advancements contributed to the efficiency of the model in convergence, rendering it applicable to a wide range of nonlinear classification and prediction problems.

Room-Temperature Antisymmetric Magnetoresistance in Van Der Waals Ferromagnet Fe3GaTe2 Nanosheets.

Van der Waals (vdW) ferromagnetic materials have emerged as a promising platform for the development of 2D spintronic devices. However, studies to date are restricted to vdW ferromagnetic materials with low Curie temperature (Tc) and small magnetic anisotropy. Here, a chemical vapor transport method is developed to synthesize a high-quality room-temperature ferromagnet, Fe3GaTe2 (c-Fe3GaTe2), which boasts a high Tc = 356 K and large perpendicular magnetic anisotropy. Due to the planar symmetry breaking, an unconventional room-temperature antisymmetric magnetoresistance (MR) is first observed in c-Fe3GaTe2 devices with step features, manifesting as three distinctive states of high, intermediate, and low resistance with the sweeping magnetic field. Moreover, the modulation of the antisymmetric MR is demonstrated by controlling the height of the surface steps. This work provides new routes to achieve magnetic random storage and logic devices by utilizing the room-temperature thickness-controlled antisymmetric MR and further design room-temperature 2D spintronic devices based on the vdW ferromagnet c-Fe3GaTe2.

Unveiling the mechanism behind the negative capacitance effect in Hf0.5Zr0.5O2-Based ferroelectric gate stacks and introducing a Circuit-Compatible hybrid compact model for Leakage-Aware NCFETs

This paper addresses the lack of understanding of the origin of negative capacitance (NC) effect in the hafnium zirconium oxide (HZO) ferroelectric (FE) gate stack and proposes a new circuit-compatible hybrid compact model for NC field-effect transistors (NCFETs). The model supports Landau and Preisach FE models, encompassing multiple FE domains, FE leakage, and FE damping. The proposed model is experimentally validated, and the intrinsic switching speed of HZO is predicted. It is revealed that the NC effect in HZO stems from a mismatch in free charge and polarization switching rates. Performance evaluation of the model reveals that HZO-NCFET achieves ∼1.18x and ∼9.17x higher amplification at low and high frequencies compared to its PZT-NCFET counterpart. Our study demonstrates the superior ON-current (2.74 mA/µm) of the Engineered Leaky-HZO NCFET, surpassing FinFET and Germanium-source L-shaped TFET by ∼7.89x and ∼4.81x, respectively. This study briefly examines the direct causes of the negative drain-induced barrier lowering effect and negative differential resistance effect in Landau NCFETs. Furthermore, we emphasize the crucial role of FE thickness in determining the magnitude of the NC effect, offering valuable insights for the design and optimization of NC-based devices and circuits. Analysis of the Miller effect in NCFET-based inverters demonstrates significant improvements owing to high ON-current and voltage amplification, making them suitable for high-speed NCFET-based circuitry. Landau and Preisach NCFET-based inverters exhibit (50.70%, 51.34%) lower overshoots and (28.45%, 28.61%) reduced propagation delay compared to the NC nanowire FET-based inverter. Moreover, NCFET-based 2:1 fork circuits significantly reduce (46.69%, 51.37%) critical clock skew compared to CMOS FET-based circuits, showcasing the potential of NCFET technology in addressing timing violations in random logic paths. Furthermore, the Landau and Preisach NCFET-based ring oscillators (ROs) achieve (39.97%, 49.38%) and (52.65%, 62.92%) higher oscillation frequencies (fOSC) compared to state-of-the-art graphene FET-RO and CMOS-RO, respectively. The 15-stage Leaky-HZO and Engineered Leaky-HZO NCFET-ROs outperform the double gate-FET-RO by ∼2.19x and ∼16.69x in terms of fOSC, highlighting their superior performance in frequency-domain metrics. These findings demonstrate the potential of NCFET-based digital and mixed-signal circuits for high-performance integrated circuit designs.

A 10-Channel, 120 nW/Channel Reconfigurable Capacitance-to-Digital Converter for Sub-μW Robust Wearable Sensing.

This paper presents a 10-channel, 120 nW/channel, reconfigurable capacitance-to-digital converter (CDC) enabling sub-μW wearable sensing applications. The proposed multi-channel architecture supports 10 channels with a shared reconfigurable 6-bit differential analog-to-digital converter (ADC). The reconfigurable nature of the CDC enables adaptive sensing range and sensing speed based on the target application. Furthermore, the architecture performs both on/off-chip parasitic correction and baseline calibration to measure the change in capacitance (ΔC), excluding baseline and parasitic capacitances. The experimental results show the measurement range of ΔC are 5.34 pF for 1x sensitivity and 1.8 pF for 3x sensitivity respectively. The capacitive divider-based architecture excludes power-hungry operational trans-impedance amplifiers for capacitance to voltage conversion, and the architecture supports programmable channel access to activate or deactivate each channel independently. The random interrupt protection logic avoids any broken sample or data error in a sampling window. Additionally, the channel monitoring logic helps keep track of specific channel information. The measured silicon result shows a total power consumption of 1.2 μW for 1.6 kHz sampling frequency when driven by a 32 kHz clock, which is 8.6x less than prior works. The CDC is also tested with DMMP (dimethyl-methylphosphonate) gas sensor in gas chromatography (GC). Implemented in 65 nm CMOS process, the 10-channel CDC occupies 0.251 mm2 of active area (0.0251 mm2/Ch).

LogicDT: a procedure for identifying response-associated interactions between binary predictors

Interactions between predictors play an important role in many applications. Popular and successful tree-based supervised learning methods such as random forests or logic regression can incorporate interactions associated with the considered outcome without specifying which variables might interact. Nonetheless, these algorithms suffer from certain drawbacks such as limited interpretability of model predictions and difficulties with negligible marginal effects in the case of random forests or not being able to incorporate interactions with continuous variables, being restricted to additive structures between Boolean terms, and not directly considering conjunctions that reveal the interactions in the case of logic regression. We, therefore, propose a novel method called logic decision trees (logicDT) that is specifically tailored to binary input data and helps to overcome the drawbacks of existing methods. The main idea consists of considering sets of Boolean conjunctions, using these terms as input variables for decision trees, and searching for the best performing model. logicDT is also accompanied by a framework for estimating the importance of identified terms, i.e., input variables and interactions between input variables. This new method is compared to other popular statistical learning algorithms in simulations and real data applications. As these evaluations show, logicDT is able to yield high prediction performances while maintaining interpretability.

Bio-Hash Secured Hardware e-Health Record System.

Dual securing strategy for all-hardware e-Health Record System is designed and developed for improved security and reduced Hardware Execution Time (HET). A compact novel Hashed Minutiae Random Fusion (HMRF) logic enables to achieve high irreversibility and increased non-reconstruction capability of the bio-template based Bio-Hash key. AES encryption of the patient's health data during Write mode and decryption during View mode are seamlessly performed through the lively generated key, yielding low HET through optimized slack. On the other hand, biometric controlled key retrieval during Read only mode for a single user access is performed on the pre-scrambled Bio-Hash key, to enable bypassed decryption (direct) of the Patient's health data for self-review. The proposed pseudo cascaded SHA-3 (Secured Hash Algorithm) architecture being the first stage in HMRF, hashes the biometric minutiae of both Patient (P) and Medical Practitioner (MP) with low Latency. Thus, facilitating in further lowering of the HET by reducing the clock count by one. The subsequent Random Compression Logic (RCL) skims the hashed value from 512 to 128 bits along with the help of priority compression logic (PCL) to achieve reduced bits handling thereby lowering the Power budget. Four fusion modes are leveraged to achieve better randomization and non-recoverability. Implementation of this HMRF logic on Virtex-7 (V7) FPGA device has yielded low Area of 4191 slices. Lesser Area of 11.6% is observed for this HMRF module compared to the reported design, excluding level shifter and PCL. Further, low HETs of 8.2/8.3/8.0 ns during Write/View/Read only modes respectively are being noticed. The dynamic Power dissipated for the three modes of operations are found to be 1.418/1.420/0.676 watts respectively.

Linear complementary pair of codes based lightweight RFID protocol

Data security and privacy is an essential topic in today’s life. It is necessary to prevent secret data from leakage. There are many services where data transfer is done without any physical contact and at a low-cost. Radio frequency identification (RFID) is one of the basic technical knowledge that solves the problem of data privacy. Many RFID protocols have been designed to ensure data security and privacy. But, a large portion of these protocols suffers from common security attacks and high computational costs. We present a lightweight RFID protocol based on linear complementary pair of codes to overcome these issues. This protocol ensures formal security using a random oracle model and BAN logic. For security verification of our protocol, we use the Scyther simulation tool. In addition, we compare the performance of our protocol in terms of storage costs, communication costs and computational costs with related existing protocols. We determine that our protocol gives preferable security and effectiveness over related competing protocols and is applicable for RFID systems.

Giant intrinsic magnetoresistance in spin-filtered tunnel junctions with ferrimagnetic electrode

In recent years, magnetic tunnel junctions (MTJs) have attracted strong research interest due to their potential use in nonvolatile memory technologies, such as magnetoresistive random access memory and magnetic logic applications. Half-metallic materials have been proposed as ideal electrode materials for MTJs to achieve large tunnel magnetoresistance (TMR) effects. Here, we design and investigate a spin-filter MTJ (sf-MTJ) consisting of a ferrimagnetic inverse Heusler alloy, ${\mathrm{Mn}}_{2}\mathrm{CoSi}$ as the electrode and CaS as the insulating tunnel barrier using ab initio quantum transport calculations. Our results demonstrate a high zero-bias voltage TMR ratio that initially oscillated before decreasing as the bias voltage increased. Despite the oscillatory TMR under bias voltage, the spin injection remains high and stable, highlighting the potential of sf-MTJs formed by ${\mathrm{Mn}}_{2}\mathrm{CoSi}$ electrodes for practical applications.

Giant tunneling magnetoresistance in in-plane double-barrier magnetic tunnel junctions based on MXene Cr2C.

The discovery of two-dimensional (2D) magnetic materials makes it possible to realize in-plane magnetic tunnel junctions. In this study, the transport characteristics of an in-plane double barrier magnetic tunnel junction (IDB-MTJ) based on Cr2C have been studied by density functional theory combined with the nonequilibrium Green's function method. The results showed its maximum tunneling magnetoresistance ratio (TMR) value reached 6.58 × 1010. Its minimum TMR value (3.86 × 106) was also comparable to those of conventional field effect transistors (FETs). Due to its giant TMR and unique structural characteristics, the IDB-MTJ based on Cr2C has great potential applications in magnetic random access memory (MRAM) and logic computing.

Flexible, Light-Interacting, B-Shaped Structures for Computations.

Integrating mechanical computing functions into robotic materials, microelectromechanical systems, or soft robotics can improve their intelligence in stimulation-response processes. Current mechanical computing systems exhibit limitations, including incomplete functions, unchangeable computing rules, difficulties in realizing random logic, and lack of reusability. To overcome these limitations, we propose a straightforward method of designing mechanical computing systems-based on the logic expressions-for complex computations. We designed soft, B-shaped mechanical metamaterial units, and compressed them to render stress inputs; the outputs are represented by the light-shielding effects caused by the unit deformations. We realized logic gates and corresponding combinations (including half/full binary adder/subtractor and addition/subtraction of 2 numbers with multiple bits) and provided a versatile solution for making a mechanical analog-to-digital converter to generate both ordered and disordered numbers. We performed all of the computations within the elastic regions of the B-shaped units; thus, after one computation, the systems can return to the initial states for reuse. The proposed mechanical computers will potentially enable robotic materials, microelectromechanical systems, or soft robotics to perform complex tasks. Furthermore, one can extend this concept to systems that are based on other mechanisms or materials.

Guest Editors' Words

Electronic Design Automation has been the driving force of VLSI design since those circuits are far more complex beyond what a human designer can comprehend. Today, the most advanced circuits have billions of components, mostly transistors, arranged in random logic, memory, data path, analog, mixed signal, IPs, etc. The process of automation of a large VLSI chip is extremely complex, generally decomposed into several categories and steps that are part of most existing commercial tool flows. Furthermore, timing and power optimization enable a wide range of applications we see today such as computing, mobile, internet of things (IoT), etc., and can only happen with creative innovations in EDA. For its complexity, any researcher in the field must invest heavily in finding and reading appropriate literature. In this special edition, the Journal of Integrated Circuits and Systems is collecting and surveying the key topics, algorithms and approaches that pertain to the current state-of-the-art in EDA research.

Extend 0.33 NA extreme ultraviolet single patterning to pitch 28-nm metal design by low-n mask

Extending 0.33 NA extreme ultraviolet single patterning to 28-nm pitch becomes challenging in stochastic defectivity, which demands high-contrast lithographic images. The low-n attenuated phase-shift mask (attPSM) can provide superior solutions for individual pitches by mitigating mask three-dimensional effects. The simulation and experiment results have shown substantial imaging improvements: higher depth of focus at similar normalized image log slope and smaller telecentricity error values than the best binary mask configuration. In this work, the exploration of low-n attPSM patterning opportunity for pitch 28-nm metal design is investigated. Using generic building block features, the lithographic performance of the low-n attPSM is compared with the standard binary Ta-based absorber mask. In addition, the impact of mask tone (bright field (BF) versus dark field) on the pattern fidelity and process window is evaluated both by simulations and experiments. The results indicate that BF low-n attPSM provides the best patterning performance. Consequently, the BF low-n attPSM patterning performance is assessed with an actual imec N3 pitch 28-nm random logic metal design. The wafer data indicate BF low-n attPSM enables good patterning fidelity, as well as good overall process window with high exposure latitude (∼20 % ).

Methodology for Structured Data-Path Implementation in VLSI Physical Design: A Case Study

State-of-the-art modern microprocessor and domain-specific accelerator designs are dominated by data-paths composed of regular structures, also known as bit-slices. Random logic placement and routing techniques may not result in an optimal layout for these data-path-dominated designs. As a result, implementation tools such as Cadence’s Innovus include a Structured Data-Path (SDP) feature that allows data-path placement to be completely customized by constraining the placement engine. A relative placement file is used to provide these constraints to the tool. However, the tool neither extracts nor automatically places the regular data-path structures. In other words, the relative placement file is not automatically generated. In this paper, we propose a semi-automated method for extracting bit-slices from the Innovus SDP flow. It has been demonstrated that the proposed method results in 17% less density or use for a pixel buffer design. At the same time, the other performance metrics are unchanged when compared to the traditional place and route flow.

Fast Operations of Nonvolatile Ferroelectric Domain Wall Memory with Inhibited Space Charge Injection

The microampere-level domain wall currents in LiNbO3 single crystals have promising applications in nonvolatile ferroelectric domain wall random access memory and logic with high-density integration, ultrafast operation speeds, and almost unlimited switching cycles. For the memory commercialization, the improvements of the reliability and operation speed of the devices are challenging due to the high-field charge injection. The injected charge could compensate the domain-wall boundary charge that screens the domain switching field and reduces the domain wall current. In this work, two kinds of memory nanocells were fabricated on the surfaces of X-cut LiNbO3 single crystals to study the geometry-dependent charge injection. The striped memory cell due to the appearance of the size-driven reconstruction has a smaller coercive field than that of a clamped memory cell without relaxation of the lattice matching stress, which reduces low-frequency charge injection and increases the domain switching speed. At an operating voltage of 5 V, we observed a retention time of more than 1 week and an on/off current ratio of 2 × 104 for a striped-like cell, paving the route to integrate energy-efficient high-density domain wall memory in high reliability.

Electrical Properties of New Carbon-Based Magnetic Nanomaterials and Spintronic Device Design

Magnetic thin films with perpendicular anisotropy have important application value in magnetic random access memory (MRAM), track storage, spin logic and other devices, which have attracted widespread attention. Among the current common spintronic devices, CoFeB thin films and Co/Ni multilayer films have become ideal magnetic thin film materials for spintronic devices due to their large vertical anisotropy (PMA) and low damping constant. At present, the latest technology requires the thickness of the film in spintronic devices to be on the order of nanometers, which puts forward higher requirements for the preparation of magnetic films. This involves some basic issues in materials science, so the research from the perspective of materials science in the preparation process of magnetic ultra-thin films, it is particularly important to discuss the influence of preparation conditions on its microstructure and magnetic properties. This article focuses on how to obtain CoFeB films and Co/Ni multilayer films with good vertical anisotropy, and investigates the effect of the thickness of the magnetic layer in the CoFeB film, the type of substrate layer, the growth mode and the film deposition sequence on the vertical anisotropy of the CoFeB film. Influence: The influence of the substrate layer on the vertical anisotropy of the multilayer film, and the influence of the thickness and period of the magnetic layer of the multilayer film on the magnetic properties and magnetic domain structure of the Co/Ni multilayer film are studied. The physical mechanism of the change of the thickness and the number of cycles of the magnetic layer affecting the magnetic domain structure of the multilayer film is discussed. The assembled asymmetric supercapacitor has a high energy density of 36.9 Wh kg-1 (power density of 400 W kg-1) and good cycle performance (83.9% is still retained after 5000 cycles).

A Difference-Equation-Based Robust Image Encryption Scheme with Chaotic Permutations and Logic Gates

Image encryption has become an indispensable tool for achieving highly secure image-based communications. Numerous encryption approaches have appeared and demonstrated varying degrees of robustness to adversarial attacks. In this paper, an efficient and robust image encryption algorithm is established based on randomized difference equations, random permutations and randomized logic circuits. Specifically, hyperchaotic and chaotic systems are used to generate pseudo-random sequences. These sequences are thus used to define random first-order difference equations, chaotic permutations and logic circuits. Image encryption based on these three randomized modules shows high computational efficiency as well as strong robustness against statistical, differential, and chosen-plaintext attacks. The proposed scheme leads to almost zero correlation in the encrypted images, entropy values of more than 7.99 for the test images, and a key space size of 2^{572}. Furthermore, differential analysis shows that the number of pixel change rate (NPCR) and the unified average change intensity (UACI) for the proposed technique are on average 99.61 and 33.35%, respectively.

Exploration of alternative mask for 0.33NA extreme ultraviolet single patterning at pitch 28-nm metal design

Extending 0.33NA extreme ultraviolet (EUV) single patterning to pitch 28 nm will enable significantly shorter process flow for N2 node and cost-efficiency of metal layers patterning. At the same time, EUV single patterning becomes very challenging in terms of stochastic defectivity and process window. To enable EUV single patterning at pitch 28 nm with good process window and patterning fidelity (low defectivity and line edge roughness), three mask candidates are considered: a standard binary Ta-based absorber mask, a high extinction (high-k) absorber mask, and a low-n attenuated phase-shift mask (attPSM). The patterning performance of these three mask candidates is compared by means of source mask optimization. The patterning performance of the candidate masks is assessed using an imec N3 (foundry N2 equivalent) random logic M1 layout. The impact of mask tonality (bright field versus dark field) and insertion of sub-resolution assist features (SRAFs) on pattern fidelity and process window is evaluated. Considering all the aspects, simulations indicate that the low-n attPSM has the best patterning performance both for dark-field mask with SRAFs and bright-field mask without SRAFs.

Evaluation of tree-based statistical learning methods for constructing genetic risk scores

BackgroundGenetic risk scores (GRS) summarize genetic features such as single nucleotide polymorphisms (SNPs) in a single statistic with respect to a given trait. So far, GRS are typically built using generalized linear models or regularized extensions. However, these linear methods are usually not able to incorporate gene-gene interactions or non-linear SNP-response relationships. Tree-based statistical learning methods such as random forests and logic regression may be an alternative to such regularized-regression-based methods and are investigated in this article. Moreover, we consider modifications of random forests and logic regression for the construction of GRS.ResultsIn an extensive simulation study and an application to a real data set from a German cohort study, we show that both tree-based approaches can outperform elastic net when constructing GRS for binary traits. Especially a modification of logic regression called logic bagging could induce comparatively high predictive power as measured by the area under the curve and the statistical power. Even when considering no epistatic interaction effects but only marginal genetic effects, the regularized regression method lead in most cases to inferior results.ConclusionsWhen constructing GRS, we recommend taking random forests and logic bagging into account, in particular, if it can be assumed that possibly unknown epistasis between SNPs is present. To develop the best possible prediction models, extensive joint hyperparameter optimizations should be conducted.

Assessment and Mitigation of Power Side-Channel-Based Cross-PUF Attacks on Arbiter-PUFs and Their Derivatives

Unintentional uncontrollable variations in the manufacturing process of integrated circuits are used to realize silicon primitives known as physical unclonable functions (PUFs). These primitives are used to create unique signatures for security purposes. Investigating the vulnerabilities of PUFs is of utmost importance to uphold their usefulness in secure applications. One such investigation includes exploring the susceptibility of PUFs to modeling attacks that aim at extracting the PUFs’ behavior. To date, these attacks have mainly focused on a single PUF instance where the targeted PUF is attacked using the model built based on the very same PUF’s challenge–response pairs or power side channel. In this article, we move one step forward and introduce <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Cross-PUF</i> attacks where a model is created using the power consumption of one PUF instance to attack another PUF created from the same GDSII file. Through SPICE simulations, we show that these attacks are highly effective in modeling PUF behaviors even in the presence of noise and mismatches in temperature and aging of the PUF used for modeling versus the targeted PUF. To mitigate the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Cross-PUF</i> attacks, we then propose a lightweight countermeasure based on dual-rail and random initialization logic approaches called DRILL. We show that DRILL is highly effective in thwarting <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Cross-PUF</i> attacks.