Logic Circuits Research Articles

Controlling the digital-to-analog switching in HfO2-based memristors via modulating the oxide thickness

The HfO2-based memristors have been acknowledged as a highly potential candidate for nonvolatile memory and neuromorphic computing applications. However, the analog resistive switching behavior of the HfO2-based memristors still needs improvement. In this work, Cu/HfO2/Pd devices with different oxide layer thicknesses were prepared by the magnetron sputtering process. The resistance switching characteristics related to oxide layer thickness were explored, revealing significant differences in the forming, SET, and RESET characteristics depending on oxide thickness. The conduction mechanism of the Cu/HfO2/Pd memristors is mainly attributed to the space charge limited current (SCLC) model. Thinner devices tend to show a more abrupt SET behavior and larger SET voltage, while thicker devices exhibit more gradual SET behavior and a lower SET voltage. In addition, as the thickness of the oxide layer increases, the Cu/HfO2/Pd memristors transition from digital resistive switching to analog resistive switching. The formation and rupture of oxygen vacancy filaments are predominant in thicker device, and the shape of the conduction filaments has been proposed as responsible for the abrupt and gradual changes in resistive switching. This work demonstrates that the thickness of the oxide layer plays an important role in engineering digital logic and neuromorphic behavior in HfO2-based memristors.

Molecular and Cellular Mechanisms of Motor Circuit Development.

Motor circuits represent the main output of the central nervous system and produce dynamic behaviors ranging from relatively simple rhythmic activities like swimming in fish and breathing in mammals to highly sophisticated dexterous movements in humans. Despite decades of research, the development and function of motor circuits remain poorly understood. Breakthroughs in the field recently provided new tools and tractable model systems that set the stage to discover the molecular mechanisms and circuit logic underlying motor control. Here, we describe recent advances from both vertebrate (mouse, frog) and invertebrate (nematode, fruit fly) systems on cellular and molecular mechanisms that enable motor circuits to develop and function and highlight conserved and divergent mechanisms necessary for motor circuit development.

A Novel Technique to Design GNRFET Based Ternary Logic Circuits for High-Performance Applications

A Novel Technique to Design GNRFET Based Ternary Logic Circuits for High-Performance Applications

All-optical combinational logical units featuring fifth-order cascade

Modern computational technologies are increasingly encountering significant limitations, driving a shift towards alternative paradigms such as optical computing. In this study, we introduce novel all-optical combinational logic units based on diffractive neural networks (D2NNs), designed to perform high-order logical operations both efficiently and swiftly using only two modulation layers. This innovative design offers increased processing speed, improved energy efficiency, robust environmental stability, and high error tolerance, making it exceptionally well-suited for a broad spectrum of applications in optical computing and communications. By leveraging transfer learning, we successfully developed a fifth-order cascaded combinational logic circuit for practical information transmission system. Furthermore, we reveal a pioneering application of our device in Optical Time Division Multiplexing (OTDM), demonstrating its capability to manage high-speed data transfer seamlessly without the need for electronic conversion. Extensive simulations and experimental validations highlight the potential of our model as a foundational technology for future optical computing architectures, paving the way toward more sustainable and efficient optical data processing platforms.

Control of spin–orbit torque-driven domain nucleation through geometry in chirally coupled magnetic tracks

The interfacial Dzyaloshinskii–Moriya interaction (DMI) can be exploited in magnetic thin films to realize lateral chirally coupled systems, providing a way to couple different sections of a magnetic racetrack and realize interconnected networks of magnetic logic gates. Here, we systematically investigate the interplay between spin–orbit torques, chiral coupling, and the device design in domain wall racetracks. We show that the current-induced domain nucleation process can be tuned between single-domain nucleation and repeated nucleation of alternate domains by changing the orientation of an in-plane patterned magnetic region within an out-of-plane magnetic racetrack. Furthermore, by combining experiments and micromagnetic simulations, we show that the combination of damping-like and field-like spin–orbit torques with DMI results in selective domain wall injection in one of two arms of a Y-shaped device depending on the current density. Such an element constitutes the basis of domain wall based demultiplexer, which is essential for distributing a single input to any one of the multiple outputs in logic circuits. Our results provide input for the design of reliable and multifunctional domain wall circuits based on chirally coupled interfaces.

Polarization Pruning: Reliability Enhancement of Hafnia-Based Ferroelectric Devices for Memory and Neuromorphic Computing.

Ferroelectric (FE) materials are key to advancing electronic devices owing to their non-volatile properties, rapid state-switching abilities, and low-energy consumption. FE-based devices are used in logic circuits, memory-storage devices, sensors, and in-memory computing. However, the primary challenge in advancing the practical applications of FE-based memory is its reliability. To address this problem, a novel polarization pruning (PP) method is proposed. The PP is designed to eliminate weakly polarized domains by applying an opposite-sign pulse immediately after a program or erase operation. Significant improvements in the reliability of ferroelectric devices are achieved by reducing the depolarization caused by weakly polarized domains and mitigating the fluctuations in the ferroelectric dipole. These enhancements include a 25% improvement in retention, a 50% reduction in read noise, a 45% decrease in threshold voltage variation, and a 72% improvement in linearity. The proposed PP method significantly improves the memory storage efficiency and performance of neuromorphic systems.

Generating logic circuit classifiers from dendritic neural model via multi-objective optimization

Inspired by biological neurons, a novel dendritic neural model (DNM) was proposed in our previous research to pursue a classification technique with simpler architecture, fewer parameters, and higher computation speed. The trained DNM can be transitioned to logic circuit classifiers (LCCs) by discarding unnecessary synapses and dendrites. Unlike conventional artificial neural networks with floating-point calculations, the LCC operates entirely in binary so it can be easily implemented in hardware, which has significant advantages in dealing with a high velocity of data due to its high computational speed. However, oversimplifying the model architecture will lead to the performance degeneration of LCC, and how to balance the architecture and performance is not well understood in practical applications. Therefore, the primary motivation of this study is twofold. First, a theoretical analysis is presented that the transition of LCCs from DNM can be regarded as a specific regularization problem. Second, a multiobjective optimization framework that can simultaneously optimize the classification performance and model the complexity of LCC is proposed to solve the problem. Comprehensive experiments have been conducted to validate the effectiveness and superiority of the proposed framework.

A DNA Molecular Logic Circuit for Precise Tumor Identification.

Tumor-associated antigens (TAAs) are not exclusively expressed in cancer cells, inevitably causing the "on target, off tumor" effect of molecular recognition tools. To achieve precise recognition of cancer cells, by using protein tyrosine kinase 7 (PTK7) as a model TAA, a DNA molecular logic circuit Aisgc8 was rationally developed by arranging H+-binding i-motif, ATP-binding aptamer, and PTK7-targeting aptamer Sgc8c in a DNA sequence. Aisgc8 output the conformation of Sgc8c to recognize PTK7 on cells in a simulated tumor microenvironment characterized by weak acidity and abundant ATP, but not in a simulated physiological environment. Through in vitro and in vivo results, Aisgc8 demonstrated its ability to precisely recognize cancer cells and, as a result, displayed excellent performance in tumor imaging. Thus, our studies produced a simple and efficient strategy to construct DNA logic circuits, opening new possibilities to develop convenient and intelligent precision diagnostics by using DNA logic circuits.

Energy Aware Technology Mapping of Genetic Logic Circuits.

Energy and its dissipation are fundamental to all living systems, including cells. Insufficient abundance of energy carriers -as caused by the additional burden of artificial genetic circuits- shifts a cell's priority to survival, also impairing the functionality of the genetic circuit. Moreover, recent works have shown the importance of energy expenditure in information transmission. Despite living organisms being non-equilibrium systems, non-equilibrium models capable of accounting for energy dissipation and non-equilibrium response curves are not yet employed in genetic design automation (GDA) software. To this end, we introduce Energy Aware Technology Mapping, the automated design of genetic logic circuits with respect to energy efficiency and functionality. The basis for this is an energy aware non-equilibrium steady state (NESS) model of gene expression, capturing characteristics like energy dissipation -which we link to the entropy production rate- and transcriptional bursting, relevant to eukaryotes as well as prokaryotes. Our evaluation shows that a genetic logic circuit's functional performance and energy efficiency are disjoint optimization goals. For our benchmark, energy efficiency improves by 37.2% on average when comparing to functionally optimized variants. We discover a linear increase in energy expenditure and overall protein expression with the circuit size, where Energy Aware Technology Mapping allows for designing genetic logic circuits with the energy efficiency of circuits that are one to two gates smaller. Structural variants improve this further, while results show the Pareto dominance among structures of a single Boolean function. By incorporating energy demand into the design, Energy Aware Technology Mapping enables energy efficiency by design. This extends current GDA tools and complements approaches coping with burden in vivo.

High‐Performance, Single‐Component Ambipolar Organic Electrochemical Transistors with Balanced n/p‐Type Properties for Inverter and Biosensor Applications

AbstractAmbipolar organic electrochemical transistors (OECTs) with a single organic mixed ionic‐electronic conductor (OMIEC) have unique advantages by reducing fabrication complexity and cost in complementary logic circuit and bioelectronic applications. However, the design and synthesis of high‐performance ambipolar OMIECs for efficient transport and coupling both cation/anion and electron/hole remain challenging. Herein, a donor–acceptor (D–A)‐typed ambipolar OMIEC polymer (DHF‐gTT) is presented, whose superior ambipolarity stems from the concurrent oligoethyleneglycol‐functionalized D/A units that facilitates cation/anion injection and transport. Additionally, the fluorination of acceptor unit improves both hole/electron transports due to the fully‐locked backbone and promotes electron injection by down‐shifting molecular energy levels. Consequently, DHF‐gTT‐based OECTs achieve balanced figure‐of‐merit (µC*) for both p‐type and n‐type operations (12.4–14.6 F cm−1 V−1 s−1), setting new benchmarks for ambipolar OECTs, in terms of n‐type µC* and electron/hole mobilities. Such ambipolar OECTs enable the inverter to achieve a record‐high gain (102 V/V) and associated n‐type and p‐type molecular detectors to offer real‐time and highly sensitive detection of histamine and hydrogen peroxide detection, respectively. These results indicate the effectiveness of judicious molecular design on achieving high‐performance ambipolar OMIECs, allowing the state‐of‐the‐art single‐component ambipolar OECTs for both highly integrated logic circuit and bioelectronic applications.

Sequence-Unconstrained DNA Computing: DSN cycling and PER circuitry for dynamic miRNAs analysis and multifunctional logic operations

DNA strand displacement and enzyme-driven catalysis are pivotal in regulating molecular interactions and constructing molecular logic circuits. However, their application in intricate hierarchical cascading networks has been hindered by sequence crosstalk restrictions on the multiple inputs and outputs. In this study, we present a sequence-unconstrained strategy to implement versatile molecular logic circuits, relying on duplex-specific nuclease (DSN)-assisted cycling and primer exchange reaction (PER) amplification circuitry (DSN-PER). Employing linear capture probe (CP) conjugated with magnetic beads (MBs) significantly minimizes crosstalk reactions compared to the previous molecular beacon probe (MBP) for DNA barcoding. Importantly, the sequence design of “barcodes” is fully independent of target binding sites on MBs, allowing for the sensitive detection of a broad range of microRNAs (miRNAs) using the DSN-PER method. Specifically, this platform supports the programming of common logic computations (YES, NOT, OR, INHIBIT, AND, and NOR) and hierarchical circuit operation (OR-AND) in response to a specific pattern of varying miRNAs. These versatile logic circuits offer unique features with flexible sequence design, potentially broadening the applications of dynamic nucleic acid nanotechnologies in multiplexed bio-computation, intelligent diagnostics, and sophisticated DNA nanodevices.

High-fidelity teleportation of a logical qubit using transversal gates and lattice surgery

Quantum state teleportation is commonly used in designs for large-scale quantum computers. Using Quantinuum’s H2 trapped-ion quantum processor, we demonstrate fault-tolerant state teleportation circuits for a quantum error correction code—specifically the Steane code. The circuits use up to 30 qubits at the physical level and employ real-time quantum error correction. We conducted experiments on several variations of logical teleportation circuits using both transversal gates and lattice surgery. We measured the logical process fidelity to be 0.975 ± 0.002 for the transversal teleportation implementation and 0.851 ± 0.009 for the lattice surgery teleportation implementation as well as 0.989 ± 0.002 for an implementation of Knill-style quantum error correction.

Automatic Test Pattern Generation for Robust Quantum Circuit Testing

Quantum circuit testing is essential for detecting potential faults in realistic quantum devices, while the testing process itself also suffers from the inexactness and unreliability of quantum operations. This article alleviates the issue by proposing a novel framework of automatic test pattern generation (ATPG) for robust testing of logical quantum circuits. We introduce the stabilizer projector decomposition (SPD) for representing the quantum test pattern and construct the test application (i.e., state preparation and measurement) using Clifford-only circuits, which are rather robust and efficient as evidenced in the fault-tolerant quantum computation. However, it is generally hard to generate SPDs due to the exponentially growing number of the stabilizer projectors. To circumvent this difficulty, we develop an SPD generation algorithm, as well as several acceleration techniques that can exploit both locality and sparsity in generating SPDs. The effectiveness of our algorithms are validated by (1) theoretical guarantees under reasonable conditions and (2) experimental results on commonly used benchmark circuits, such as Quantum Fourier Transform (QFT), Quantum Volume (QV), and Bernstein-Vazirani (BV) in IBM Qiskit.

Breast Tumor Diagnosis Based on Molecular Learning Vector Quantization Neural Networks.

DNA nanotechnology plays a crucial role in precise cancer medicine. Currently, molecular logic circuits are applied to detect tumor-specific biomarkers and control the release of therapeutic drugs. However, these systems lack self-learning capabilities for intelligent diagnostics in biological samples, and their data processing capabilities are limited. Here, a molecular learning vector quantization neural network (LVQNN) model based on DNA strand displacement (DSD) technology for breast tumor diagnosis is developed. Compared to previous work, the molecular LVQNN boasts powerful computing abilities, handling high-dimensional data for intelligent cancer diagnosis. To verify the feasibility and versatility of the network, two distinct typical datasets are selected: one from a single source with cell morphology data from 569 cases, and a more extensive one spanning different populations and ages, with miRNA gene expression data from 1881 cases. By using the molecular LVQNN, diagnostic experiments are conducted on 50 and 120 public individuals from these two datasets, respectively, achieving accuracy rates of 94% and 97.5%. This study demonstrates that the LVQNN model exhibits significant advantages in breast cancer diagnosis and enhances diagnostic accuracy while introducing new approaches for intelligent cancer diagnosis, anticipated to bring significant breakthroughs and application prospects to precise cancermedicine.

Intelligent Analysis of Avian Influenza Virus Biomarkers Based on Chemiluminescence Resonance Energy Transfer and DNA Logic Analysis.

A one-step logical analysis of multiple targets remains challenging. Herein, we report a one-pot and intelligent DNA logical analysis platform for the diagnosis of avian influenza virus (AIV) biomarkers based on chemiluminescence resonance energy transfer (CRET) and logic operations. On the surface of Lum/PEI/CaCO3 microparticles, the excited state of luminol underwent CRET with fluorescein isothiocyanate or rhodamine B isothiocyanate, producing three well-separated light emissions at 425, 530, and 590 nm, respectively. Taking advantage of the close distance between fluorophores aligned by the catalytic hairpin assembly reaction, the CRET efficiency was greatly enhanced (53.1%). H1N1, H7N9, and H5N1 were detected with limits of detection values as low as 15, 34, and 58 pM, respectively. Three-input logic circuits were simultaneously conducted on the surface of Lum/PEI/CaCO3 microparticles, enabling the rapid and accurate discrimination of multiple AIV biomarkers in one solution. In terms of peak positions and the normalized value of the total peak intensity, three biomarkers can be simultaneously discriminated without any other complex operations. In summary, the CRET-based multiple analytical assay was developed as an intelligent biosensor for identifying AIV biomarkers, having promising application prospects in the field of multiple analysis and precise disease diagnosis.

A Modified Current-Mode VCSEL Driver for Short-Range LiDAR Sensor Applications in 180 nm CMOS

This paper presents a modified current-mode vertical-cavity surface-emitting laser (VCSEL) driver as a transmitter for short-range light detection and ranging (LiDAR) sensors, where a stable bias generator is suggested with a regulated cascode current mirror circuit to provide the bias current of 1 mA with a trivial deviation of 5.4%, even at the worst-case process–voltage–temperature (PVT) variations. Also, a modified current-steering logic circuit is exploited with N-type MOSFET (NMOS) switches to deliver the modulation currents of 0.1~10 mApp to the VCSEL diode simultaneously, with no overshoot distortions. Post-layout simulations of the modified current-mode VCSEL driver (m-CMVD), using 180 nm CMOS technology, demonstrate very large and clean output pulses with significantly reduced signal distortions. Hereby, the VCSEL diode is transformed into an equivalent circuit with a 1.6 V DC voltage and a 50 Ω resistor for circuit simulations. The proposed m-CMVD consumes a maximum of 11 mW from a 3.3 V supply voltage and the chip core occupies an area of 0.196 mm2.

Tri‐Layer Heterostructure Channel of a‐IGZO/a‐ITZO/a‐IGZO Toward Enhancement of Transport and Reliability in Amorphous Oxide Semiconductor Thin Film Transistors

AbstractThin film transistors (TFTs) based on amorphous oxide semiconductors (AOS) are promising candidates for panel displays. However, the trade‐off between mobility and reliability in AOS‐TFTs hinders their further applications in next‐generation display techniques and newly developed logic and memory circuits. Here, a structural strategy is proposed for the mobility‐reliability trade‐off, via a triple‐layer channel containing a Ga‐free high‐mobility layer (amorphous InSnZnO, a‐ITZO) sandwiched by two Ga‐rich layers (amorphous InGaZnO, a‐IGZO) with higher reliability. Gate‐induced carrier accumulation is verified mainly being energetically confined within the high mobility a‐ITZO layer, at the newly defined a‐ITZO/a‐IGZO interface. Compared to single layer a‐ITZO‐TFTs, triple‐channel a‐IGZO/a‐ITZO/a‐IGZO TFTs (GTG‐TFTs) exhibit outstanding stability and electrical transport performances, with suppressed positive/negative‐bias‐stress voltage shifts from 1/0.3 to 0.1/0.004 V, enhanced field effect mobility from ≈40 to 56 cm2V−1s−1, and optimized sub‐threshold swing down to 80 mV dec−1. Further numerical simulations and charge transport characterizations, including magnetotransport and gate‐induced Hall effect, indicate that charge transport in tri‐layer structure is less affected by energetic disorders present at gate insulator interfaces.

Logical quantum circuits protected by the Steane code for specific noises in trapped ions

Logical quantum circuits protected by the Steane code for specific noises in trapped ions

High-Performance Ultraviolet to Near-Infrared Antiambipolar Photodetectors Based on 1D CdSxSe1-x/2D Te Heterojunction.

Antiambipolar heterojunctions are regarded as a revolutionary technology in the fields of electronics and optoelectronics, enabling the switch between positive and negative transconductance within a single device, which is crucial for diverse logic circuit applications. This study pioneers a mixed-dimensional photodetector featuring antiambipolar properties, facilitated by the van der Waals integration of one-dimensional CdSxSe1-x nanowires and two-dimensional Te nanosheets. This antiambipolar device enables flexible control over carrier transport via gate voltage, thus paving new paths for future optoelectronic devices. Furthermore, by precisely managing the stoichiometry of the ternary alloy CdSxSe1-x nanowires, fine-tuning of the nanowire band structure is achieved. This allows for customizable heterojunction band alignment (Type I and Type II), enabling adjustable band alignment. Through sophisticated band engineering, optimal Type II band alignment is achieved at the CdSxSe1-x/Te interface, significantly enhancing the device's photoelectric conversion efficiency through the synergistic effect of different dimensional materials. Exhibiting outstanding photoresponse across a broad spectral range from ultraviolet to near-infrared, especially under 450 nm illumination, the CdSxSe1-x/Te heterojunction photodetector demonstrates superior performance, including an impressive responsivity of 284 A W-1, a high detectivity of 1.07 × 1017 Jones, an elevated external quantum efficiency of 7.83 × 104 %, and a swift response time of 11 μs. Ultimately, this customizable antiambipolar photodetector lays a solid foundation for the advancement of next-generation optoelectronic technologies.

Design of ternary reversible Feynman and Toffoli gates in ternary quantum-dot cellular automata

The use of reversible logic gates leads to a reduction in energy loss in logic circuits by preventing information loss. New computing methods, such as quantum-dot cellular automata (QCA), have been offered by nanotechnology emerging with nanoelectronics to make more comprehensive logic circuits. In nanotechnology-based systems, some bits are erased when the system performs any computation, and this causes heat dissipation and energy loss in systems. Adder circuits are the basis of any arithmetic operation and one of the main parts of many circuits for creating complex hardware; therefore, the use of enhanced adder circuits leads to high performance in logic circuits. In irreversible logic, the energy that is transferred from the power supply to the circuit is converted into heat, and energy loss occurs. Power management plays a vital role in modern computational systems, and using ternary logic instead of previous technologies leads to better performance. The main purpose of our study is to design ternary quantum-dot cellular automata (TQCA) reversible logic gates based on ternary quantum-dot cellular technology. Reversible gates are the basis of creating a reversible circuit. In this paper, the Muthukrishnan-Stroud (M-S) gate, which is the basis of all other reversible ternary gates, is implemented in ternary QCA technology, and then, reversible ternary Feynman and Toffoli (C2NOT) gates are designed. More optimal adder circuits can be realized in three-valued technology using Feynman and Toffoli gates. The area, delay, and cell count of the proposed TQCA designs are compared with those of other related works, and the effect of fault on the designs in the presence of cell omission defect is determined. The occupied areas of the proposed Feynman and Toffoli gate designs are 0.069 μm2 and 0.073 μm2, respectively. Moreover, the fault tolerance levels of these TQCA gates are 77% and 92%, respectively.