Switching Ratio Research Articles

Optimization of the memristor fabrication based on graph convolutional network

Abstract In this article, a machine learning model for accurately predicting the performance of unknown memristors is constructed by employing a graph convolutional network approach. Thickness and elemental composition are used to transform memristors into graph-structured data. This model exhibits high accuracy and, based on extensive training with a certain type of memristor data, can be applied to novel memristors and give rapid predictions of the performance with only a small-batch sample reported in the literature, showing the potential for excellent transfer learning. This model is also applied to predict the performance of halide memristors, which have received less attention in current research, and it is indeed that a halide perovskite memristor with potential high switching ratio is predicted.

Polarization insensitive electrically reconfigurable meta-lens for the 2 µm wavelength

The conventional fiber communication band of 1.55 µm is reaching its limit attributable to the escalation in bandwidth requirements for high-speed and bulk data transmission. Researchers are exploring a 2 µm waveband for its higher capacity and low attenuation as a solution for the next generation communication technologies. Accordingly, here we report an optically engineered metasurface for this waveband for fiber coupling or lensing. The structure is polarization-insensitive and dynamically tunable between its reflective (OFF) and transmissive (ON) modes. For tunability, we incorporate a novel phase change material In3SbTe2 (IST) for its faster, non-volatile, and reversible metallic-to-insulator phase transition. The integration of indium tin oxide (ITO) as a micro-heater to electrically modulate the light by altering the phase of IST provides the device with additional functionality for point-of-care applications. Using the finite-difference-time-domain (FDTD) technique, we have achieved a modulation depth of 90%. The focusing efficiency is as high as 76% and the ON-OFF switching ratio of the optimized lens is 26 dB. The multilayer insertion of thin IST ensures uniform phase transition with switching energy as low as 232.98 nJ/µm2. Thus, with remarkable performance at 2 µm and dynamic multifunctionality, our proposed device will revolutionize the upcoming telecommunication technologies and beyond.

Low power tactile sensory neuron using nanoparticle-based strain sensor and memristor

Endowing strain sensors with neuromorphic computing capabilities could permit the efficient processing of tactile information on the edge. The realization of such functionalities from a simple circuit without software processing holds promise for attaining skin-based perception. Here, leveraging the intrinsic neuronal plasticity of memristive neurons, various firing patterns induced by the applied strain were demonstrated. More specifically, tonic, bursting, transition from tonic to bursting, adaptive, and nociceptive activities were captured. The implementation of these patterns permits the facile translation of the analog pressure signals into digital spikes, attaining accurate perception of various tactile characteristics. The tactile sensory neuron consisting of an RC circuit was composed of a SiO2-based conductive bridge memristor exhibiting leaky integrate-and-fire properties and a Pt nanoparticles (NPs)-based strain sensor with a gauge factor of ∼270. A dense layer of Pt NPs was also used as the bottom electrode for the memristive element, yielding the manifestation of a threshold switching mode with a switching voltage of only ∼350 mV and an exceptional switching ratio of 107. Our work provides valuable insights for developing low power neurons with tactile feedback for prosthetics and robotics applications.

First-principles studies of strain-tunable InN monolayer: applications for switching and optoelectronic devices

Abstract Two-dimensional (2D) materials are attracting significant attention for their potential applications in the post-Moore era. In this work, we systematically investigate the effect of strains on the electronic structure, transport and optoelectronic properties of 2D Indium nitride (InN) monolayer using density functional theory and non-equilibrium Green’s function methods. The results show that strains can modulate the electronic properties. Specifically, biaxial strain triggers the transition from semiconductor to metal and indirect to direct band gap. On this basis, the constructed InN-based nanodevice exhibits current switching ratios up to 1010. In addition, the optoelectronic device based on InN monolayer exhibits a robust photoelectric response in the red light. Meanwhile, biaxial strain can improve the optoelectronic performance of InN-based optoelectronic devices. The compressive strains blue-shift the photocurrent peaks of the InN monolayer, which effectively modulates its detection range in the visible light region. These findings underscore the potential applications in nanotechnology, particularly in nano-switches and optoelectronic devices.

A Single-Crystal Antimony Trioxide Dielectric for 2D Field-Effect Transistors.

The remarkable potential of two-dimensional (2D) materials in sustaining Moore's law has sparked a research frenzy. Extensive efforts have been made in the research of utilizing 2D semiconductors as channel materials in field-effect transistors. However, the next generation of integrated devices requires the integration of gate dielectrics with wider bandgaps and higher dielectric constants. Here, insulating α-Sb2O3 single-crystal nanosheets are synthesized by one-step chemical vapor deposition method. Importantly, the α-Sb2O3 single-crystal dielectric exhibits a high dielectric constant of 11.8 and a wide bandgap of 3.78 eV. Besides, the atomically smooth interface between α-Sb2O3 and MoS2 enables the fabrication of dual-gated field-effect transistors with the top gate dielectric of α-Sb2O3 nanosheets. The field-effect transistors exhibit a switching ratio of exceeding 108, which achieves the manipulation of field-effect transistors by using 2D dielectric materials. These results hold significant implications for optimizing the performances of 2D devices and innovating microelectronics.

Ultra-sensitive dengue NS1 protein detection via asymmetric source-drain, heterojunction and dual-dielectric cavities in a uniform tunnel FET biosensor

In this paper, we present a unique Asymmetric Source-Drain Heterojunction Dual-Dielectric Uniform Tunnel Field Effect Transistor (A-SD-HJ-DD-UTFET) based biosensor tailored for the early detection of dengue NS1 protein during the acute phase of infection offering early diagnosis and potentially life-saving intervention. The proposed biosensor design features simplified fabrication, a narrow drain region, and a dual material control gate, enhancing specificity and sensitivity for dengue virus detection. Using a heterojunction configuration, this device optimizes electron flow for improved detection accuracy. The roles of Tunnel Gate (TG) and Auxiliary Gate (AG) are studied in terms of band energy, electric field, electrostatic potential, and other sensitivity parameters. Sentaurus TCAD tool is utilized for analyzing the characteristics of the proposed A-SD-HJ-DD-UTFET biosensor. Simulation results indicate that the designed A-SD-HJ-DD-UTFET biosensor achieves a superior Subthreshold Swing (SS) of 15.4 mV/dec and an enhanced ION/IOFF sensitivity of about 2.25 × 10¹¹ with a maximum ON and minimum OFF state currents of 2.28 × 10–4 A/μm and 1.28 × 10–16 A/μm respectively for detecting NS1 protein of dengue. Additionally, it boasts a high switch ratio in the order of 1012. The proposed biosensor outperforms conventional devices, including the state-of-the-art Junctionless (JL)-TFET biosensors. The superior electrical characteristics of the proposed A-SD-HJ-DD-UTFET biosensor make it a promising device for early detection of the dengue NS1 protein, providing a potent solution for mitigating the spread of dengue infections.

Synaptic Properties of an Interfacial Memristor Based on a Ga2O3/Nb:SrTiO3 Heterojunction.

Memristors have been extensively studied for tremendous potential for future neuromorphic computing hardware applications because of their ability to imitate biological synaptic processes. Herein, we report an interfacial memristor based on a Ga2O3/Nb:SrTiO3 heterojunction that shows stable bipolar resistive switching behavior, long retention time, and high switching ratio. The conductance of the Au/Ga2O3/Nb:SrTiO3/In memristor can be gradually modulated under the voltage sweep mode as well as positive and negative pulse voltage stimulations, respectively, thus realizing the long-term potentiation/depression characteristics of the simulated biological synapse. A neural network based on the prepared memristor was built to recognize the handwritten picture data set with a recognition accuracy of 92.78% by using the NeuroSimV3.0 platform. Our work indicates that the Ga2O3/Nb:SrTiO3 heterojunction memristor has significant potential in a neuromorphic computing system.

Toward Ultrathin: Advances in Solution-Processed Organic Semiconductor Transistors.

In recent years, organic semiconductor (OSC) ultrathin films and their solution-processed organic field-effect transistors (OFETs) have garnered attention for their high flexibility, light weight, solution processability, and tunable optoelectronic properties. These features make them promising candidates for next-generation optoelectronic applications. An ultrathin film typically refers to a film thickness of less than 10 nm, i.e., several molecular layers, which poses challenges for OSC materials and solution-processed methods. In this paper, first we introduce the carrier-transport regulation mechanism under ultrathin limits. Second, we summarize various solution-processed techniques for OSC ultrathin films and elucidate advances in their OFETs performance, such as enhanced or maintained mobilities, improved switching ratios, reduced threshold voltages, and minimized contact resistance. The relationship between the ultrathin-film thickness, microstructure of various OSCs (small molecules and polymers), and device performance is discussed. Third, we explore the recent application of OSC ultrathin-film-based OFETs, such as gas sensors, biosensors, photodetectors, and ferroelectric OFETs (Fe-OFETs). Finally, the conclusion is drawn, and the challenges and prospects of ultrathin OSC transistors are presented. Nowadays, research on ultrathin films is still in its early stages; further experience in precise film deposition control is crucial to advancing research and broadening the scope of applications for OSC ultrathin devices.

Field‐Free Spin‐Orbit Torque Switching in Perpendicularly Magnetized Ta/CoFeB/MgO/NiO/Ta with a Canted Antiferromagnetic Insulator NiO Interlayer

AbstractIn this study, deterministic current‐induced spin‐orbit torque (SOT) magnetization switching is achieved, particularly in systems with perpendicular magnetic anisotropy (PMA), without the need for a collinear in‐plane field, a traditionally challenging requirement. In a Ta/CoFeB/MgO/NiO/Ta structure, spin reflection at the MgO/NiO interface generates a spin current with an out‐of‐plane spin polarization component σz. Notably, the sample featuring 0.8 nm MgO and 2 nm NiO demonstrates an impressive optimal switching ratio approaching 100% without any in‐plane field. A systematic investigation of the effects of the MgO and NiO thickness demonstrates that the formation of noncollinear spin structures and canted magnetization in the ultrathin NiO interlayer plays a pivotal role to the field‐free SOT switching. The integration of NiO as an antiferromagnetic insulator effectively mitigates current shunting effects and enhances the thermal stability of the device. This advancement in the CoFeB/MgO system holds promise for significant applications in spintronics, marking a crucial step toward realizing innovative technologies.

Scalable Synaptic Transistor Memory from Solution-Processed Carbon Nanotubes for High-Speed Neuromorphic Data Processing.

Neural networks as a core information processing technology in machine learning and artificial intelligence demand substantial computational resources to deal with the extensive multiply-accumulate operations. Neuromorphic computing is an emergent solution to address this problem, allowing the computation performed in memory arrays in parallel with high efficiencies conforming to the neural networks. Here, scalable synaptic transistor memories are developed from solution-sorted carbon nanotubes. The transistors exhibit a large switching ratio of over 105, a significant memory window of ≈12V arising from charge trapping, and low response delays down to tens of nanoseconds. These device characteristics endow highly stabilized reconfigurable conductance states, successful emulation of synaptic functions, and a high data processing speed. Importantly, the devices exhibit uniform characteristic metrics, e.g., with a 1.8% variation in the memory window, suggesting an industrial-scale manufacturing capability of the fabrication. Using the memories, a hardware convolution kernel is designed and parallel image processing is demonstrated at a speed of 1M bit per second per input channel. Given the efficacy of the convolution kernel, a promising prospect of the memories in implementing neuromorphic computing is envisaged. To explore the potential, large-scale convolution kernels are simulated and high-speed video processing is realized for autonomous driving.

Nonvolatile logic inverters based on 2D CuInP2S6 ferroelectric field effect transistors

With the capability of in-memory computing, integrated nonvolatile logic devices can mitigate the back-and-forth movement of data between storage and logic units, thus effectively enhancing computational speed and reducing power consumption. In this work, two-dimensional (2D) CuInP2S6, which reveals robust polarization within a few nanometer thicknesses, was utilized as gate dielectric for ferroelectric field effect transistor (FeFET). Device with a ReS2 channel demonstrated a high on/off ratio of current of 105, accompanied by a substantial hysteresis window of 2.8 V. Additionally, ReS2 FETs, gated with an h-BN layer, exhibited a switch ratio of 108 and minimal hysteresis of 61.6 mV at room temperature, attributed to the atomically flat heterointerface with negligible traps. Leveraging the performance of these devices enabled the creation of a nonvolatile logic inverter, wherein the ReS2/h-BN FET acts as the load transistor, and ReS2/h-BN/CIPS FeFET serves as the driving unit. This configuration stably operates with low power consumption of 0.45 μW and outstanding retention exceeding 1000 s. This work presents a viable device architecture for designing nonvolatile logic circuits applicable in in-memory computing.

Optimization and analysis of Si/SiGe strained vertically stacked heterostructure on insulator FeFinFET for high performance analog and RF applications

As semiconductor technology advances, the exploration of novel materials and device architectures becomes imperative to meet the growing demands of integrated circuits for analog and radio-frequency (RF) applications. In this paper, various advanced technologies have been amalgamated such as integration of ferroelectric layer in multigate FinFET along with the adaptation of SOI technology. Further strain technology is also used which employs a tri-layered strained-silicon channel system with the help of SiGe to form Vertically Stacked Heterostructure on Insulator Ferroelectric based FinFET (VS-HOI-FeFinFET) and on comparison with baseline FeFinFET, it is found to show remarkable improvements in terms of various measured parameters such as drain current, switching ratio, threshold voltage and subthreshold swing. Subsequently, gate stacking architecture is incorporated in VS-HOI-FeFinFET to further optimize the device performance. The four different configurations C1 to C4 are taken in terms of four different combinations of gate stack materials considered for gate oxide such as C1(SiO2+Al2O3), C2(SiO2+HfO2), C3(Al2O3), and C4(Al2O3+HfO2). It is found that the static and analog performance of VS-HOI-GS-FeFinFET enhance sequentially from configuration C1 to C4 such as switching ratio is enhanced upto around 5 times, DIBL and quality factor are improved by around 41% and 58% respectively along with significant improvement in device efficiency, early voltage, intrinsic gain, output conductance and output resistance. Subsequently performance optimization of VS-HOI-GS-FeFinFET with variation in mole fraction of germanium is also explored for various analog metrics. Further, several RF parameters are also explored and it is observed that the gain frequency product (GFP) and gain transconductance frequency product (GTFP) are augmented by around three times in magnitude along with 16% reduction in the unity gain cut off frequency in C4 configuration, exhibiting its ability of high frequency amplification with minimized noise distortion thus makes the device suitable for various high performance Analog and RF applications.

A multilevel resistive switching memristor based on flexible organic–inorganic hybrid film with recognition function

Abstract Brain-inspired neuromorphic computing systems fueled the emergence of memristor-based artificial synapses, however, conventional silicon-based devices restricted their usage in the wearable field because of their difficulty in bending. To tackle the above challenge, a vertically structured flexible memristor with aluminum-based hydroquinone organic–inorganic hybrid film and Al2O3 as the functional layer, ITO and Pt as the bottom and top electrodes, and PET as the substrate has been developed utilizing molecular/atomic layer deposition to achieve a tradeoff between the resistive transition properties and the flexibility of memristors. The obtained devices combine stable resistive switching behavior and flexibility, showing high switching ratio of 103, better retention (up to 105 s) and endurance properties (up to 104 cycles), and robustness at radius of curvature of 4.5 mm after 104 bending cycles. Furthermore, the presence of multilevel resistive states in these devices ensures that the memristor can emulate synaptic properties such as paired-pulse facilitation, transition from short-term plasticity to long-term plasticity, long-term potentiation and depression, and spike-time-dependent plasticity. The resistive switching mechanism and the role of the bending state on the electrical performance of the device are explored. The fully connected artificial neural network based on the memristor can achieve a recognition accuracy of 90.2% for handwritten digits after training and learning. Flexible memristor will bring feasible advances to the integration of neuromorphic computing and wearable functionality.

Scalable In2S3 based optical memristor devices as artificial synapse for logic realization and neuromorphic computing

This paper presents the scalable production of indium sulfide (In2S3) based optical memristors as an artificial synapse for logic realization and neuromorphic computing applications. The optical memristor device's performance was tested using the electrical and optical stimulation (ultraviolet (UV) to near infrared (NIR)) at room temperature. The memristor has shown the improved performance metrics for optical stimulation as compared to electrical stimulation. The In2S3 based optical memristor offers a resistance switching ratio of ∼103 at room temperature. In addition, the memristor has ultra-fast program and reprogram capability (38.8/39 μs) at 880 nm. Moreover, stability/scalability of the device was tested using the cycle-to-cycle variability test at different modulated frequencies. The electrical and optical signals were used as an input for logic gate realization. The neuromorphic computing model was implemented to predict the digits and alphabets with an accuracy of 98.19 % and 99.18 % respectively. These demonstrated optical memristors can be the key technology for future memory devices that surpass the limitations of von-Neumann bottleneck.

High-speed Ta2O5-based threshold switching memristor for LIF neurons

Due to their high similarity to biological ion channels, low power consumption, small footprint, and the fact that they do not require reset circuits, threshold switching memristors have been intensively studied for simulating neurons in neuromorphic chips. Switching speed is one of the key challenges which limit the application of threshold switching memristors in chips. In this study, Ta2O5 threshold switching memristors with high switching speeds were prepared by doping with silver. The results show that 14 wt. % Ag doped Ta2O5 threshold switching memristors exhibit excellent bi-directional threshold switching performance, featuring fast switching speeds (<20 ns, <18 ns), low leakage currents (<10 pA), and high switching ratio (>107). According to the field nucleation theory, the rapid switching speed can be attributed to the low nucleation energy (0.26 eV) of silver within the Ta2O5 matrix, which is achieved by incorporating 14 wt. % Ag during the doping process. Based on Pspice, a LIF (leaky integrate-and-fire) neuron based on the silver nanoparticles doped Ta2O5 threshold switching memristors is built, and its firing function has been simulated. The results show that the LIF neuron with a short switching time is able to excite pulse spiking with high frequencies. These results demonstrated that the silver nanoparticles doped Ta2O5-based threshold switching memristors hold significant potential for constructing high-speed artificial neural networks.

Octopus-Inspired Adhesives with Switchable Attachment to Challenging Underwater Surfaces.

Adhesives that excel in wet or underwater environments are critical for applications ranging from healthcare and underwater robotics to infrastructure repair. However, achieving strong attachment and controlled release on difficult substrates, such as those that are curved, rough, or located in diverse fluid environments, remains a major challenge. Here, an octopus-inspired adhesive with strong attachment and rapid release in challenging underwater environments is presented. Inspired by the octopus's infundibulum structure, a compliant, curved stalk, and an active deformable membrane for multi-surface adhesion are utilized. The stalk's curved shape enhances conformal contact on large-scale curvatures and increases contact stress for adaptability to small-scale roughness. These synergistic mechanisms improve contact across multiple length scales, resulting in switching ratios of over 1000 within ≈30 ms with consistent attachment strength of over 60 kPa on diverse surfaces and conditions. These adhesives are demonstrated through the robust attachment and precise manipulation of rough underwater objects.

Label-free biomolecule detection with dielectrically modulated double gate single cavity InGaAs/GaAsSb HTFET: Design considerations and performance evaluation

Dielectrically Modulated Double Gate Single Cavity InGaAs/GaAsSb HTFET (DMDG–SC–InGaAs/GaAsSb HTFET) is a novel label-free, nanocavity embedded dielectrically modulated heterostructure TFET-based biosensor. The III-V heterostructure (InGaAs/GaAsSb) has a high ION/IOFF ratio, better gate control, and higher tunnelling probability. In order to effectively reduce ambipolarity, asymmetrical doping is used at the p+ source and n+ drain, along with gate work function engineering. The stacked layers of HfO2/SiO2 gate oxide help to reduce the fringing electric field. The suggested device utilizes a dielectrically controlled technique to achieve biomolecule conjugation. This is done by etching a single nanogap cavity in the gate dielectric material towards the source end. An evaluation of the dielectric constants [K = 2.1, 2.63, 3.30, 6.3, and 12] of neutral and charged biomolecules compared to air [k = 1] is essential to determine the sensitivity of biosensors in an arid environment. The transconductance-to-current ratio (gm/Ids), switching ratio (ION/IOFF), and threshold voltage are the performance metrics used to evaluate the device sensitivity. The DM-DG–SC–InGaAs/GaAsSb HTFETpromises to be very sensitive while using less power during the detection process. It also shows that it could be a good choice for label-free biosensor applications.

The influence of structural defects on the electrical and infrared emission properties of VO2 thin films

Defect engineering is widely used in the modification of transition metal oxides. In this study, defects are introduced into the polycrystalline VO2 film by the energetic Ar ion irradiation, and the influence of structural defects on the electrical and infrared emission properties of VO2 thin films have been investigated. The decrease in electrical switching ratio with the increase of defect ratio (displacement per atom (dpa)) can be described as R10°C/R90°C=2.032×(dpa+0.005)−1.8069, while the infrared modulation performance is Δε=−0.119×ln(dpa+0.061). The dpa thresholds of the electrical switching ratio and the infrared modulation performance are ηdpaRR = 0.005/atom and ηdpaΔε = 0.0426/atom, respectively, indicating that the electrical switching ratio of VO2 films is more responsive to defects than the infrared modulation performance. The relationship between transition temperature and defect ratio has be determined. Concerning electrical properties, the heating phase transition temperature can be described as TMITHeating=25.88−10.93×ln(dpa+0.01); while for infrared emission modulation, the heating phase transition temperature is given by Tε−MITHeating=31.65−8.18×ln(dpa+0.01). While reducing the phase transition temperature, the VO2 thin films still exhibit an electrical switching ratio of more than two orders of magnitude and obvious infrared modulation performance. It not only offers a viable solution for broadening the application scope of VO2 but also contributes to understanding the role of defects in VO2 thin films for further research.

A Flexible Multifunctional Sensor Based on an AgNW@ZnONR Composite Material.

A multifunctional sensor comprising flexible and transparent ultraviolet (UV) photodetectors (PDs) with strain gauges based on Ag nanowire (AgNW)@ZnO nanorods (ZnONRs) was fabricated using a cost-effective, simple, and efficient method. High-aspect ratio silver nanowires were synthesized using the polyol method. An AgNW@ZnONR composite was formed via the hydrothermal method to ensure the multifunctional capability of the flexible sensors. After refining the process parameters, the size of the ZnO nanorods was decreased to fabricate pliable multifunctional sensors using AgNW@ZnONRs. At a deposition of 0.207 g of AgNW@ZnONRs, the sensor achieves its maximum switching ratio and fastest response time under conditions of 2000 μW/cm2 UV optical power density. With a ton (rise time) of 2.7 s and a toff (fall time) of 2.3 s, the ratio of Ion to Ioff current is 1151. Additionally, the sensor's maximum optical current value correlates linearly with UV light's power density. The maximum response current increased from 222.5 pA to 588.1 pA, an increase of 164.3%, when the bending angle was increased from 15° to 90° for the sensor with a deposition of 0.276 g of AgNW@ZnONRs. There was no degradation in the response of the sensors after 10,000 bending cycles, as they have excellent stability and repeatability, which means they can meet the requirements of wearable sensor applications. Therefore, there is great potential for the practical application of multifunctional AgNW@ZnONRs in flexible sensors.

Reliability Enhancement of a Double-Switch Single-Ended Primary Inductance–Buck Regulator in a Wind-Driven Permanent Magnet Synchronous Generator Using a Double-Band Hysteresis Current Controller

The wind power exchange system (WECS) covered in this paper consists of a voltage source inverter (VSI), a DSSB regulator, and an uncontrolled rectifier. An AC grid or a heavy inductive or resistive load (RL) can be supplied by this system. The DSSB is a recently developed DC-DC regulator consisting of an improved single-ended primary inductance regulator (SEPIC) followed by a buck regulator. It has a peak efficiency of 95–98% and a voltage gain of (D (1+D)/(1−D). where D is the regulator transistor’s on-to-off switching ratio. The proposed regulator improves the voltage stability and MPPT strategy (optimal or maximum power-point tracking). The combination of the DSSB and the proposed regulator improves the efficiency of the system and increases the power output of the wind turbine by reducing the harmonics of the system voltages and current. This method also reduces the influence of air density as well as wind speed variations on the MPPT strategy. Classical proportional–integral (PI) controllers are used in conjunction with a vector-controlled voltage source inverter, which adheres to the suggested DSSB regulator, to control the PMSM speed and d-q axis currents and to correct for current error. In addition to the vector-controlled voltage source inverter (which follows the recommended DSSB regulator), classical proportional–integral controllers are used to regulate the PMSM speed and d-q axis currents, and to correct current errors. In addition, a model Predictive Controller (PPC) is used with the pitch angle control (PAC) of WECS. This is done to show how well the proposed WECS (WECS with DSSB regulator) enhances voltage stability. A software-based simulation (MATLAB/Simulink) evaluates the results for ideal and unoptimized parameters of the WT and WECS under a variety of conditions. The results of the simulation show an increase in MPPT precision and output power performance.