Present work investigates the DC and Analog/RF characteristics such as the drain current (ID), Transconductance (gm), Transconductance Generation Factor (TGF), Cut-off frequency (fT) Frequency Transconductance Product (FTP), Transit time (τ), and the total resistance of the source region, drain region, and channel resistance (RSD+CH) for Triple Metal (TM) Inversion Mode (IM) and Junctionless (JL) Cylindrical Gate All Around (CGAA) Germanium nanowire (GeNW) MOSFETs with 3 nm gate length using Silvaco ATLAS 3D TCAD. In this work, the Non-Equilibrium Green Function’s (NEGF) approach along with the self-consistent solution of Schrödinger’s equation and Poisson’s equation has been considered. The channel is taken to be lightly doped in the case of IM TM CGAA GeNW type of device. The effect of TM Gate work function engineering for GeNW channel of diameter 3 nm with gate oxide Al2O3 the thickness of 0.8 nm on ID, gm, TGF, fT, τ, FTP and RSD+CH has been studied. Moreover, a comparative study has been made between IMTM and JLTM CGAA GeNW devices with the above-mentioned parameters. For the JL device, the optimization of doping concentration is performed to get the same (i) ION current and (ii) threshold voltage (VTH) as the IM device. About 9.63 times and 8.89 times reduction in IOFF is seen for the same ION and same VTH devices respectively as compared to IM device. It has been found that TM Gate variation minimizes drain-induced barrier lowering (DIBL) in IM and JL devices. The JL GeNW showed much lower DIBL 39.38 mV/V, a near ideal SS 60 mV/dec, and higher ION/IOFF current ratio 4.71 × 1011 which is much better as compared to those reported in the literature for cylindrical gate all around (CGAA) devices. Also, it is found that the JL GeNW device performs better than IM in terms of SS, DIBL, ION/IOFF, gm, TGF, fT, τ, FTP and RSD+CH.

This work investigates triple-metal (TM) gate work-function engineering applied to both junctionless (JL) and inversion-mode (IM) double surrounding gate (DSG) germanium (Ge) nanotube (NT) MOSFETs for sub-3-nm technology nodes. A comprehensive analysis of DC and analog/RF performance metrics is performed, including drain current (ID), transconductance (gm), transconductance gain factor (TGF), cutoff frequency (fT), transconductance frequency product (FTP), intrinsic time constant (τ), and total series resistance (RSD+CH), for a gate length of 3 nm, using Silvaco ATLAS 3D TCAD. Carrier transport is modeled using the Non-Equilibrium Green’s Function (NEGF) formalism, self-consistently coupled with the Schrödinger and Poisson equations. The IM Ge NT device employs a lightly doped channel, Al2O3 gate dielectric with a thickness of 0.8 nm, and a Ge nanotube channel radius of 1.5 nm. A detailed comparison between IM and JL TM-DSG GeNT MOSFETs is presented. To ensure a fair comparison, the doping concentration of the JL GeNT is optimized under two conditions: (i) matching the ON-state current (ION) of the IM device and (ii) achieving an identical threshold voltage (VTH). The results demonstrate that the OFF-state current (IOFF) of the JL device is approximately 15.81 times and 11.67 times lower than that of the IM device under matched ION and VTH conditions, respectively. Consequently, the ION/IOFF ratio of the JL device improves by 15.78 times and 12.52 times, respectively. Furthermore, the JL GeNT MOSFET exhibits a low drain-induced barrier lowering (DIBL) of 30.88 mV/V, a near-ideal subthreshold slope of 60 mV/dec, and a high ION/IOFF ratio of approximately 3.82×10^11 . In addition, enhanced gm, TGF, fT, and FTP, along with reduced τ and RSD+CH, are achieved compared to reported cylindrical gate-all-around (CGAA) MOSFETs in existing literature.

This work presents a biosensor based on a junctionless cylindrical gate all around (CGAA) In0.53Ga0.47As nanowire MOSFET that uses the Dielectric Modulation (DM) technique and quadruple metal (QM) gate engineering to detect neutral biomolecules species such as uricase, streptavidin, protein, biotin, choline oxidase, and APTES, among others, electrically and without labels. A nanogap cavity region is created in the JL In0.53Ga0.47As NW MOSFET for biomolecule immobilization by etching the gate oxide layer above the Al2O3 interfacial layer. The sensing parameters for biomolecule detection in a dry environment have been the change in the drain current (ID), threshold voltage (VTH), off-current sensitivity (SIoff), threshold voltage sensitivity (SVth), ION/IOFF current ratio, and subthreshold slope (SS) of the device. The current study adds a novel, previously unrecognized biomolecule sensing metric—SS—to the existing literature. In contrast to the results found in previous research, the sensitivity metrics for JL In0.53Ga0.47As NW, such as a smaller DIBL (56.39 mV/V), a smaller SIoff (2.64 × 10-3), a higher SVth (10), a nearly perfect subthreshold slope (SS) (60 mV/dec), and a higher ION/IOFF current ratio (6.83 × 108), have been acquired in this work.

This work synthesized ZnO nanoparticles doped and co-doped with Ag and La using a cost-efficient sol-gel method. The structural and morphological features of the nanoparticles were characterized by X-ray diffraction (XRD) and field emission scanning electron microscopy (FESEM). The XRD and FE-SEM confirm the formation of the hexagonal structure of all the synthesized samples. Optical properties were analyzed using UV-Visible absorption and photoluminescence spectroscopy. These nanoparticles were subsequently employed as photoanodes in dye-sensitized solar cells (DSSCs). Several configurations of Ag and La doped and co-doped ZnO nanoparticles were tested as photoanodes to assess their impact on device performance. The introduction of Ag and La dopants into ZnO leads to a notable enhancement in the photovoltaic efficiency of the DSSCs. The DSSC incorporating bare ZnO photoanode achieved an efficiency of 0.2554% and on the other hand Ag and La co-doped ZnO photoanode achieved the highest efficiency of 0.9483%, a 271% increase compared to DSSC using undoped ZnO photoanodes. This significant improvement is attributed to the combined effects of Ag and La ions. Ag ions help create a blocking layer that suppresses electron recombination, while La ions enhance light absorption by broadening the spectrum through up/down conversion. The combined effect of Ag and La dopants is responsible for the observed efficiency enhancement in the DSSCs.

This study reports an approach for enhancing the photocatalytic efficiency of ZnO by co-doping with cerium (Ce), silver (Ag), and nitrogen (N), supported by multi-walled carbon nanotubes (MWCNTs). The Ce/Ag/N-doped ZnO-MWCNT nanocomposites were synthesized via a hydrothermal method, resulting in a significant reduction in the band gap from 3.19 eV to 2.89 eV. This change enabled higher visible light absorption, achieving enhanced photocatalytic degradation efficiencies of 92.12% for Congo red and 87.5% for methylene blue within 80 minutes. Comprehensive characterization using XRD, FTIR, BET, and PL analyses revealed enhanced surface area, increased oxygen vacancies, and improved charge separation dynamics due to the synergistic effects of multi-element doping and MWCNT integration. The strategic incorporation of Ce, Ag, and N not only reduced the electron-hole recombination rate but also facilitated the generation of reactive oxygen species (ROS) that are crucial for efficient dye degradation. These findings indicate the significant potential of the synthesized nanocomposites as advanced photocatalysts for environmental remediation under visible light irradiation.

In this work, Triple Metal (TM) and Quadruple Metal (QM) gate engineering have been done for both junctionless (JL) inversion mode (IM) and Double surrounding Gate (DSG) Si nanotube (SiNT) MOSFET to study drain current (ID) characteristics for gate length of 2 nm using Silvaco ATLAS 3D TCAD. For this, the Non Equilibrium Green’s Function (NEGF) method has been used along with self-consistent solution of Schrödinger’s equation with Poisson’s equation. In case of IM channel region of SiNT device, there is lightly doping. In this device SiO2 is used as gate oxide thickness of 0.8 nm, with Si channel radius of 1.5 nm have been used. A comparison has also been done between results of TM DSG and QM DSG SiNT. For a reasonable comparison between JL and IM SiNT, in each case of TM and QM JL SiNT doping concentration are optimized for two goals (i) to obtain the same ION as IM SiNT and (ii) to obtain the same threshold voltage (VTH) as IM SiNT. This results in about 10 times smaller IOFF for both JL, ION and VTH matching SiNT for both TM and QM case. This also results in about 10 times higher ION/IOFF current ratio for all JL device as compared to IM device for both TM and QM case. All used JL SiNT results in smaller DIBL in both TM and QM case as compared to IM SiNT device. In this work for JL SiNT, a smaller DIBL 36.46 mV/V, nearly ideal subthreshold slope (SS) 60 mV/dec, and higher ION/IOFF current ratio 4.41 × 1010 have been obtained in comparison to available literature CGAA device results.

This study investigates the DC and RF characteristics of Quadruple Metal (QM) Inversion Mode (IM) and Junctionless (JL) Cylindrical Gate-All-Around (CGAA) Silicon Nanowire (SiNW) MOSFETs with a 3 nm gate length, using Silvaco ATLAS 3D TCAD and the Non-Equilibrium Green Function (NEGF) method with self-consistent Schrödinger-Poisson solutions. Key parameters analyzed include drain current (ID), transconductance (gm), transconductance generation factor (TGF), cut-off frequency (fT), frequency transconductance product (FTP), transit time (τ), and total resistance (RSD+CH) for a SiNW with a 3 nm diameter and 0.8 nm gate oxide. The impact of QM gate work function engineering is compared between IMQM and JLQM devices. JL devices are optimized for equivalent ION and VTH as IM devices, achieving 246.96 times and 86.32 times lower IOFF, respectively. QM gate variation reduces DIBL in both devices, with JL SiNW showing superior performance: DIBL ( 75.42 mV/V), near-ideal subthreshold swing ( 60 mV/dec), and high ION/IOFF ( 1.92 × 1011), outperforming IM devices in SS, DIBL, ION/IOFF, gm, TGF, fT, τ, FTP, and RSD+CH.

This study investigates the photocatalytic properties of carbon nanotube (CNT)-supported nitrogen-, cobalt-, and silver-doped zinc oxide (ZnO) synthesized via the solvothermal method. Various characterization techniques, including X-ray photoelectron spectroscopy (XPS), BET surface area analysis, energy-dispersion X-ray (EDX) spectroscopy, UV–visible spectroscopy (UV–Vis), scanning electron microscopy (SEM), X-ray diffraction (XRD), photoluminescence (PL), Fourier transform infrared (FTIR), and transmission electron microscopy (TEM), were employed. Photoluminescence spectroscopy revealed lattice defects and the doping effect on ZnO’s electron–hole recombination. FTIR spectroscopy identified functional groups, and EDX and XPS confirmed the presence of Ag, Co, C, Zn, O, and N. XRD and TEM estimated crystal sizes between 21 and 24 nm. UV–Vis spectroscopy showed a reduced band gap from 3.18 to 2.40 eV. SEM images depicted hexagonal nanoparticle structures. BET analysis showed a Category 4 adsorption isotherm and a pore diameter of 8.527 nm. The nanocomposite ZnO exhibited significant photocatalytic degradation under visible light, achieving 96

In the present work, the authors have studied the Quasi-Static Capacitance–Voltage (QSCV) characteristics of 10 nm gate length double gate (DG) NMOSFETs of different channel materials namely, Si, Ge, and In_0.53Ga_0.47As , the results are reported using Silvaco ATLAS TCAD. The QSCV approach provides the advantage of immunity against frequency-dependent effects and has the ability to measure the small capacitance in the range of 100 fF. In this device, we consider the self-consistent solution of Schrodinger’s equation with Poisson’s equation. Further, the conduction band splitting in multiple sub-bands has been considered with light doping in the channel region. For this, the authors have studied C-V behaviour of the devices by observing the effect of metal gate work function engineering (using Ta, W, Mo, Ni, Au and Pt), channel engineering (using Si, In_0.53Ga_0.47As and Ge) and variation of channel thickness (2 nm, 5 nm, 10 nm and 1502 nm) with gate oxide (SiO_2) of thickness 1.2 nm. In further studies, SiO_2 was replaced its EOT with HfO_2 and results were again studied. The comparison of the behavior of C-V curve has been done for the above-mentioned channel materials. It was found that there is a significant reduction in inversion mode Capacitance with voltage for all the channel materials used for both SiO 2 based devices and with HfO 2 based devices. This has been attributed to quantization which results in a decrease in the overall gate to channel capacitance (C GC ) and hence increases the threshold voltage in MOS device. The quantization effect is lightly seen in Si for channel thickness of 2 nm, however for the same thickness, quantization is seen in Ge. Also for In 0.53 Ga 0.47 As quantization is seen for channel thickness of 2nm, 5nm, and 10 nm because of its low electron effective mass. The QSCV characteristics are also used to measure oxide thickness, flat-band voltage, threshold voltage, maximum depletion region thickness, distribution of charges in dielectric, interface traps charge and interface states between channel and gate oxide before fabrication of the device.

Moore’s law, along with the International Roadmap for Devices and Systems, continues to guide the scaling of devices below 10 nm. The challenges posed by such small-dimensioned devices form the basis of the present work. A junctionless MOSFET with a triple-metal gate structure is proposed as an alternative to conventional single-gate bulk MOSFETs for future CMOS technology. The present work investigated the direct current and analog/radio frequency characteristics including the drain current (I_D ), transconductance (g_m) , transconductance generation factor (TGF), cut-off frequency (f_T) , frequency–transconductance product (FTP), transit time (τ ), and the total resistance of the source region, drain region, and channel (R_SD+CH) for triple-metal (TM) inversion-mode (IM) and junctionless (JL) cylindrical gate-all-around (CGAA) silicon nanowire (SiNW) MOSFETs with 3-nm gate length using the Silvaco ATLAS 3D TCAD tool. The non-equilibrium Green’s function and the self-consistent solution of the Schrödinger and Poisson equations were considered. The channel was taken to be lightly doped in the case of the IM TM CGAA SiNW device. The effect of the TM gate work function engineering for a SiNW channel with a diameter of 3 nm and gate oxide (Al_2O_3) thickness of 0.8 nm was investigated with respect to I_D , g_m , TGF, f_T , τ , FTP, and R_SD+CH , and a comparative study between the IM TM and JL TM CGAA SiNW devices was carried out with respect to these parameters. For the JL device, optimization of the doping concentration was performed to obtain the same (i) ION current and (ii) threshold voltage (VTH) as the IM device. An 8.61- and 5.72-fold reduction in IOFF was seen for the same ION and VTH for the JL versus the IM device. It was found that the TM gate variation led to a reduction in drain-induced barrier lowering (DIBL) in the IM and JL devices. The JL SiNW showed much lower DIBL of 39.49 mV/V, a near-ideal subthreshold slope (SS) of 60 mV/dec, and higher I_ON/I_OFF current ratio of 2.98 × 1012. which is much better than the values reported in the literature for CGAA devices. Also, the JL SiNW device was found to perform better than the IM SiNW device in terms of SS, DIBL, I_ON/I_OFF , g_m, TGF, fT, τ , FTP, and R_SD+CH .

Present work investigates the DC and Analog/RF characteristics such as the drain current (I_D ), Transconductance (g_m) , Transconductance Generation Factor (TGF), Cut-off frequency (f_T) , Frequency Transconductance Product (FTP), Transit time (τ ), and the total resistance of the source region, drain region, and channel resistance (R_SD+CH) for Dual Metal (DM) Inversion Mode (IM) and Junctionless (JL) Cylindrical Gate All Around (CGAA) Silicon nanowire (SiNW) MOSFETs with 5 nm gate length using Silvaco ATLAS 3D TCAD. In this work, the Non-Equilibrium Green’s Function approach along with the self-consistent solution of Schrödinger’s equation and Poisson’s equation has been considered. The channel is taken to be lightly doped in the case of IM DM CGAA SiNW type of device. The effect of DM Gate work function engineering for SiNW channel of diameter 3 nm with gate oxide (SiO_2) the thickness of 0.8 nm on I_D , g_m , TGF, f_T , τ , FTP and R_CH has been studied. Moreover, a comparative study has been made between IMDM and JLDM CGAA SiNW devices with the above-mentioned parameters. For the JL device, the optimization of doping concentration is performed to get the same (i) ION current and (ii) threshold voltage (VTH) as the IM device. About 3.09 times and 21.89 times reduction in IOFF is seen for the same ION and VTH optimized devices respectively as compared to IM device. It has been found that DM Gate variation minimizes drain-induced barrier lowering (DIBL) in IM and JL devices. The JL SiNW showed much lower DIBL 16.46 mV/V, a near ideal SS 60 mV/dec, and higher I_ON/I_OFF current ratio 7.04 × 108 which is much better as compared to those reported in the literature for cylindrical gate all around (CGAA) devices. Also, it is found that the JL SiNW device performs better than IM in terms of SS, DIBL, I_ON/I_OFF , g_m, TGF, fT, τ , FTP and R_SD+CH .

In line with Moore's Law and the International Roadmap for Devices and Systems (IDRS), shrinking MOSFET dimensions to the 3 nm technology node requires the introduction and thorough investigation of new device structures and advanced materials. The current study focuses on the implementation of Triple Metal (TM) and Quadruple Metal (QM) gate work function engineering techniques on both junctionless (JL) and inversion mode (IM) Double surrounding Gate (DSG) In0.53Ga0.47As nanotube (NT) MOSFET. The objective is to analyze the drain current (ID) characteristics for a gate length of 3 nm using Silvaco ATLAS 3D TCAD. In order to make a fair comparison between JL and IM In0.53Ga0.47As NT, the doping concentration of TM and QM JL In0.53Ga0.47As NT is tuned to achieve two specific objectives. Firstly, the goal is to produce the same ION as IM In0.53Ga0.47As NT. Secondly, the aim is to achieve the same threshold voltage (VTH) as IM In0.53Ga0.47As NT. It was discovered that the IOFF for JL devices is approximately 2.93 times smaller compared to IM devices in the TM situation, while considering matching ION and VTH. The JL devices have an IOFF that is 12.9 times smaller and an IOFF that is 102 times smaller compared to the IM device for the QM situation. This is achieved by matching the ION and VTH values. It achieves a lesser drain-induced barrier lowering (DIBL) of approximately 28.10 mV/V, a virtually perfect subthreshold slope (SS) of roughly 60mV/dec, and a larger current ratio of ION/IOFF, which is approximately 1.42 x 107.

In the present research paper, Mn (transition metal) and Ce (rare earth metal) doped and co-doped ZnO nanoparticles were synthesized using a cost-effective sol-gel technique. As synthesized samples were characterized using x-ray diffraction and field emission scanning electron microscope to examine the structure and morphology respectively. The optical properties were examined by UV-Visible and photoluminescence spectroscopic techniques. The synthesized samples were used as photoanode for the fabrication of dye-sensitized solar cell (DSSC). The utilization of a photoanode, containing Mn and Ce doped and co-doped in ZnO, in DSSC leads to a significant enhancement in photovoltaic conversion efficiency with natural dye lawsonia inermis. Different combinations of Mn or Ce doped and co-doped ZnO nanoparticles were used for testing their effectiveness as photoanode in DSSC. It was observed that the efficiency for Mn and Ce co-doped ZnO photoanode-based DSSC was found to be 0.2118%, which is approximately a 750% increase as compared to bare ZnO photoanode based DSSC. The enhancement in the efficiency of DSSCs was due to the formation of a blocking layer by Mn ions which helps to stop the flow of electrons backward and the broadening of the spectrum region with the help of Ce ions using up/down conversion process also helps to achieve higher efficiency. This enhancement in the efficiency of DSSC may be attributed to the synergic effect of Mn and Ce.

In the present work Dielectric Modulation (DM) technique along with Triple Metal (TM) gate engineering has been used for the junctionless (JL) cylindrical gate all around (CGAA) Si nanowire (NW) MOSFET based biosensor for label free electrical detection of neutral biomolecules species like Uricase, Streptavidin, Protein, Biotin, ChOx (choline oxidase), and APTES etc. For this device, the Drift Diffusion approach has been used along with self -consistent solution of Schrodinger's equation with Poisson's equation. For the biomolecule immobilization, a nanogap cavity region is formed in the JL SiNW MOSFET by etching gate oxide layer above the SiO 2 interfacial layer. The change in the drain current ( I D ), threshold voltage ( V th ), off -current sensitivity ( S Ioff ), threshold voltage sensitivity ( S Vth ) and I on / I off current ratio of the device have been considered as the sensing parameters for detection of biomolecules under dry environment condition. In present work a new sensing metric of sensing of biomolecules - DIBL has been added which has never been reported in literature. In this work for JL SiNW, sensitivity metrics like smaller DIBL -50.47 mV/V, higher S Ioff 9 .33 x 10 5 , higher S Vth 28 .72, nearly ideal subthreshold slope (SS) -60 mV/dec, and higher I on / I off current ratio -9.01 x 10 12 have been obtained in comparison to available literature results.

This research work reveals the CdO–ZnO nanocomposites as photocatalysts for the degradation of MB (Methylene blue), RhB (Rhodamine B), and MO (Methyl orange) dyes. The composites have been prepared through a hydrothermal route with different cadmium oxide contents (0–30

The three-dimensional convolutional neural network (3D-CNN) and long short-term memory (LSTM) have consistently outperformed many approaches in video-based facial expression recognition (VFER). The image is unrolled to a one-dimensional vector by the vanilla version of the fully-connected LSTM (FC-LSTM), which leads to the loss of crucial spatial information. Convolutional LSTM (ConvLSTM) overcomes this limitation by performing LSTM operations in convolutions without unrolling, thus retaining useful spatial information. Motivated by this, in this paper, we propose a neural network architecture that consists of a blend of 3D-CNN and ConvLSTM for VFER. The proposed hybrid architecture captures spatiotemporal information from the video sequences of emotions and attains competitive accuracy on three FER datasets open to the public, namely the SAVEE, CK + , and AFEW. The experimental results demonstrate excellent performance without external emotional data with the added advantage of having a simple model with fewer parameters. Moreover, unlike the state-of-the-art deep learning models, our designed FER pipeline improves execution speed by many factors while achieving competitive recognition accuracy. Hence, the proposed FER pipeline is an appropriate candidate for recognizing facial expressions on resource-limited embedded platforms for real-time applications.

Currently, the available CR spectrum is not being used to their full potential. Certainly, the CR system is capable of meeting this challenge. Whenever a licensed user has to start another transmission on that channel, spectrum handoff allows an unlicensed user to leave its current channel. The SU then switches to a different channel to finish the incomplete transmission. This technique uses the handshaking protocol to transmit and receive an acknowledgment before data transmission to obtain the user's wait time.This paper describes the Convolution Neural Network automatically extracts the features without any human supervision. For classification, a two-layer hidden neural-network is utilized once features are extracted. The CNN performs convolution operation to extract the complex features of the data that is significant for doing regression. First, the preprocessed data is delivered to the CNN's input layer. The CNN conducts a convolution operation on the data to extract the complex features that are important for regression. . The developed model consists of a sequence layer, Long Short Term Memory (LSTM) layer, fully connected layer, and a regression layer. LSTM memory cells were used in the LSTM layer to provide extended memory support. LSTM units save the essential past state information to increase performance by accounting for dependencies, and they erase the unnecessary information to save memory an [1]d energy. The fully linked layer collects the processed output from all of the LSTM hidden units. The regression layer receives a single output as a result of this. The regression layer computes an output for which the loss value is computed and propagated backwards during the training phase. This is done for all of the training iterations until the loss is zero. The anticipated values of waiting time are next tested using a fully trained regression model. The observed waiting time as a function of the number of rounds played. The loss and RMSE (Root mean square error) keep decreasing for increasing number of iterations of training.

Present work investigates the DC and Analog/RF characteristics such as the drain current (I_D ), Transconductance (g_m) , Transconductance Generation Factor (TGF), Cut-off frequency (f_T) , Frequency Transconductance Product (FTP), Transit time (τ ), and the total resistance of the source region, drain region, and channel resistance (R_SD+CH) for Dual Metal (DM) Inversion Mode (IM) and Junctionless (JL) Cylindrical Gate All Around (CGAA) Silicon nanowire (SiNW) MOSFETs with 5 nm gate length using Silvaco ATLAS 3D TCAD. In this work, the Drift Diffusion (DD) approach along with the self-consistent solution of Schrödinger’s equation and Poisson’s equation has been considered. The channel is taken to be lightly doped in the case of IM DM CGAA SiNW type of device. The effect of DM Gate work function engineering for SiNW channel of diameter 3 nm with gate oxide (SiO_2) the thickness of 0.8 nm on I_D , g_m , TGF, f_T , τ , FTP and R_CH has been studied. Moreover, a comparative study has been made between IMDM and JLDM CGAA SiNW devices with the above-mentioned parameters. For the JL device, the optimization of doping concentration is performed to get the same (i) I ON current and (ii) threshold voltage (V TH ) as the IM device. About 2.96 times and 6.1 times reduction in I OFF is seen for the same I ON and V TH optimized devices respectively as compared to IM device. It has been found that DM Gate variation minimizes drain-induced barrier lowering (DIBL) in IM and JL devices. The JL SiNW showed much lower DIBL 20.82 mV/V, a near ideal SS 60 mV/dec, and higher I_ON/I_OFF current ratio 5.63 × 10 12 which is much better as compared to those reported in the literature for cylindrical gate all around (CGAA) devices. Also, it is found that the JL SiNW device performs better than IM in terms of SS, DIBL, I_ON/I_OFF, TGF, f T , τ , FTP and R_SD+CH .

Face expression recognition (FER) is a widely emerging research area in today’s era. The previous 2D-based techniques contain some drawbacks like illumination in data, variation in pose, and use ordinary feature extraction processes on scaled images. So, to overcome these kinds of hazards, 3D-based techniques have come to provide optimal solutions. The 3D-based techniques provide solutions for solving the face as well as video recognition problems with less pose variation problems and with optimal accuracy. This paper makes an attempt to provide a systematic review of various 3D techniques for FER with pros and cons, as well as different categories of emotions. The paper presents and analyses various existing FER-based models proposed by researchers and compares them with performance parameters. Furthermore, the paper provides a review of the different datasets used for FER.