Inferential models are widely used in the chemical industry to infer key process variables, which are challenging or expensive to measure, from other more easily measured variables. The aim of this paper is three-fold...Inferential models are widely used in the chemical industry to infer key process variables, which are challenging or expensive to measure, from other more easily measured variables. The aim of this paper is three-fold: to present a theoretical review of some of the well known linear inferential modeling techniques, to enhance the predictive ability of the regularized canonical correlation analysis (RCCA) method, and finally to compare the performances of these techniques and highlight some of the practical issues that can affect their predictive abilities. The inferential modeling techniques considered in this study include full rank modeling techniques, such as ordinary least square (OLS) regression and ridge regression (RR), and latent variable regression (LVR) techniques, such as principal component regression (PCR), partial least squares (PLS) regression, and regularized canonical correlation analysis (RCCA). The theoretical analysis shows that the loading vectors used in LVR modeling can be computed by solving eigenvalue problems. Also, for the RCCA method, we show that by optimizing the regularization parameter, an improvement in prediction accuracy can be achieved over other modeling techniques. To illustrate the performances of all inferential modeling techniques, a comparative analysis was performed through two simulated examples, one using synthetic data and the other using simulated distillation column data. All techniques are optimized and compared by computing the cross validation mean square error using unseen testing data. The results of this comparative analysis show that scaling the data helps improve the performances of all modeling techniques, and that the LVR techniques outperform the full rank ones. One reason for this advantage is that the LVR techniques improve the conditioning of the model by discarding the latent variables (or principal components) with small eigenvalues, which also reduce the effect of the noise on the model prediction. The results also show that PCR and PLS have comparable performances, and that RCCA can provide an advantage by optimizing its regularization parameter.展开更多
The size of InGaN micro-LEDs is continuously decreasing to meet the demands of various emerging applications,especially in tiny micro-displays such as ARVR.However,the conventional pixel definition based on plasma etc...The size of InGaN micro-LEDs is continuously decreasing to meet the demands of various emerging applications,especially in tiny micro-displays such as ARVR.However,the conventional pixel definition based on plasma etching significantly damages the mesa sidewalls,leading to a severe reduction in efficiency as the micro-LED size decreases.This seriously impedes the development and application of micro-LEDs.In this work,we comprehensively explain the origin of micro-LED sidewall effects and corresponding physical models.Subsequently,we systematically review recent progress in micro-LED fabrication aiming at suppressing sidewall effects.Furthermore,we discuss advancements in micro-LED fabrication with"damage-free"techniques,which hold the potential to fundamentally address the issue of plasma damage in the micro-LED process.We believe this review will deepen the understanding of micro-LED sidewall effects and provide a better insight into the latest associated fabrication technologies for high-efficientInGaNmicro-LEDs.展开更多
This study pioneers a high-performance UV polarization-sensitive photodetector by ingeniously integrating noncentrosymmetric metal nanostructures into a graphene(Gr)/Al_(2)O_(3)/GaN heterojunction.Unlike conventional ...This study pioneers a high-performance UV polarization-sensitive photodetector by ingeniously integrating noncentrosymmetric metal nanostructures into a graphene(Gr)/Al_(2)O_(3)/GaN heterojunction.Unlike conventional approaches constrained by graphene's intrinsic isotropy or complex nanoscale patterning,our design introduces asymmetric metal architectures(E-/T-type) to artificially create directional anisotropy.These structures generate plasmon-enhanced localized electric fields that selectively amplify photogenerated carrier momentum under polarized UV light(325 nm),synergized with Fowler-Nordheim tunneling(FNT) across an atomically thin Al_(2)O_(3) barrier.The result is a breakthrough in performance:a record anisotropy ratio of 115.5(E-type,-2 V) and exceptional responsivity(97.7 A/W),surpassing existing graphene-based detectors by over an order of magnitude.Crucially,by systematically modulating metal geometry and density,we demonstrate a universal platform adaptable to diverse 2D/3D systems.This study provides a valuable reference for developing and practically applying photodetectors with higher anisotropy than ultraviolet polarization sensitivity.展开更多
Advancements in neuromorphic computing have given an impetus to the development of systems with adaptive behavior,dynamic responses,and energy efficiency characteristics.Although charge-based or emerging memory techno...Advancements in neuromorphic computing have given an impetus to the development of systems with adaptive behavior,dynamic responses,and energy efficiency characteristics.Although charge-based or emerging memory technologies such as memristors have been developed to emulate synaptic plasticity,replicating the key functionality of neurons—integrating diverse presynaptic inputs to fire electrical impulses—has remained challenging.In this study,we developed reconfigurable metal-oxide-semiconductor capacitors(MOSCaps)based on hafnium diselenide(HfSe2).The proposed devices exhibit(1)optoelectronic synaptic features and perform separate stimulus-associated learning,indicating considerable adaptive neuron emulation,(2)dual light-enabled charge-trapping and memcapacitive behavior within the same MOSCap device,whose threshold voltage and capacitance vary based on the light intensity across the visible spectrum,(3)memcapacitor volatility tuning based on the biasing conditions,enabling the transition from volatile light sensing to non-volatile optical data retention.The reconfigurability and multifunctionality of MOSCap were used to integrate the device into a leaky integrate-and-fire neuron model within a spiking neural network to dynamically adjust firing patterns based on light stimuli and detect exoplanets through variations in light intensity.展开更多
Wide-bandgap semiconductors exhibit much larger energybandgaps than traditional semiconductors such as silicon,rendering them very promising to be applied in the fields of electronics and optoelectronics.Prominent exa...Wide-bandgap semiconductors exhibit much larger energybandgaps than traditional semiconductors such as silicon,rendering them very promising to be applied in the fields of electronics and optoelectronics.Prominent examples of semiconductors include SiC,GaN,ZnO,and diamond,which exhibitdistinctive characteristics such as elevated mobility and thermalconductivity.These characteristics facilitate the operation of awide range of devices,including energy-efficient bipolar junctiontransistors(BJTs)and metal-oxide-semiconductor field-effecttransistors(MOSFETs),as well as high-frequency high-electronmobility transistors(HEMTs)and optoelectronic components suchas light-emitting diodes(LEDs)and lasers.These semiconductorsare used in building integrated circuits(ICs)to facilitate theoperation of power electronics,computer devices,RF systems,andother optoelectronic advancements.These breakthroughs includevarious applications such as imaging,optical communication,andsensing.Among them,the field of power electronics has witnessedtremendous progress in recent years with the development of widebandgap(WBG)semiconductor devices,which is capable ofswitching large currents and voltages rapidly with low losses.However,it has been proven challenging to integrate these deviceswith silicon complementary metal oxide semiconductor(CMOS)logic circuits required for complex control functions.The monolithic integration of silicon CMOS with WBG devices increases thecomplexity of fabricating monolithically integrated smart integrated circuits(ICs).This review article proposes implementingCMOS logic directly on the WBG platform as a solution.However,achieving the CMOS functionalities with the adoption of WBGmaterials still remains a significant hurdle.This article summarizesthe research progress in the fabrication of integrated circuitsadopting various WBG materials ranging from SiC to diamond,with the goal of building future smart power ICs.展开更多
The traditional plasma etching process for defining micro-LED pixels could lead to significant sidewall damage.Defects near sidewall regions act as non-radiative recombination centers and paths for current leakage,sig...The traditional plasma etching process for defining micro-LED pixels could lead to significant sidewall damage.Defects near sidewall regions act as non-radiative recombination centers and paths for current leakage,significantly deteriorating device performance.In this study,we demonstrated a novel selective thermal oxidation(STO)method that allowed pixel definition without undergoing plasma damage and subsequent dielectric passivation.Thermal annealing in ambient air oxidized and reshaped the LED structure,such as p-layers and InGaN/GaN multiple quantum wells.Simultaneously,the pixel areas beneath the pre-deposited SiO_(2)layer were selectively and effectively protected.It was demonstrated that prolonged thermal annealing time enhanced the insulating properties of the oxide,significantly reducing LED leakage current.Furthermore,applying a thicker SiO_(2)protective layer minimized device resistance and boosted device efficiency effectively.Utilizing the STO method,InGaN green micro-LED arrays with 50-,30-,and 10-μm pixel sizes were manufactured and characterized.The results indicated that after 4 h of air annealing and with a 3.5-μm SiO_(2)protective layer,the 10-μm pixel array exhibited leakage currents density 1.2×10^(-6)A/cm^(2)at-10 V voltage and a peak on-wafer external quantum efficiency of~6.48%.This work suggests that the STO method could become an effective approach for future micro-LED manufacturing to mitigate adverse LED efficiency size effects due to the plasma etching and improve device efficiency.Micro-LEDs fabricated through the STO method can be applied to micro-displays,visible light communication,and optical interconnect-based memories.Almost planar pixel geometry will provide more possibilities for the monolithic integration of driving circuits with micro-LEDs.Moreover,the STO method is not limited to micro-LED fabrication and can be extended to design other III-nitride devices,such as photodetectors,laser diodes,high-electron-mobility transistors,and Schottky barrier diodes.展开更多
This paper addresses a set-theoretic method for the detection of data corruption cyber-attacks on the load frequency control loop of a networked power system. The system consists of several interconnected control area...This paper addresses a set-theoretic method for the detection of data corruption cyber-attacks on the load frequency control loop of a networked power system. The system consists of several interconnected control areas forming a power grid. Based on the overall discrete-time network dynamics, a convex and compact polyhedral robust invariant set is extracted and is used as a set-induced anomaly detector. If the state vector exits the invariant set,then an alarm will be activated, and the potential threat is considered disclosed. The attack scenario used to assess the efficiency of the proposed anomaly detector concerns corrupted frequency sensor measurements transmitted to the automatic generation control unit of a compromised control area. Simulation studies highlight the ability of a set-theoretic approach to disclose persistent and intermittent attack patterns even when they occur at the same time with changes in the power load demand.展开更多
Optoelectronic devices are advantageous in in-memory light sensing for visual information processing,recognition,and storage in an energy-efficient manner.Recently,in-memory light sensors have been proposed to improve...Optoelectronic devices are advantageous in in-memory light sensing for visual information processing,recognition,and storage in an energy-efficient manner.Recently,in-memory light sensors have been proposed to improve the energy,area,and time efficiencies of neuromorphic computing systems.This study is primarily focused on the development of a single sensing-storage-processing node based on a two-terminal solution-processable MoS2 metal-oxide-semiconductor(MOS)charge-trapping memory structure—the basic structure for charge-coupled devices(CCD)—and showing its suitability for in-memory light sensing and artificial visual perception.The memory window of the device increased from 2.8 V to more than 6V when the device was irradiated with optical lights of different wavelengths during the program operation.Furthermore,the charge retention capability of the device at a high temperature(100 ℃)was enhanced from 36 to 64%when exposed to a light wavelength of 400 nm.The larger shift in the threshold voltage with an increasing operating voltage confirmed that more charges were trapped at the Al_(2)O_(3)/MoS_(2) interface and in the MoS_(2) layer.A small convolutional neural network was proposed to measure the optical sensing and electrical programming abilities of the device.The array simulation received optical images transmitted using a blue light wavelength and performed inference computation to process and recognize the images with 91%accuracy.This study is a significant step toward the development of optoelectronic MOS memory devices for neuromorphic visual perception,adaptive parallel processing networks for in-memory light sensing,and smart CCD cameras with artificial visual perception capabilities.展开更多
文摘Inferential models are widely used in the chemical industry to infer key process variables, which are challenging or expensive to measure, from other more easily measured variables. The aim of this paper is three-fold: to present a theoretical review of some of the well known linear inferential modeling techniques, to enhance the predictive ability of the regularized canonical correlation analysis (RCCA) method, and finally to compare the performances of these techniques and highlight some of the practical issues that can affect their predictive abilities. The inferential modeling techniques considered in this study include full rank modeling techniques, such as ordinary least square (OLS) regression and ridge regression (RR), and latent variable regression (LVR) techniques, such as principal component regression (PCR), partial least squares (PLS) regression, and regularized canonical correlation analysis (RCCA). The theoretical analysis shows that the loading vectors used in LVR modeling can be computed by solving eigenvalue problems. Also, for the RCCA method, we show that by optimizing the regularization parameter, an improvement in prediction accuracy can be achieved over other modeling techniques. To illustrate the performances of all inferential modeling techniques, a comparative analysis was performed through two simulated examples, one using synthetic data and the other using simulated distillation column data. All techniques are optimized and compared by computing the cross validation mean square error using unseen testing data. The results of this comparative analysis show that scaling the data helps improve the performances of all modeling techniques, and that the LVR techniques outperform the full rank ones. One reason for this advantage is that the LVR techniques improve the conditioning of the model by discarding the latent variables (or principal components) with small eigenvalues, which also reduce the effect of the noise on the model prediction. The results also show that PCR and PLS have comparable performances, and that RCCA can provide an advantage by optimizing its regularization parameter.
基金The authors would like to acknowledge the support of KAUST Baseline Fund BAS/1/1664-01-01,Transition Award in Semiconductors,Award No.FCC/1/5939,OpportunityFundURF/1/5557-01-01.
文摘The size of InGaN micro-LEDs is continuously decreasing to meet the demands of various emerging applications,especially in tiny micro-displays such as ARVR.However,the conventional pixel definition based on plasma etching significantly damages the mesa sidewalls,leading to a severe reduction in efficiency as the micro-LED size decreases.This seriously impedes the development and application of micro-LEDs.In this work,we comprehensively explain the origin of micro-LED sidewall effects and corresponding physical models.Subsequently,we systematically review recent progress in micro-LED fabrication aiming at suppressing sidewall effects.Furthermore,we discuss advancements in micro-LED fabrication with"damage-free"techniques,which hold the potential to fundamentally address the issue of plasma damage in the micro-LED process.We believe this review will deepen the understanding of micro-LED sidewall effects and provide a better insight into the latest associated fabrication technologies for high-efficientInGaNmicro-LEDs.
基金National Natural Science Foundation of China(62375090, 62374062, 52002135)Natural Science Foundation of Guangdong Province of China(2023B1515120071)+2 种基金Science and Technology Program of Guangdong Province of China (2023A0505050131,2022A0505050066, 2024A1515011081)Characteristic Innovation Project of Universities in Guangdong Province(2023KTSCX028)Science and Technology Program of Guangzhou,China (2024A04J6456)
文摘This study pioneers a high-performance UV polarization-sensitive photodetector by ingeniously integrating noncentrosymmetric metal nanostructures into a graphene(Gr)/Al_(2)O_(3)/GaN heterojunction.Unlike conventional approaches constrained by graphene's intrinsic isotropy or complex nanoscale patterning,our design introduces asymmetric metal architectures(E-/T-type) to artificially create directional anisotropy.These structures generate plasmon-enhanced localized electric fields that selectively amplify photogenerated carrier momentum under polarized UV light(325 nm),synergized with Fowler-Nordheim tunneling(FNT) across an atomically thin Al_(2)O_(3) barrier.The result is a breakthrough in performance:a record anisotropy ratio of 115.5(E-type,-2 V) and exceptional responsivity(97.7 A/W),surpassing existing graphene-based detectors by over an order of magnitude.Crucially,by systematically modulating metal geometry and density,we demonstrate a universal platform adaptable to diverse 2D/3D systems.This study provides a valuable reference for developing and practically applying photodetectors with higher anisotropy than ultraviolet polarization sensitivity.
基金supported by the King Abdullah University of Science and Technology(KAUST)Baseline Fund.
文摘Advancements in neuromorphic computing have given an impetus to the development of systems with adaptive behavior,dynamic responses,and energy efficiency characteristics.Although charge-based or emerging memory technologies such as memristors have been developed to emulate synaptic plasticity,replicating the key functionality of neurons—integrating diverse presynaptic inputs to fire electrical impulses—has remained challenging.In this study,we developed reconfigurable metal-oxide-semiconductor capacitors(MOSCaps)based on hafnium diselenide(HfSe2).The proposed devices exhibit(1)optoelectronic synaptic features and perform separate stimulus-associated learning,indicating considerable adaptive neuron emulation,(2)dual light-enabled charge-trapping and memcapacitive behavior within the same MOSCap device,whose threshold voltage and capacitance vary based on the light intensity across the visible spectrum,(3)memcapacitor volatility tuning based on the biasing conditions,enabling the transition from volatile light sensing to non-volatile optical data retention.The reconfigurability and multifunctionality of MOSCap were used to integrate the device into a leaky integrate-and-fire neuron model within a spiking neural network to dynamically adjust firing patterns based on light stimuli and detect exoplanets through variations in light intensity.
基金supported by KAUST BaselineFund:BAS/1/1664-01-01,KAUST Near-term Grand Challenge Fund:REI/1/4999-01-01,KAUST Impact Acceleration Fund:REI/1/5124-01-01.
文摘Wide-bandgap semiconductors exhibit much larger energybandgaps than traditional semiconductors such as silicon,rendering them very promising to be applied in the fields of electronics and optoelectronics.Prominent examples of semiconductors include SiC,GaN,ZnO,and diamond,which exhibitdistinctive characteristics such as elevated mobility and thermalconductivity.These characteristics facilitate the operation of awide range of devices,including energy-efficient bipolar junctiontransistors(BJTs)and metal-oxide-semiconductor field-effecttransistors(MOSFETs),as well as high-frequency high-electronmobility transistors(HEMTs)and optoelectronic components suchas light-emitting diodes(LEDs)and lasers.These semiconductorsare used in building integrated circuits(ICs)to facilitate theoperation of power electronics,computer devices,RF systems,andother optoelectronic advancements.These breakthroughs includevarious applications such as imaging,optical communication,andsensing.Among them,the field of power electronics has witnessedtremendous progress in recent years with the development of widebandgap(WBG)semiconductor devices,which is capable ofswitching large currents and voltages rapidly with low losses.However,it has been proven challenging to integrate these deviceswith silicon complementary metal oxide semiconductor(CMOS)logic circuits required for complex control functions.The monolithic integration of silicon CMOS with WBG devices increases thecomplexity of fabricating monolithically integrated smart integrated circuits(ICs).This review article proposes implementingCMOS logic directly on the WBG platform as a solution.However,achieving the CMOS functionalities with the adoption of WBGmaterials still remains a significant hurdle.This article summarizesthe research progress in the fabrication of integrated circuitsadopting various WBG materials ranging from SiC to diamond,with the goal of building future smart power ICs.
基金support of KAUST Baseline Fund BAS/1/1664-01-01,KAUST Competitive Research Grants URF/1/3437-01-01,URF/1/3771-01-01KAUST Near-term Grand Challenge Fund REI/1/4999-01-01KAUST Impact Acceleration Fund REI/1/5124-01-01.
文摘The traditional plasma etching process for defining micro-LED pixels could lead to significant sidewall damage.Defects near sidewall regions act as non-radiative recombination centers and paths for current leakage,significantly deteriorating device performance.In this study,we demonstrated a novel selective thermal oxidation(STO)method that allowed pixel definition without undergoing plasma damage and subsequent dielectric passivation.Thermal annealing in ambient air oxidized and reshaped the LED structure,such as p-layers and InGaN/GaN multiple quantum wells.Simultaneously,the pixel areas beneath the pre-deposited SiO_(2)layer were selectively and effectively protected.It was demonstrated that prolonged thermal annealing time enhanced the insulating properties of the oxide,significantly reducing LED leakage current.Furthermore,applying a thicker SiO_(2)protective layer minimized device resistance and boosted device efficiency effectively.Utilizing the STO method,InGaN green micro-LED arrays with 50-,30-,and 10-μm pixel sizes were manufactured and characterized.The results indicated that after 4 h of air annealing and with a 3.5-μm SiO_(2)protective layer,the 10-μm pixel array exhibited leakage currents density 1.2×10^(-6)A/cm^(2)at-10 V voltage and a peak on-wafer external quantum efficiency of~6.48%.This work suggests that the STO method could become an effective approach for future micro-LED manufacturing to mitigate adverse LED efficiency size effects due to the plasma etching and improve device efficiency.Micro-LEDs fabricated through the STO method can be applied to micro-displays,visible light communication,and optical interconnect-based memories.Almost planar pixel geometry will provide more possibilities for the monolithic integration of driving circuits with micro-LEDs.Moreover,the STO method is not limited to micro-LED fabrication and can be extended to design other III-nitride devices,such as photodetectors,laser diodes,high-electron-mobility transistors,and Schottky barrier diodes.
文摘This paper addresses a set-theoretic method for the detection of data corruption cyber-attacks on the load frequency control loop of a networked power system. The system consists of several interconnected control areas forming a power grid. Based on the overall discrete-time network dynamics, a convex and compact polyhedral robust invariant set is extracted and is used as a set-induced anomaly detector. If the state vector exits the invariant set,then an alarm will be activated, and the potential threat is considered disclosed. The attack scenario used to assess the efficiency of the proposed anomaly detector concerns corrupted frequency sensor measurements transmitted to the automatic generation control unit of a compromised control area. Simulation studies highlight the ability of a set-theoretic approach to disclose persistent and intermittent attack patterns even when they occur at the same time with changes in the power load demand.
基金The authors acknowledge financial support from the Semiconductor Initiative,King Abdullah University of Science and Technology,Saudi Arabia(KAUST Research Funding(KRF)under Award No.ORA-2022-5314).
文摘Optoelectronic devices are advantageous in in-memory light sensing for visual information processing,recognition,and storage in an energy-efficient manner.Recently,in-memory light sensors have been proposed to improve the energy,area,and time efficiencies of neuromorphic computing systems.This study is primarily focused on the development of a single sensing-storage-processing node based on a two-terminal solution-processable MoS2 metal-oxide-semiconductor(MOS)charge-trapping memory structure—the basic structure for charge-coupled devices(CCD)—and showing its suitability for in-memory light sensing and artificial visual perception.The memory window of the device increased from 2.8 V to more than 6V when the device was irradiated with optical lights of different wavelengths during the program operation.Furthermore,the charge retention capability of the device at a high temperature(100 ℃)was enhanced from 36 to 64%when exposed to a light wavelength of 400 nm.The larger shift in the threshold voltage with an increasing operating voltage confirmed that more charges were trapped at the Al_(2)O_(3)/MoS_(2) interface and in the MoS_(2) layer.A small convolutional neural network was proposed to measure the optical sensing and electrical programming abilities of the device.The array simulation received optical images transmitted using a blue light wavelength and performed inference computation to process and recognize the images with 91%accuracy.This study is a significant step toward the development of optoelectronic MOS memory devices for neuromorphic visual perception,adaptive parallel processing networks for in-memory light sensing,and smart CCD cameras with artificial visual perception capabilities.
