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Controlling colloidal processing of (K,Na)NbO3-based materials in aqueous medium
摘要： K0.5Na0.5NbO3-based materials are serious candidates to replace lead-based piezoceramics since they show excellent electrical and piezoelectric properties. The tape casting technique can be used to obtain highly textured KNN-based ceramics; however, despite industrial and environmental advantages of water-based processing, there are not reports about the control of colloidal processing conditions to obtain optimized K0.5Na0.5NbO3-based slurries in aqueous medium. This paper reports a procedure for controlling colloidal processing conditions to obtain optimized (K0.5Na0.5)0.97Li0.03Nb0.8Ta0.2O3 suspensions. Zeta potential and cationic solubility measurements as a function of pH showed that pH 8.5 is adequate for controlling colloidal stability and rheological behavior of aqueous suspensions, while flow curves analysis allowed optimizing processing parameters, such as, powder content, amount of deflocculant and binder, and sonication time. Optimized colloidal suspensions were prepared and used to obtain high quality tapes. Processed ceramics from these stacked tapes show equivalent properties to those processed directly from powders, which demonstrates the effectiveness of the colloidal route reported here.
关键词： Aqueous tape casting,KNN,Lead-free,Rheological properties,Colloidal suspensions
更新于2025-11-14 17:28:48
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[IEEE 2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) - Bangkok, Thailand (2018.10.21-2018.10.24)] 2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) - Optimal PCA-EOC-KNN Model for Detection of NS1 from Salivary SERS Spectra
摘要： Non Structural Protein 1 (NS1) has recently been known as an alternative biomarker for diseases caused by flavivirus. It has been clinically acknowledged for early detection of dengue infection, since NS1 presence in blood can be as early as the first day of infection. Surface Enhanced Raman Spectroscopy (SERS) is an improvement to Raman spectroscopy, which amplifies the intensity of Raman scattering so to be usable. This also enables SERS to detect molecular structure up to a single molecule. As such, it is favorable amongst researchers investigating disease biomarker. Algorithm k-nearest neighbor (kNN) is a strategy to classify an unknown based on learning data, nearest to the class. Our work here intends to determine the optimal nearest neighbor number, distance rule and classifier rule for PCA-EOC-KNN model for automated detection of NS1 fingerprint from SERS spectra of adulterated saliva. Results show that PCA-EOC-KNN classifier performs with accuracy, precision, sensitivity and specificity above 90%, using Consensus classifier rule, Euclidean or Correlation or Cosine distance rule and k-value of 1, 3 and 5.
关键词： k-Nearest Neighbour (kNN),Nonstructural Protein 1 (NS1),Principal Component Analysis (PCA)
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE 13th Annual International Conference on Nano/Micro Engineered and Molecular Systems (NEMS) - Singapore, Singapore (2018.4.22-2018.4.26)] 2018 IEEE 13th Annual International Conference on Nano/Micro Engineered and Molecular Systems (NEMS) - Self-Powered, High-Sensitive Human Cutaneous Activities Sensor
摘要： A self-powered piezoelectric sensor based on lead-free (K,Na)NbO3 (KNN) thin film for human health monitoring is presented. The sensor is fabricated on a flexible substrate and exhibits high sensitivity and stability. It can detect various physiological signals such as pulse, respiration, and body movement. The results demonstrate its potential for wearable health monitoring applications.
关键词： piezoelectric sensor,KNN thin film,health monitoring,lead-free,flexible substrate,wearable
更新于2025-09-23 15:22:29
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ENHANCED STRUCTURAL AND ELECTRICAL PROPERTIES OF LEAD-FREE Y-DOPED (K, Na) NbO3 THIN FILMS
摘要： Yttrium- doped KNN thin films were grown on Si substrates using the sol-gel technique. The profound effects of Yttrium with different content element (mol % = 0, 0.1, 0.3, 0.5, 0.7 and 0.9) on the structural and electrical properties of KNN films were analyzed. The doped samples demonstrated a mainly uniform and homogenous microstructure with grain size less than 100 nm. The existence of Y Kα line shown in EDX spectrum confirmed the presence of Y-dopant in KNN based-compound. Small shift position of the Raman peaks indicated that Y incorporated on the interstitial A-site while broaden FWHM ascribed that Y preferably enters B-site lattice at high dopant concentration. The enhanced electrical resistivity at 0.5 mol % Y suggested that more conduction electrons were formed in KNN lattice structure.
关键词： doped,rare-earth,KNN,thin film,yttrium
更新于2025-09-23 15:22:29
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Identification of Gravesa?? ophthalmology by laser-induced breakdown spectroscopy combined with machine learning method
摘要： Diagnosis of the Graves’ ophthalmology remains a significant challenge. We identified between Graves’ ophthalmology tissues and healthy controls by using laser-induced breakdown spectroscopy (LIBS) combined with machine learning method. In this work, the paraffin-embedded samples of the Graves’ ophthalmology were prepared for LIBS spectra acquisition. The metallic elements (Na, K, Al, Ca), non-metallic element (O) and molecular bands ((C-N), (C-O)) were selected for diagnosing Graves’ ophthalmology. The selected spectral lines were inputted into the supervised classification methods including linear discriminant analysis (LDA), support vector machine (SVM), k-nearest neighbor (kNN), and generalized regression neural network (GRNN), respectively. The results showed that the predicted accuracy rates of LDA, SVM, kNN, GRNN were 76.33%, 96.28%, 96.56%, and 96.33%, respectively. The sensitivity of four models were 75.89%, 93.78%, 96.78%, and 96.67%, respectively. The specificity of four models were 76.78%, 98.78%, 96.33%, and 96.00%, respectively. This demonstrated that LIBS assisted with a nonlinear model can be used to identify Graves’ ophthalmopathy with a higher rate of accuracy. The kNN had the best performance by comparing the three nonlinear models. Therefore, LIBS combined with machine learning method can be an effective way to discriminate Graves’ ophthalmology.
关键词： support vector machine (SVM),linear discriminant analysis (LDA),Graves’ ophthalmology,laser-induced breakdown spectroscopy (LIBS),k-nearest neighbor (kNN),generalized regression neural network (GRNN)
更新于2025-09-23 15:21:01
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KNN-Based Representation of Superpixels for Hyperspectral Image Classification
摘要： Superpixel segmentation has been demonstrated to be a powerful tool in hyperspectral image (HSI) classification. Each superpixel region can be regarded as a homogeneous region, which is composed of a series of spatial neighboring pixels. However, a superpixel region may contain the pixels from different classes. To further explore the optimal representations of superpixels, a new framework based on two k selection rules is proposed to find the most representative training and test samples. The proposed method consists of the following four steps: first, a superpixel segmentation algorithm is performed on the HSI to cluster the pixels with similar spectral features into the same superpixel. Then, a domain transform recursive filtering is used to extract the spectral–spatial features of the HSI. Next, the k nearest neighbor (KNN) method is utilized to select k1 representative training samples and k2 test pixels for each superpixel, which can effectively overcome the within-class variations and between-class interference, respectively. Finally, the class label of superpixels can be determined by measuring the averaged distances among the selected training and test samples. Experiments conducted on four real hyperspectral datasets show that the proposed method provides competitive classification performances with respect to several recently proposed spectral–spatial classification methods.
关键词： superpixel segmentation,hyperspectral image classification,k nearest neighbor (KNN),Domain transform recursive filtering (RF)
更新于2025-09-23 15:21:01
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Ferroelectric properties and phase transitions of high performance vertically aligned KNN nanowire-arrays grown by pulsed laser deposition
摘要： Pulsed laser deposition (PLD) was used to synthesize piezoelectric nanowire-arrays of K0.5Na0.5NbO3 (KNN) on Pt/TiO2/SiO2/Si substrates. These arrays were successfully prepared by using two different deposition conditions than the previously reported for KNN. KNN with orthorhombic structure and minority secondary phases were identified by XRD. Ferroelectric and Piezoelectric properties were confirmed by piezoresponse force microscopy, and showed that nanowire-arrays have an improvement in their effective piezoelectric coefficient of d33eff = 94.6 pm/V and 133.6 pm/V, higher than previously reported coefficients. Pulsed laser photoacoustic technique was used to analyze the phase transition temperatures and they showed a phase transition (O-T) at ～170 ?C and a phase transition (T-C) at ～360 ?C, lower temperatures than those found for bulk ceramics. Furthermore, it was identified the presence of minor amount of secondary ferroelectric phase (K4Nb6O17).
关键词： Phase transitions,KNN nanowire-arrays,Ferroelectric properties,Pulsed laser deposition,Piezoelectric coefficient
更新于2025-09-23 15:19:57
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[IEEE 2019 18th International Conference on Optical Communications and Networks (ICOCN) - Huangshan, China (2019.8.5-2019.8.8)] 2019 18th International Conference on Optical Communications and Networks (ICOCN) - An Equalization Method based on W-KNN for PON with PAM4
摘要： We proposed a machine learning equalization technique based on weighted KNN for 50Gbps PAM4 PON systems. The simulation results show that 35dB loss budget is achieved by Weighted-KNN equalization technique.
关键词： KNN,PON,PAM4,Machine learning
更新于2025-09-16 10:30:52
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[IEEE 2019 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT) - Coimbatore, India (2019.2.20-2019.2.22)] 2019 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT) - Improved Fault Detection and Location Scheme for Photovoltaic Systems
摘要： Photovoltaic is encountering a quick innovation development since a decade ago. Yet, strange conditions, for example, shortcomings, low irradiance and so forth it influence the yield of PV framework. To enhance the execution of and productivity of PV framework, it is important to create enhanced blame location procedures. This paper for the most part centres around recognition conspire for LL and LG blames in the PV cluster. Such blames stay undetected under irradiance conditions, especially, when a most extreme power point following calculation is in administration. In the event that these shortcomings are undetected, there is extensively loss of yield of PV framework, in the event that these issues are not recognized for longer time, it might harm the board and conceivably cause fire dangers. The exhibited blame identification conspire utilizes Multi-Resolution Signal Decomposition (MSD) procedure and two machine learning calculations to be specific Fuzzy Logic and K-Nearest Neighbor (KNN) to group the blame and decide its area. Reenactment results confirm the exactness, unwavering quality and versatility of the exhibited plan.
关键词： K-Nearest Neighbour (KNN) algorithm,Fuzzy logic,MSD,Machine Learning algorithm,Fault detection
更新于2025-09-11 14:15:04
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Effect of cobalt substitution on the multiferroic characteristics of ferroelectric potassium sodium niobate (K0.5Na0.5NbO3) ceramics
摘要： The room-temperature multiferroic behavior of cobalt-substituted KNN [K0.5Na0.5Nb1?xCoxO3, 0.02 ≤ x ≤ 0.05] ceramics has been investigated. Both the X-ray diffraction and selected area electron diffraction analysis confirm that all the compositions found to be crystallized in the single phase (Orthorhombic, Amm2) without any formation of cobalt clusters and/or other secondary phases such as Co3O4. Co2+ oxidation state and the presence of oxygen vacancies in the samples have been studied through X-ray photoelectron spectroscopic measurements. The changes in the bandgap with the increase of Co concentration in KNN are noticed from UV–Visible absorption spectroscopy. Magnetic measurement on the samples reveals a dominant antiferromagnetic interaction attributed to the Co2+–Co2+ exchange interactions via F0-center and coupling between Co2+–Co2+ through O2?. The existence of exchange bias (EB) effect is also observed in KNaNb1?xCoxO3 (x = 0.03, 0.04, 0.05) samples from the magnetic measurements. In addition, it is found that defect complexes formed between Co′′′ Nb and oxygen vacancy lead to the enhanced dielectric, ferro, and piezoelectric properties of K0.5Na0.5Nb1?xCoxO3 ceramics.
关键词： Multiferroic,Cobalt-substituted KNN,Ferroelectric,Exchange bias,Antiferromagnetic
更新于2025-09-10 09:29:36