Journal of Micro and Nano-Manufacturing最新文献_第7页

Electric Vehicle Battery End-Of-Use Recovery Management: Degradation Prediction and Decision Making 电动汽车电池报废回收管理:退化预测与决策

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Journal of Micro and Nano-Manufacturing Pub Date : 2022-06-27 DOI: 10.1115/msec2022-85536

Yixin Zhao, S. Behdad

{"title":"Electric Vehicle Battery End-Of-Use Recovery Management: Degradation Prediction and Decision Making","authors":"Yixin Zhao, S. Behdad","doi":"10.1115/msec2022-85536","DOIUrl":"https://doi.org/10.1115/msec2022-85536","url":null,"abstract":"\u0000 Electric vehicles (EVs) are spreading rapidly in the market due to their better responsiveness and environmental friendliness. An accurate diagnosis of EV battery status from operational data is necessary to ensure reliability, minimize maintenance costs, and improve sustainability. This paper presents a deep learning approach based on the long short-term memory network (LSTM) to estimate the state of health (SOH) and degradation of lithium-ion batteries for electric vehicles without prior knowledge of the complex degradation mechanisms. Our results are demonstrated on the open-source NASA Randomized Battery Usage Dataset with batteries aging under changing operating conditions. The randomized discharge data can better represent practical battery usage. The study provides additional end-of-use suggestions, including continued use, remanufacturing/repurposing, recycling, and disposal; for battery management dependent on the predicted battery status. The suggested replacement point is proposed to avoid a sharp degradation phase of the battery to prevent a significant loss of active material on the electrodes. This facilitates the remanufacturing/repurposing process for the replaced battery, thereby extending the battery’s life for secondary use at a lower cost. The prediction model provides a tool for customers and the battery second use industry to handle their EV battery properly to get the best economy and system reliability compromise.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82495523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Physics-Informed Artificial Intelligence for Temperature Prediction in Metal Additive Manufacturing: A Comparative Study 基于物理的人工智能在金属增材制造中的温度预测:比较研究

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Journal of Micro and Nano-Manufacturing Pub Date : 2022-06-27 DOI: 10.1115/msec2022-85159

Suyog Ghungrad, B. Gould, S. Wolff, Azadeh Haghighi

{"title":"Physics-Informed Artificial Intelligence for Temperature Prediction in Metal Additive Manufacturing: A Comparative Study","authors":"Suyog Ghungrad, B. Gould, S. Wolff, Azadeh Haghighi","doi":"10.1115/msec2022-85159","DOIUrl":"https://doi.org/10.1115/msec2022-85159","url":null,"abstract":"\u0000 Prediction of the temperature history of printed paths in additive manufacturing is crucial towards establishing the process-structure-property relationship. Traditional approaches for predictions such as physics-based simulations are computationally costly and time-consuming, whereas data driven approaches are highly dependent on huge, labeled datasets. Moreover, these labeled datasets are mostly scarce and costly in additive manufacturing owing to its unique application domain (mass customization) and complicated data-gathering stage. Recently, model-based or physics-informed artificial intelligence approaches have shown promising potential in overcoming the existing limitations and challenges faced by purely analytical or data driven approaches. In this work, a novel physics-informed artificial intelligent structure for scenarios with limited data is presented and its performance for temperature prediction in the selective laser melting additive manufacturing process is compared with one of the state-of-the-art data driven approaches, namely long short-term memory (LSTM) neural networks. Temperature data for training and testing was extracted from infrared images of single-track layer-based experiments for Ti64 material with different combinations of process parameters. Compared to LSTM, the proposed approach has higher computational efficiency and achieves better accuracy in limited data scenarios, making it a potential candidate for real-time closed-loop control of the additive manufacturing process under limited and sparse data scenarios. In other words, the proposed model is capable to learn more efficiently under such scenarios in comparison to LSTM model.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84719718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Real-Time Structured Light Scanning Characterization of Surface Topography of Direct Energy Deposited 316L Stainless Steel 直接能量沉积316L不锈钢表面形貌的实时结构光扫描表征

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Journal of Micro and Nano-Manufacturing Pub Date : 2022-06-27 DOI: 10.1115/msec2022-85783

Weijun Shen, Xing Zhang, Y. Liao, Beiwen Li

{"title":"Real-Time Structured Light Scanning Characterization of Surface Topography of Direct Energy Deposited 316L Stainless Steel","authors":"Weijun Shen, Xing Zhang, Y. Liao, Beiwen Li","doi":"10.1115/msec2022-85783","DOIUrl":"https://doi.org/10.1115/msec2022-85783","url":null,"abstract":"\u0000 Direct energy deposition (DED) has been widely used for additive manufacturing of metallic components toward a variety of applications. Surface characteristics of DED-fabricated components play key roles in determining the property and performance. Besides the average surface roughness which has been extensively investigated in literature, surface skewness and kurtosis are critical for surface integrity, particularly its durability due to stress concentration points. In this work, surface skewness and kurtosis of DED-fabricated 316L stainless steel as affected by processing parameters are investigated. In particular, the surface quality is measured using a microscopic structured light scanning (SLS) system, which is a relatively fast, low-cost, high-efficiency dimensional inspection metrology as compared to other methods. The results demonstrated the correlations between the printing parameters (laser power and scanning speed) and the surface topography of DED printed parts. It is found that the skewness and kurtosis of the surface are more sensitive to the change in scanning speed within a relatively low laser power range. Skewness is positively correlated with the scanning speed, while kurtosis shows a negative correlation with the scanning speed. Given a high scanning speed, Kurtosis and Skewness are more sensitive to the changes of scanning speed. Understanding the relationship between DED processing parameters and areal surface characteristics provides guidance and insights for process optimization and post-processing design towards additive manufacturing of high-performance metallic components.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86179941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effect of Porosity on Tool Wear During Micromachining of Additive Manufactured Titanium Alloy 增材钛合金微加工过程中孔隙率对刀具磨损的影响

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Journal of Micro and Nano-Manufacturing Pub Date : 2022-06-27 DOI: 10.1115/msec2022-80096

V. Varghese, Soham Mujumdar

{"title":"Effect of Porosity on Tool Wear During Micromachining of Additive Manufactured Titanium Alloy","authors":"V. Varghese, Soham Mujumdar","doi":"10.1115/msec2022-80096","DOIUrl":"https://doi.org/10.1115/msec2022-80096","url":null,"abstract":"\u0000 Porosity is a major quality issue in additively manufactured (AM) materials due to improper selection of raw material or process parameters. While porosity is kept to a minimum for structural applications, parts with intentional (engineered) porosity find applications in prosthetics, sound dampeners & mufflers, catalytic converters, electrodes, heat exchangers, filters, etc. During post-processing of additive manufactured components using secondary machining to obtain required dimensional tolerance and/or surface quality, part porosity could lead to fluctuating cutting forces and reduced tool life. The machinability of the porous AM material is poor compared to the homogenous wrought material due to the intermittent cutting and anisotropy of AM materials. The cutting parameters for machining are generally optimized for continuous wrought material and are not applicable for porous AM material. Micromilling experiments were carried out on AM Ti6Al4V alloy with different porosity levels and cutting speed using a 1 mm diameter end mill. The progression of tool wear and associated mechanisms during micro-milling of additive manufactured Ti6Al4V samples with different porosity levels are experimentally investigated. Insights into tool-workpiece interaction during micro-machining are obtained in cases where pore size could be comparable to the cutting tool diameter. This research could lead to efficient hybrid additive-subtractive manufacturing technologies with improved tool life and reduced costs.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86911894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Characterizing the Conductivity of Aerosol Jet Printed Silver Traces on Glass Using Intense Pulsed Light (IPL) 用强脉冲光(IPL)表征玻璃上气溶胶喷射印刷银迹的电导率

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Journal of Micro and Nano-Manufacturing Pub Date : 2022-06-27 DOI: 10.1115/msec2022-85649

Connor Ferris, Dilan Ratnayake, Alexander Curry, Danming Wei, Erin Gerber, T. Druffel, K. Walsh

{"title":"Characterizing the Conductivity of Aerosol Jet Printed Silver Traces on Glass Using Intense Pulsed Light (IPL)","authors":"Connor Ferris, Dilan Ratnayake, Alexander Curry, Danming Wei, Erin Gerber, T. Druffel, K. Walsh","doi":"10.1115/msec2022-85649","DOIUrl":"https://doi.org/10.1115/msec2022-85649","url":null,"abstract":"\u0000 Aerosol Jet Printing is a novel micron-scale printing technology capable of handling a variety of materials due to a large print material viscosity range and high substrate standoff distance of 3–5 mm. To finalize the properties of printed materials, a form of post-processing is often required. A current widely applicable post-processing technique exists in traditional oven curing. However, oven curing greatly restricts the viable substrates as well as curing time. Intense Pulsed Light (IPL) offers the chance to greatly expand this substrate variety and decrease curing time. However, limited models currently exist to relate the finished material properties to the unique settings of current IPL technology. In this paper, an experiment is developed through a General Full Factorial Design of Experiments (DOE) model to characterize conductivity of Ag ink using IPL as a post processing technique. This is conducted through Novacentrix Ag ink (JSA426) by 3 × 3 mm Van der Pauw sensor pads cured using IPL. Sample pads were generated in triplicate over a range of Energy Levels, Counts and Durations for IPL and the resulting conductivity measured. The collected conductivity data was then analyzed using ANOVA to determine the significant interactions. From this, a regression model is developed to predict the conductivity for any Energy-Count-Duration value. The methods employed are applicable to any post-processing technique, and further optimization of the model is proposed for future work.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91210235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Tiling of Cellular Structures Into 3D Parts According to the Density Values of SIMP Topology Optimization 根据SIMP拓扑优化的密度值将细胞结构平铺成三维零件

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Journal of Micro and Nano-Manufacturing Pub Date : 2022-06-27 DOI: 10.1115/msec2022-85307

Damla Ozkapici Helvaci, U. Yaman

{"title":"Tiling of Cellular Structures Into 3D Parts According to the Density Values of SIMP Topology Optimization","authors":"Damla Ozkapici Helvaci, U. Yaman","doi":"10.1115/msec2022-85307","DOIUrl":"https://doi.org/10.1115/msec2022-85307","url":null,"abstract":"\u0000 In this study, a novel approach is proposed to enhance the performance of the parts optimized by Solid Isotropic Material with Penalization (SIMP) method. SIMP is a topology optimization method that aims the optimum distribution of material in a design domain subjected to predefined loads, constraints and boundary conditions. The method forces every finite element composing the geometry to have a density of either 1 or 0. The main reason behind penalizing is that regions with intermediate densities are difficult to fabricate. However, including these regions in the optimization output may provide better performance results. Based on this idea, a method is proposed to utilize intermediate densities in a manufacturable form and is applied to 3D geometries. Besides, the remodeled topology is checked against any unconnected cells. In contrast to many methods, which delete the unconnected elements, the proposed method provides connectivity by adding cells.\u0000 The outputs of the proposed method are fabricated by using Electron Beam Melting (EBM) and Stereolithography (SLA) technologies. EBM uses material powder and a heat source to melt and fuse the powders while SLA uses photosensitive resin and an ultraviolet light to cure the resin. A common limitation of both technologies is that powder/resin may remain inside the internal features which do not have access to outer surface of the part through the channels. The proposed method ensures the easy removal of excess powder/resin after fabrication. Performance of the method is compared with the SIMP method through test and analysis.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81019838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

3D Co-Printability of PCL and Hybrid Hydrogels PCL和混合水凝胶的3D共打印性能

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Journal of Micro and Nano-Manufacturing Pub Date : 2022-06-27 DOI: 10.1115/msec2022-85685

Connor Quigley, Md. Ahasan Habib

{"title":"3D Co-Printability of PCL and Hybrid Hydrogels","authors":"Connor Quigley, Md. Ahasan Habib","doi":"10.1115/msec2022-85685","DOIUrl":"https://doi.org/10.1115/msec2022-85685","url":null,"abstract":"\u0000 3D bioprinting has recently gained popularity due to its inherent capability of releasing cell-seeded and cell-laden biomaterials in a defined location to fabricate patient-specific scaffolds. Multi-nozzle extrusion-based 3D bio-printing allows the fabrication of various natural and synthetic biopolymers and the investigations of material to material and cell to material interactions, and eventually with a high percentage of cell viability and proliferation. Although natural hydrogels are demanding candidates for bio-printing because of their biocompatibility and high-water content, ensuring the scaffold’s fidelity with only natural hydrogel polymers is still challenging. Polycaprolactone (PCL) is a potential synthetic bioprinting material that can provide improved mechanical properties for fabricated scaffolds, especially bone and cartilage scaffolds. In this paper, application-oriented structural viability such as 3D printability, shape fidelity, and mechanical properties of the scaffolds fabricated by PCL and other natural hydrogel materials will be investigated. Scaffolds will be fabricated using various natural hybrid hydrogels such as Alginate-Carboxymethyl Cellulose; Alginate-Carboxymethyl Cellulose-TEMPO NFC, and PCL simultaneously using various infill densities, applied pressures, print speeds, and toolpath patterns. Shape fidelities of printed scaffolds will be analyzed. This research can help identify optimum natural-synthetic polymer combinations based on the materials interaction, external and internal geometries, and mechanical properties for large-scale multi-material bio fabrication.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81203515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Pre-Crosslinked Hybrid Hydrogels for 3D Bio-Printing Process: Rheological Analysis 预交联混合水凝胶用于3D生物打印过程:流变分析

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Journal of Micro and Nano-Manufacturing Pub Date : 2022-06-27 DOI: 10.1115/msec2022-85700

Slesha Tuladhar, Cartwright Nelson, Md. Ahasan Habib

{"title":"Pre-Crosslinked Hybrid Hydrogels for 3D Bio-Printing Process: Rheological Analysis","authors":"Slesha Tuladhar, Cartwright Nelson, Md. Ahasan Habib","doi":"10.1115/msec2022-85700","DOIUrl":"https://doi.org/10.1115/msec2022-85700","url":null,"abstract":"\u0000 Bioprinting for regenerative medicine has been gaining a lot of popularity in today’s world. Despite being one of the rigorously studied fields, there are still several challenges yet to be solved. Geometric fidelity and mechanical complexities stand as roadblocks when it comes to the printability of the customized scaffolds. Exploring the rheological properties of the compositions helps us understand the physical and mechanical properties of the biomaterials which are closely tied to the printability of the filament and eventually, geometric fidelity of the scaffolds. To ensure the structural integrity of the scaffolds, viscosity enhancers such as Carboxymethyl Cellulose (CMC) and crosslinkers like CaCl2 and CaSO4 were used. These crosslinkers can be used before (pre-crosslinking) and after (post-crosslinking) the extrusion of considered compositions to investigate and compare the outcome. To do this, mixtures of Carboxymethyl Cellulose (CMC, viscosity enhancer), Alginate, and CaCl2 and CaSO4 (crosslinkers) were prepared at various concentrations maintaining minimum solid content (≤ 8%). Each composition was subjected to a set of rheological tests like Flow curve for shear thinning behavior, three-point thixotropic for recovery rate, amplitude test for gelation point, and frequency tests. This research thoroughly investigates compositions when they are introduced to crosslinkers and viscosity enhancers which can be crucial for 3D printing world.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75891946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving Geometric Accuracy in Wire and Arc Additive Manufacturing With Engineering-Informed Machine Learning 利用工程信息机器学习提高线材和电弧增材制造的几何精度

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Journal of Micro and Nano-Manufacturing Pub Date : 2022-06-27 DOI: 10.1115/msec2022-85325

C. Ruiz, D. Jafari, Vignesh Venkata Subramanian, T. Vaneker, Wei Ya, Qiang Huang

{"title":"Improving Geometric Accuracy in Wire and Arc Additive Manufacturing With Engineering-Informed Machine Learning","authors":"C. Ruiz, D. Jafari, Vignesh Venkata Subramanian, T. Vaneker, Wei Ya, Qiang Huang","doi":"10.1115/msec2022-85325","DOIUrl":"https://doi.org/10.1115/msec2022-85325","url":null,"abstract":"\u0000 Wire and arc additive manufacturing (WAAM) is a promising technology for fast and cost-effective fabrication of large-scale components made of high-value materials for industries such as petroleum and aerospace. By using robotic arc welding and wire filler materials, WAAM can fabricate complex large near-net shape parts with high deposition rates, short lead times and millimeter resolution. However, due to high temperature gradients and residual stresses, current WAAM technologies suffer from high surface roughness and poor shape accuracy. This limits the adoption of these technologies in industry and complicates process control and optimization. Since its conception, considerable research efforts have been made on improving the mechanical and microstructural performance of WAAM components while few studies have investigated their geometric accuracy. In this work, we propose an engineering-informed machine learning (ML) framework for predicting and compensating for the geometric deformation of WAAM fabricated products based on a few sample parts. The proposed ML algorithm efficiently separates geometric shape deviation into deformation and surface roughness. Then, the predicted shape deformation of a new product is minimized by applying optimal geometric compensation to the product design. Experimental validation on cylindrical shapes showed that the proposed methodology can effectively reduce product shape deviation, which facilitates the widespread adoption of WAAM.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76570142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hydrogel and Graphene Embedded Piezoresistive Microcantilever Sensor for Solvent and Gas Flow Detection 水凝胶和石墨烯嵌入压阻微悬臂式传感器用于溶剂和气体流量检测

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Journal of Micro and Nano-Manufacturing Pub Date : 2022-06-27 DOI: 10.1115/msec2022-85544

Dipannita Ghosh, Md Ashiqur Rahman, Ali Ashraf, Nazmul Islam

{"title":"Hydrogel and Graphene Embedded Piezoresistive Microcantilever Sensor for Solvent and Gas Flow Detection","authors":"Dipannita Ghosh, Md Ashiqur Rahman, Ali Ashraf, Nazmul Islam","doi":"10.1115/msec2022-85544","DOIUrl":"https://doi.org/10.1115/msec2022-85544","url":null,"abstract":"\u0000 Piezoresistive microcantilever sensor is widely used in sensing applications including liquid and gas flow detection. Microcantilevers can function as an embedded system if they are coated with polymers or nanomaterials to improve sensing performance. In this paper, we investigated the performance of piezoresistive microcantilevers (PMC) with and without additional coating. We studied the sensitivity of the PMC sensor after coating it with a three-dimensional porous hydrogel and piezoresistive graphene oxide layer. Hydrogel embedded piezoresistive microcantilever (EPM) showed better results than PMC during solvent sensing application. The resistance change for hydrogel embedded PMC was higher compared to bare PMC by 430% (3.2% to 17%) while detecting isopropyl alcohol (IPA), by approximately 1.5 orders of magnitude (0.19% to 5.7%) while detecting the presence of deionized water. Graphene Oxide coated PMC showed a wider detection range by 30 milliliter/min and 24% better sensitivity than bare PMC during the gas detection experiment. Additionally, we compared the experiment result with COMSOL simulation to develop a model for our embedded PMC sensing. Simulation shows significantly higher deflection of the EPM compared to the bare PMC (66.67% higher while detecting IPA, consistent with the trend observed during the experiment). The facile drop casting-based embedded microcantilever fabrication technique can lead to improved performance in different sensing applications. Our future work will focus on detecting biomolecules by using our constructed embedded systems.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76604749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0