Pub Date : 2023-11-02DOI: 10.1007/s10404-023-02695-8
JinChuan Li, KeLi Zhang, JingCun Fan, HengAn Wu, FengChao Wang
Understanding the slip behaviors on the graphene surfaces is crucial in the field of nanofluidics and nanofluids. The reported values of the slip length in the literature from both experimental measurements and simulations are quite scattered. The presence of low concentrations of functional groups may have a greater impact on the flow behavior than expected. Using non-equilibrium molecular dynamics simulations, we specifically investigated the influence of hydroxyl-functionalized graphene surfaces on the boundary slip, particularly the effects related to hydrogen bond dynamics. We observed that hydroxyl groups significantly hindered the sliding motion of neighboring water molecules. Hydrogen bonds can be found between hydroxyl groups and water molecules. During the flow process, these hydrogen bonds continuously form and break, resulting in the energy dissipation. We analyzed the energy balance under different driving forces and proposed a theoretical model to describe the slip length which also considers the influence of hydrogen bond dynamics. The effects of the driving force and the surface functional group concentration were also studied.
{"title":"Boundary slip moderated by interfacial hydrogen bond dynamics","authors":"JinChuan Li, KeLi Zhang, JingCun Fan, HengAn Wu, FengChao Wang","doi":"10.1007/s10404-023-02695-8","DOIUrl":"10.1007/s10404-023-02695-8","url":null,"abstract":"<div><p>Understanding the slip behaviors on the graphene surfaces is crucial in the field of nanofluidics and nanofluids. The reported values of the slip length in the literature from both experimental measurements and simulations are quite scattered. The presence of low concentrations of functional groups may have a greater impact on the flow behavior than expected. Using non-equilibrium molecular dynamics simulations, we specifically investigated the influence of hydroxyl-functionalized graphene surfaces on the boundary slip, particularly the effects related to hydrogen bond dynamics. We observed that hydroxyl groups significantly hindered the sliding motion of neighboring water molecules. Hydrogen bonds can be found between hydroxyl groups and water molecules. During the flow process, these hydrogen bonds continuously form and break, resulting in the energy dissipation. We analyzed the energy balance under different driving forces and proposed a theoretical model to describe the slip length which also considers the influence of hydrogen bond dynamics. The effects of the driving force and the surface functional group concentration were also studied.</p></div>","PeriodicalId":706,"journal":{"name":"Microfluidics and Nanofluidics","volume":"27 12","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134795434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chong Ahn, Taekhee Lee, Jae Hoon Shin, Jong Seong Lee, V Thiyagarajan Upaassana, Sthitodhi Ghosh, Bon Ki Ku
Early detection of pulmonary responses to silica aerosol exposure, such as lung inflammation as well as early identification of silicosis initiation, is of great importance in disease prevention of workers. In this study, to early screen the health condition of the workers who are exposed to respirable silica dusts, an immunoassay lab on a chip (LOC) was designed, developed and fully characterized for analyzing Clara cell protein 16 (CC16) in serum which has been considered as one of the potential biomarkers of lung inflammation or lung damage due to the respirable silica dusts. Sandwich immunoassay of CC16 was performed on the LOC developed with a custom-designed portable analyzer using artificial serums spiked with CC16 protein first and then human serums obtained from the coal mine workers exposed to the respirable silica-containing dusts. The dynamic range of CC16 assay performed on the LOC was in a range of 0.625-20 ng/mL, and the achieved limit of detection (LOD) was around 0.35 ng/mL. The assay results of CC16 achieved from both the developed LOC and the conventional 96 well plate showed a reasonable corelation. The correlation between the conventional reader and the developed portable analyzer was found to be reasonable, resulting in R2 ~ 0.93. This study shows that the LOC developed for the early detection of CC16 can be potentially applied for the development of a field-deployable point-of-care testing (POCT) for the early monitoring of the field workers who are exposed to silica aerosol.
早期检测接触二氧化硅气溶胶的肺部反应(如肺部炎症)以及早期识别矽肺病的诱发因素,对工人的疾病预防具有重要意义。为了早期筛查暴露于可吸入二氧化硅粉尘的工人的健康状况,本研究设计、开发了一种芯片上免疫测定实验室(LOC),并对其进行了全面鉴定,用于分析血清中的克拉细胞蛋白 16(CC16),该蛋白被认为是可吸入二氧化硅粉尘导致肺部炎症或肺损伤的潜在生物标志物之一。首先使用添加了 CC16 蛋白的人工血清,然后使用从暴露于含可吸入二氧化硅粉尘的煤矿工人处获得的人体血清,在定制设计的便携式分析仪开发的 LOC 上进行了 CC16 的三明治免疫测定。在 LOC 上进行的 CC16 检测的动态范围为 0.625-20 纳克/毫升,检出限(LOD)约为 0.35 纳克/毫升。开发的 LOC 和传统 96 孔板的 CC16 检测结果显示出合理的相关性。传统阅读器与开发的便携式分析仪之间的相关性也很合理,R2 ~ 0.93。这项研究表明,所开发的用于早期检测 CC16 的 LOC 有可能被用于开发一种可现场部署的护理点检测(POCT),以对暴露于二氧化硅气溶胶的现场工作人员进行早期监测。
{"title":"Lab on a chip for detecting Clara cell protein 16 (CC16) for potential screening of the workers exposed to respirable silica aerosol.","authors":"Chong Ahn, Taekhee Lee, Jae Hoon Shin, Jong Seong Lee, V Thiyagarajan Upaassana, Sthitodhi Ghosh, Bon Ki Ku","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Early detection of pulmonary responses to silica aerosol exposure, such as lung inflammation as well as early identification of silicosis initiation, is of great importance in disease prevention of workers. In this study, to early screen the health condition of the workers who are exposed to respirable silica dusts, an immunoassay lab on a chip (LOC) was designed, developed and fully characterized for analyzing Clara cell protein 16 (CC16) in serum which has been considered as one of the potential biomarkers of lung inflammation or lung damage due to the respirable silica dusts. Sandwich immunoassay of CC16 was performed on the LOC developed with a custom-designed portable analyzer using artificial serums spiked with CC16 protein first and then human serums obtained from the coal mine workers exposed to the respirable silica-containing dusts. The dynamic range of CC16 assay performed on the LOC was in a range of 0.625-20 ng/mL, and the achieved limit of detection (LOD) was around 0.35 ng/mL. The assay results of CC16 achieved from both the developed LOC and the conventional 96 well plate showed a reasonable corelation. The correlation between the conventional reader and the developed portable analyzer was found to be reasonable, resulting in <i>R</i><sup>2</sup> ~ 0.93. This study shows that the LOC developed for the early detection of CC16 can be potentially applied for the development of a field-deployable point-of-care testing (POCT) for the early monitoring of the field workers who are exposed to silica aerosol.</p>","PeriodicalId":706,"journal":{"name":"Microfluidics and Nanofluidics","volume":"27 11","pages":"1-10"},"PeriodicalIF":2.3,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10772934/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139401355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-27DOI: 10.1007/s10404-023-02689-6
F. Sofos, C. Dritselis, S. Misdanitis, T. Karakasidis, D. Valougeorgis
Kinetic theory and modeling have been proven extremely suitable in computing the flow rates in rarefied gas pipe flows, but they are computationally expensive and more importantly not practical in design and optimization of micro- and vacuum systems. In an effort to reduce the computational cost and improve accessibility when dealing with such systems, two efficient methods are employed by leveraging machine learning (ML). More specifically, random forest regression (RFR) and symbolic regression (SR) have been adopted, suggesting a framework capable of extracting numerical predictions and analytical equations, respectively, exclusively derived from data. The database of the reduced flow rates W used in the current ML framework has been obtained using kinetic modeling and it refers to nonlinear flows through circular tubes (tube length over radius (l in [0,5]) and downstream over upstream pressure (p in [0,0.9])) in a very wide range of the gas rarefaction parameter (delta in [0,10^3]). The accuracy of both RFR and SR models is assessed using statistical metrics, as well as the relative error between the ML predictions and the kinetic database. The predictions obtained by RFR show very good fit on the simulation data, having a maximum absolute relative error of less than (12.5%). Various expressions of the form of (W=W(p,l,delta )) with different accuracy and complexity are acquired from SR. The proposed equation, valid in the whole range of the relevant parameters, exhibits a maximum absolute relative error less than (17%). To further improve the accuracy, the dataset is divided into three subsets in terms of (delta) and one SR-based closed-form expression of each subset is proposed, achieving a maximum absolute relative error smaller than (9%). Very good performance of all proposed equations is observed, as indicated by the obtained accuracy measures. Overall, the present ML-predicted data may be very useful in gaseous microfluidics and vacuum technology for engineering purposes.
动力学理论和模型已被证明非常适用于计算稀薄气体管道流动的流量,但它们的计算成本很高,更重要的是在微系统和真空系统的设计和优化中不实用。在处理此类系统时,为了降低计算成本并提高可访问性,利用机器学习(ML)采用了两种有效的方法。更具体地说,采用了随机森林回归(RFR)和符号回归(SR),提出了一个能够分别从数据中提取数值预测和分析方程的框架。目前ML框架中使用的降低流量W数据库是通过动力学建模获得的,它指的是在很宽的气体稀薄参数(delta in [0,10^3])范围内通过圆管(管长除以半径(l in [0,5])和下游除以上游压力(p in [0,0.9]))的非线性流动。使用统计指标评估RFR和SR模型的准确性,以及ML预测与动力学数据库之间的相对误差。RFR预测结果与模拟数据拟合良好,最大绝对相对误差小于(12.5%)。由sr得到了不同精度和复杂度的(W=W(p,l,delta ))形式的表达式。所提出的方程在所有相关参数范围内都有效,其最大绝对相对误差小于(17%)。为了进一步提高准确率,将数据集按(delta)划分为三个子集,并对每个子集提出一个基于sr的封闭形式表达式,最大绝对相对误差小于(9%)。所有提出的方程都有很好的性能,正如所获得的精度测量所表明的那样。总的来说,目前的机器学习预测数据可能对气体微流体和真空技术的工程用途非常有用。
{"title":"Computation of flow rates in rarefied gas flow through circular tubes via machine learning techniques","authors":"F. Sofos, C. Dritselis, S. Misdanitis, T. Karakasidis, D. Valougeorgis","doi":"10.1007/s10404-023-02689-6","DOIUrl":"10.1007/s10404-023-02689-6","url":null,"abstract":"<div><p>Kinetic theory and modeling have been proven extremely suitable in computing the flow rates in rarefied gas pipe flows, but they are computationally expensive and more importantly not practical in design and optimization of micro- and vacuum systems. In an effort to reduce the computational cost and improve accessibility when dealing with such systems, two efficient methods are employed by leveraging machine learning (ML). More specifically, random forest regression (RFR) and symbolic regression (SR) have been adopted, suggesting a framework capable of extracting numerical predictions and analytical equations, respectively, exclusively derived from data. The database of the reduced flow rates <i>W</i> used in the current ML framework has been obtained using kinetic modeling and it refers to nonlinear flows through circular tubes (tube length over radius <span>(l in [0,5])</span> and downstream over upstream pressure <span>(p in [0,0.9])</span>) in a very wide range of the gas rarefaction parameter <span>(delta in [0,10^3])</span>. The accuracy of both RFR and SR models is assessed using statistical metrics, as well as the relative error between the ML predictions and the kinetic database. The predictions obtained by RFR show very good fit on the simulation data, having a maximum absolute relative error of less than <span>(12.5%)</span>. Various expressions of the form of <span>(W=W(p,l,delta ))</span> with different accuracy and complexity are acquired from SR. The proposed equation, valid in the whole range of the relevant parameters, exhibits a maximum absolute relative error less than <span>(17%)</span>. To further improve the accuracy, the dataset is divided into three subsets in terms of <span>(delta)</span> and one SR-based closed-form expression of each subset is proposed, achieving a maximum absolute relative error smaller than <span>(9%)</span>. Very good performance of all proposed equations is observed, as indicated by the obtained accuracy measures. Overall, the present ML-predicted data may be very useful in gaseous microfluidics and vacuum technology for engineering purposes.</p></div>","PeriodicalId":706,"journal":{"name":"Microfluidics and Nanofluidics","volume":"27 12","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10404-023-02689-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134797671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With continuous efforts of researchers all over the world, the field of inertial microfluidics is constantly growing, to cater to the requirements of diverse areas like healthcare, biological and chemical analysis, materials synthesis, etc. The scale, automation, or unique physics of these systems has been expanding their scope of applications. In this review article, we have provided insights into the fundamental mechanisms of inertial microfluidics, the forces involved, the interactions and effects of different applied forces on the suspended particles, the underlying physics of these systems, and the description of numerical studies, which are the prime factors that govern designing of effective and practical devices.. Further, we describe how various forces lead to the migration and focusing of suspended particles at equilibrium positions in channels with different cross-sections and also review various factors affecting the same. We also focus on the effect of suspended particles on the flow of fluids within these systems. Furthermore, we discuss how Dean flows are created in a curved channel and how different structures affect the creation of secondary flows, and their application to mixing, manipulating, and focusing particles as fluid. Finally, we describe various applications of microfluidics for diagnostic and other clinical purposes, and discuss the challenges and advancements in this field. We anticipate that this manuscript will elucidate the basics and quantitative aspects of inertial fluid dynamic effects for application in biomedicines, materials synthesis, chemical process control, and beyond.