FEM and Analytical Modeling of the Incipient Chip Formation for the Generation of Micro-Features.
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ABSTRACT:
SUBMITTER: Lanzetta M
PROVIDER: S-EPMC8306726 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Minimizing misalignments during the interconnection of microfluidic modules is extremely critical to develop a fully integrated microfluidic device. Misalignments arising during chip-to-chip or world-to-chip interconnections can be greatly detrimental to efficient functioning of microfluidic devices. To address this problem, we have performed numerical simulations to investigate the effect of misalignments arising in three types of interconnection methods: (i) end-to-end interconnection (ii) channel overlap when chips are stacked on top of each other, and (iii) tube-in-reservoir misalignment occurring due to the offset between the external tubing and the reservoir. For the case of end-to-end interconnection, the effect of misalignment was investigated for 0, 13, 50, 58, and 75% reduction in the available flow area at the location of geometrical misalignment. In the channel overlap interconnection method, various possible misalignment configurations were simulated by maintaining the same amount of misalignment (75% flow area reduction). The effect of misalignment in a tube-in-reservoir interconnection was investigated by positioning the tube at an offset of 164 ?m from the reservoir center. All the results were evaluated in terms of the equivalent length of a straight pipe. The effect of Reynolds number (Re) was also taken into account by performing additional simulations of aforementioned cases at Re ranging between 0.075 ? Re ? 75. Correlations were developed and the results were interpreted in terms of equivalent length (Le ). Equivalent length calculations revealed that the effect of misalignment in tube-in-reservoir interconnection method was the least significant when compared to the other two methods of interconnection.
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Project description:Three-dimensional (3D) helical mesostructures are attractive for applications in a broad range of microsystem technologies, due to their mechanical and electromagnetic properties as stretchable interconnects, radio frequency antennas and others. Controlled compressive buckling of 2D serpentine-shaped ribbons provides a strategy to formation of such structures in wide ranging classes of materials (from soft polymers to brittle inorganic semiconductors) and length scales (from nanometer to centimeter), with an ability for automated, parallel assembly over large areas. The underlying relations between the helical configurations and fabrication parameters require a relevant theory as the basis of design for practical applications. Here, we present an analytic model of compressive buckling in serpentine microstructures, based on the minimization of total strain energy that results from various forms of spatially dependent deformations. Experiments at micro- and millimeter-scales, together with finite element analyses (FEA), were exploited to examine the validity of developed model. The theoretical analyses shed light on general scaling laws in terms of three groups of fabrication parameters (related to loading, material and 2D geometry), including a negligible effect of material parameters and a square root dependence of primary displacements on the compressive strain. Furthermore, analytic solutions were obtained for the key physical quantities (e.g., displacement, curvature and maximum strain). A demonstrative example illustrates how to leverage the analytic solutions in choosing the various design parameters, such that brittle fracture or plastic yield can be avoided in the assembly process.
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Project description:BackgroundThe ChIP-chip technology has been used in a wide range of biomedical studies, such as identification of human transcription factor binding sites, investigation of DNA methylation, and investigation of histone modifications in animals and plants. Various methods have been proposed in the literature for analyzing the ChIP-chip data, such as the sliding window methods, the hidden Markov model-based methods, and Bayesian methods. Although, due to the integrated consideration of uncertainty of the models and model parameters, Bayesian methods can potentially work better than the other two classes of methods, the existing Bayesian methods do not perform satisfactorily. They usually require multiple replicates or some extra experimental information to parametrize the model, and long CPU time due to involving of MCMC simulations.ResultsIn this paper, we propose a Bayesian latent model for the ChIP-chip data. The new model mainly differs from the existing Bayesian models, such as the joint deconvolution model, the hierarchical gamma mixture model, and the Bayesian hierarchical model, in two respects. Firstly, it works on the difference between the averaged treatment and control samples. This enables the use of a simple model for the data, which avoids the probe-specific effect and the sample (control/treatment) effect. As a consequence, this enables an efficient MCMC simulation of the posterior distribution of the model, and also makes the model more robust to the outliers. Secondly, it models the neighboring dependence of probes by introducing a latent indicator vector. A truncated Poisson prior distribution is assumed for the latent indicator variable, with the rationale being justified at length.ConclusionThe Bayesian latent method is successfully applied to real and ten simulated datasets, with comparisons with some of the existing Bayesian methods, hidden Markov model methods, and sliding window methods. The numerical results indicate that the Bayesian latent method can outperform other methods, especially when the data contain outliers.
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Project description:In this article, ultrasonic guided wave propagation and interaction with the rivet hole cracks has been formulated using closed-form analytical solution while the local damage interaction, scattering, and mode conversion have been obtained from finite element analysis. The rivet hole cracks (damage) in the plate structure gives rise to the non-axisymmetric scattering of Lamb wave, as well as shear horizontal (SH) wave, although the incident Lamb wave source (primary source) is axisymmetric. The damage in the plate acts as a non-axisymmetric secondary source of Lamb wave and SH wave. The scattering of Lamb and SH waves are captured using wave damage interaction coefficient (WDIC). The scatter cubes of complex-valued WDIC are formed that can describe the 3D interaction (frequency, incident direction, and azimuth direction) of Lamb waves with the damage. The scatter cubes are fed into the exact analytical framework to produce the time domain signal. This analysis enables us to obtain the optimum design parameters for better detection of the cracks in a multiple-rivet-hole problem. The optimum parameters provide the guideline of the design of the sensor installation to obtain the most noticeable signals that represent the presence of cracks in the rivet hole.
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Project description:Organs-on-chips are broadly defined as microfabricated surfaces or devices designed to engineer cells into microscale tissues with native-like features and then extract physiologically relevant readouts at scale. Because they are generally compatible with patient-derived cells, these technologies can address many of the human relevance limitations of animal models. As a result, organs-on-chips have emerged as a promising new paradigm for patient-specific disease modeling and drug development. Because neuromuscular diseases span a broad range of rare conditions with diverse etiology and complex pathophysiology, they have been especially challenging to model in animals and thus are well suited for organ-on-chip approaches. In this Review, we first briefly summarize the challenges in neuromuscular disease modeling with animal models. Next, we describe a variety of existing organ-on-chip approaches for neuromuscular tissues, including a survey of cell sources for both muscle and nerve, and two- and three-dimensional neuromuscular tissue-engineering techniques. Although researchers have made tremendous advances in modeling neuromuscular diseases on a chip, the remaining challenges in cell sourcing, cell maturity, tissue assembly and readout capabilities limit their integration into the drug development pipeline today. However, as the field advances, models of healthy and diseased neuromuscular tissues on a chip, coupled with animal models, have vast potential as complementary tools for modeling multiple aspects of neuromuscular diseases and identifying new therapeutic strategies.
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Project description:Microscale supercapapcitors based on hierarchical nanoporous hybrid electrodes consisting of 3D bicontinuous nanoporous gold and pseudocapacitive manganese oxide deliver an excellent stack capacitance of 99.1 F cm-3 and a high energy density of 12.7 mW h cm-3 with a retained high power density of 46.6 W cm-3.
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Project description:A method is presented that modifies a 2mFobs - DFmodel ?A-weighted map such that the resulting map can strengthen a weak signal, if present, and can reduce model bias and noise. The method consists of first randomizing the starting map and filling in missing reflections using multiple methods. This is followed by restricting the map to regions with convincing density and the application of sharpening. The final map is then created by combining a series of histogram-equalized intermediate maps. In the test cases shown, the maps produced in this way are found to have increased interpretability and decreased model bias compared with the starting 2mFobs - DFmodel ?A-weighted map.
| S-EPMC4356370 | biostudies-literature
Project description:ChIP sequencing (ChIP-seq) is a new method for genomewide mapping of protein binding sites on DNA. It has generated much excitement in functional genomics. To score data and determine adequate sequencing depth, both the genomic background and the binding sites must be properly modeled. To develop a computational foundation to tackle these issues, we first performed a study to characterize the observed statistical nature of this new type of high-throughput data. By linking sequence tags into clusters, we show that there are two components to the distribution of tag counts observed in a number of recent experiments: an initial power-law distribution and a subsequent long right tail. Then we develop in silico ChIP-seq, a computational method to simulate the experimental outcome by placing tags onto the genome according to particular assumed distributions for the actual binding sites and for the background genomic sequence. In contrast to current assumptions, our results show that both the background and the binding sites need to have a markedly nonuniform distribution in order to correctly model the observed ChIP-seq data, with, for instance, the background tag counts modeled by a gamma distribution. On the basis of these results, we extend an existing scoring approach by using a more realistic genomic-background model. This enables us to identify transcription-factor binding sites in ChIP-seq data in a statistically rigorous fashion.
| S-EPMC2507756 | biostudies-literature
Project description:IntroductionMitral Valve (MV) 3D structural data can be easily obtained using standard transesophageal echocardiography (TEE) devices but quantitative pre- and intraoperative volume analysis of the MV is presently not feasible in the cardiac operation room (OR). Finite element method (FEM) modelling is necessary to carry out precise and individual volume analysis and in the future will form the basis for simulation of cardiac interventions.MethodWith the present retrospective pilot study we describe a method to transfer MV geometric data to 3D Slicer 2 software, an open-source medical visualization and analysis software package. A newly developed software program (ROIExtract) allowed selection of a region-of-interest (ROI) from the TEE data and data transformation for use in 3D Slicer. FEM models for quantitative volumetric studies were generated.ResultsROI selection permitted the visualization and calculations required to create a sequence of volume rendered models of the MV allowing time-based visualization of regional deformation. Quantitation of tissue volume, especially important in myxomatous degeneration can be carried out. Rendered volumes are shown in 3D as well as in time-resolved 4D animations.ConclusionThe visualization of the segmented MV may significantly enhance clinical interpretation. This method provides an infrastructure for the study of image guided assessment of clinical findings and surgical planning. For complete pre- and intraoperative 3D MV FEM analysis, three input elements are necessary: 1. time-gated, reality-based structural information, 2. continuous MV pressure and 3. instantaneous tissue elastance. The present process makes the first of these elements available. Volume defect analysis is essential to fully understand functional and geometrical dysfunction of but not limited to the valve. 3D Slicer was used for semi-automatic valve border detection and volume-rendering of clinical 3D echocardiographic data. FEM based models were also calculated.MethodA Philips/HP Sonos 5500 ultrasound device stores volume data as time-resolved 4D volume data sets. Data sets for three subjects were used. Since 3D Slicer does not process time-resolved data sets, we employed a standard movie maker to animate the individual time-based models and visualizations. Calculation time and model size were minimized. Pressures were also easily available. We speculate that calculation of instantaneous elastance may be possible using instantaneous pressure values and tissue deformation data derived from the animated FEM.
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Project description:Apparent occupancy levels of proteins bound to DNA in vivo can now be routinely measured on a genomic scale. A challenge in relating these occupancy levels to assembly mechanisms that are defined with biochemically isolated components lies in the veracity of assumptions made regarding the in vivo system. Assumptions regarding behavior of molecules in vivo can neither be proven true nor false, and thus is necessarily subjective. Nevertheless, within those confines, connecting in vivo protein-DNA interaction observations with defined biochemical mechanisms is an important step towards fully defining and understanding assembly/disassembly mechanisms in vivo. To this end, we have developed a computational program PathCom that models in vivo protein-DNA occupancy data as biochemical mechanisms under the assumption that occupancy levels can be related to binding duration and explicitly defined assembly/disassembly reactions. We exemplify the process with the assembly of the general transcription factors (TBP, TFIIB, TFIIE, TFIIF, TFIIH, and RNA polymerase II) at the genes of the budding yeast Saccharomyces. Within the assumption inherent in the system our modeling suggests that TBP occupancy at promoters is rather transient compared to other general factors, despite the importance of TBP in nucleating assembly of the preinitiation complex. PathCom is suitable for modeling any assembly/disassembly pathway, given that all the proteins (or species) come together to form a complex.
| S-EPMC2848545 | biostudies-literature