“…Alternatively, Monte-Carlo (MC) methods can be interpreted as a virtual manufacture and testing by running (a large number of) iterations, where a set of values { ′ } is obtained from a random number generator assuming Gaussian distributions of { ′ } of standard deviations {Δ } around their nominal values { } and inserted into equation ( 11) for obtaining a histogram for Ω′ in the simulated experiment. These band widths ΔΩ (20), which are associated with concurrently loaded valves, and thus change over the course of an LUO sequence, need to "fit" into the practically available envelope of spin rates between min and max ; these boundaries are, on the lower end at min , constrained by a minimum centrifugal field (1) or pressure (2) required to stabilize a liquid distribution Λ, e.g., to suppress unwanted capillary motion (9); the upper value at max is imposed by factors such as the limited torque of the spindle motor spindle (10), the pressure tightness of the (bonded) lid, and operational safety.…”
Larger-scale integration (LSI) resides at the heart of comprehensive sample-to-answer automation and parallelisation of assay panels for frequent and ubiquitous bioanalytical testing in decentralised the point-of-use / point-of-care settings. With an emphasis on rotational, centrifugo-pneumatic flow control, this paper employs a virtual “digital twin” strategy, considering experimental tolerances, to efficiently design such “Lab-on-a-Disc” systems featuring high packing density, reliability, configurability, modularity, manufacturability, performance while minimizing development and fabrication cost.
“…Alternatively, Monte-Carlo (MC) methods can be interpreted as a virtual manufacture and testing by running (a large number of) iterations, where a set of values { ′ } is obtained from a random number generator assuming Gaussian distributions of { ′ } of standard deviations {Δ } around their nominal values { } and inserted into equation ( 11) for obtaining a histogram for Ω′ in the simulated experiment. These band widths ΔΩ (20), which are associated with concurrently loaded valves, and thus change over the course of an LUO sequence, need to "fit" into the practically available envelope of spin rates between min and max ; these boundaries are, on the lower end at min , constrained by a minimum centrifugal field (1) or pressure (2) required to stabilize a liquid distribution Λ, e.g., to suppress unwanted capillary motion (9); the upper value at max is imposed by factors such as the limited torque of the spindle motor spindle (10), the pressure tightness of the (bonded) lid, and operational safety.…”
Larger-scale integration (LSI) resides at the heart of comprehensive sample-to-answer automation and parallelisation of assay panels for frequent and ubiquitous bioanalytical testing in decentralised the point-of-use / point-of-care settings. With an emphasis on rotational, centrifugo-pneumatic flow control, this paper employs a virtual “digital twin” strategy, considering experimental tolerances, to efficiently design such “Lab-on-a-Disc” systems featuring high packing density, reliability, configurability, modularity, manufacturability, performance while minimizing development and fabrication cost.
“…These LUOs are overwhelmingly processed in a batch-wise, rather than a continuous-flow fashion, by transiently sealing their fluidic exit with a normally-closed valve, thus intermittently stopping the flow while continuing rotation within certain boundaries, e.g., for vigorous agitation of the liquid sample. These centrifugal LUOs and their linked downstream detection techniques have been comprehensive reviewed elsewhere [24][25][26][49][50][51][52][53][54][55][56][57][58][59][60][61][62][63][64][65][66][67].…”
Current, application-driven trends towards larger-scale integration (LSI) of microfluidic systems for comprehensive assay automation and multiplexing pose significant technological and economical challenges to developers. By virtue of their intrinsic capability for powerful sample preparation, centrifugal systems have attracted significant interest in academia and business since the early 1990s. This review models common, rotationally controlled valving schemes at the heart of such “Lab-on-a-Disc” (LoaD) platforms to predict critical spin rates and reliability of flow control mainly based on geometries, location and liquid volumes to be processed, and their experimental tolerances. In absence of larger-scale manufacturing facilities during product development, the method presented here facilitates the provision of efficient simulation tools for virtual prototyping and characterization to greatly expedite design optimization according to key performance metrics. This virtual in silico approach thus significantly accelerates, de-risks and lowers costs along the critical advancement from idea, fluidic testing, bioanalytical validation and scale-up to commercial mass manufacture.
“…Yet, the portrayed approach can readily be extended to other flow control mechanisms. While essential ingredients for LoaD applications, we refer to various to the broad literature on centrifugally implemented LUOs and downstream detection techniques [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33].…”
Enhancing the degree of functional multiplexing while assuring operational reliability and manufacturability at competitive costs are crucial components to enable comprehensive sample-to-answer automation, e.g., for use in common, decentralized “Point-of-Care” or “Point-of-Use” scenarios. This paper demonstrates a model-based ‘digital twin’ approach which efficiently supports the algorithmic design optimization of exemplary centrifugo-pneumatic (CP) dissolvable-film (DF) siphon valves towards larger-scale integration (LSI) of well-established “Lab-on-a-Disc” (LoaD) systems. Obviously, the spatial footprint of the valves and their upstream laboratory unit operations (LUOs) have to fit, at a given radial position prescribed by its occurrence in the assay protocol, into the locally available disc space. At the same time, the retention rate of rotationally actuated valve and, most challenging, its band width related to unavoidable experimental tolerances need to slot into a defined interval of the practically allowed frequency envelope. A set of design rules, metrics, and methods and instructive showcases for computationally assisted optimization of valve structures are presented.
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