Oscillatory multiphase flow strategy for chemistry and biology

Continuous multiphase flow strategies are commonly employed for high-throughput parameter screening of physical, chemical, and biological processes as well as continuous preparation of a wide range of fine chemicals and micro/nano particles with processing times up to 10 min. The inter-dependency of mixing and residence times, and their direct correlation with reactor length have limited the adaptation of multiphase flow strategies for studies of processes with relatively long processing times (0.5–24 h). In this frontier article, we describe an oscillatory multiphase flow strategy to decouple mixing and residence times and enable investigation of longer timescale experiments than typically feasible with conventional continuous multiphase flow approaches. We review current oscillatory multiphase flow technologies, provide an overview of the advancements of this relatively new strategy in chemistry and biology, and close with a perspective on future opportunities.Natural Sciences and Engineering Research Council of Canada (Postgraduate Fellowship

Development of safety improvement method in city zones based on road network characteristics

Background and Objective: Extensive studies have so far been carried out on developing safety models. Despite the extensive efforts made in identifying independent variables and methods for developing models, little research has been carried out in providing amendatory solutions for enhancing the level of safety. Thus, the present study first developed separate accident frequency prediction models by transportation modes, and then in the second phase, a development of safety improvement method (DSIM) was proposed. Materials and Methods: To this end, the data related to 14,903 accidents in 96 traffic analysis zones in Tehran, Iran, were collected. To evaluate the effect of intra-zone correlation, a multilevel model and a negative binomial (NB) model were developed based on both micro- and macro-level independent variables. Next, the DSIM was provided, aiming at causing the least change in the area under study and with attention to the defined constraints and ideal gas molecular movement algorithm. Results: Based on a comparison of the goodness-of-fit measures for the multilevel model with those of the NB model, the multilevel models showed a better performance in explaining the factors affecting accidents. This is due to considering the multilevel structure of the data in such models. The final results were obtained after 200 iterations of the optimization algorithm. Thus, to decrease accidents by 30 and cause the least change in the area under study, the independent variable of vehicle kilometer traveled per road segment underwent a considerable change, while little change was observed for the other variables. Conclusions: The final results of the DSIM showed that the ultimate solutions derived from this method can be different from the final solutions derived from the analysis of the results from the safety models. Hence, it is necessary to develop new methods to propose solutions for increasing safety

Enhanced addressability and localization in digital microfluidic multiplexer systems

This research presents a novel digital microfluidic multiplexer structure based on a cross-referencing architecture. The new multiplexing technique uses bi-polar voltage activation and threshold effects to overcome addressability limitations and eliminate inter-microdroplet interference. Fan et al. in 2002 introduced cross-referencing for enhancing addressability. The technique uses two sets of rectangular electrodes: top rows and bottom columns. Such a system achieves m+n addressability with only m+n electrodes. This is a significant achievement as voltage addressing and microdroplet actuation are performed by the same linear electrode structures. There remains one major drawback to the conventional cross-referencing method. Desired motion of a microdroplet on an electrode grid can result in undesired motion of other microdroplets placed on the same electrode row. Other groups have proposed intriguing solutions to this problem with cascaded differential voltage activation and graph theory, respectively. However, these methods become increasingly complex for systems with multiple microdroplets, as the solutions for addressability must have a limited number of microdroplets. The proposed method introduces a new multiplexing format for cross-referencing of DMF systems through the simultaneous use of threshold-based voltage actuation (which sets a minimum voltage to initiate microdroplet motion) and bi-polar voltage activation on the overlying and underlying electrodes. The threshold voltage effect for requirement one has been characterized numerically and experimentally, and the results are presented here. With regard to requirement two, it is necessary to employ a voltage addressing scheme that can preferentially isolate overlapped regions of the 2-D grid. This goal can be achieved using a bi-polar electrode activation technique, as the bi-polar DMF multiplexers will have a ±2Vapp voltage difference in the overlapped location and only a maximum of ±1 Vapp voltage difference in all other locations. This relationship has been quantified using an electrostatic 3-D COMSOL model of the proposed DMF multiplexer. A fabrication recipe for the proposed DMF multiplexer system is reported in this research, and the multiplexing protocol has been studied experimentally to verify the numerical analyses. The proposed technique with this threshold-based bi-polar activation can improve mxn addressability with multiple microdroplets in a cross-referenced DMF grid.Applied Science, Faculty ofEngineering, School of (Okanagan)Graduat

Control and Automation of Fluid Flow, Mass Transfer and Chemical Reactions in Microscale Segmented Flow

Flowing trains of uniformly sized bubbles/droplets (i.e., segmented flows) and the associated mass transfer enhancement over their single-phase counterparts have been studied extensively during the past fifty years. Although the scaling behaviour of segmented flow formation is increasingly well understood, the predictive adjustment of the desired flow characteristics that influence the mixing and residence times, remains a challenge. Currently, a time consuming, slow and often inconsistent manual manipulation of experimental conditions is required to address this task. In my thesis, I have overcome the above-mentioned challenges and developed an experimental strategy that for the first time provided predictive control over segmented flows in a hands-off manner. A computer-controlled platform that consisted of a real-time image processing module within an integral controller, a silicon-based microreactor and automated fluid delivery technique was designed, implemented and validated. In a first part of my thesis I utilized this approach for the automated screening of physical mass transfer and solubility characteristics of carbon dioxide (CO2) in a physical solvent at a well-defined temperature and pressure and a throughput of 12 conditions per hour. Second, by applying the segmented flow approach to a recently discovered CO2 chemical absorbent, frustrated Lewis pairs (FLPs), I determined the thermodynamic characteristics of the CO2-FLP reaction. Finally, the segmented flow approach was employed for characterization and investigation of CO2-governed liquid-liquid phase separation process.The second part of my thesis utilized the segmented flow platform for the preparation and shape control of high quality colloidal nanomaterials (e.g., CdSe/CdS) via the automated control of residence times up to approximately 5 minutes. By introducing a novel oscillatory segmented flow concept, I was able to further extend the residence time limitation to 24 hours. A case study of a slow candidate reaction, the etching of gold nanorods during up to five hours, served to illustrate the utility of oscillatory segmented flows in assessing the shape evolution of colloidal nanomaterials on-chip via continuous optical interrogation at only one sensing location. The developed cruise control strategy will enable plug'n play operation of segmented flows in applications that include flow chemistry, material synthesis and in-flow analysis and screening.Ph.D

Performance metrics to unleash the power of self-driving labs in chemistry and materials science

Abstract With the rise of self-driving labs (SDLs) and automated experimentation across chemical and materials sciences, there is a considerable challenge in designing the best autonomous lab for a given problem based on published studies alone. Determining what digital and physical features are germane to a specific study is a critical aspect of SDL design that needs to be approached quantitatively. Even when controlling for features such as dimensionality, every experimental space has unique requirements and challenges that influence the design of the optimal physical platform and algorithm. Metrics such as optimization rate are therefore not necessarily indicative of the capabilities of an SDL across different studies. In this perspective, we highlight some of the critical metrics for quantifying performance in SDLs to better guide researchers in implementing the most suitable strategies. We then provide a brief review of the existing literature under the lens of quantified performance as well as heuristic recommendations for platform and experimental space pairings

Research Acceleration in Self‐Driving Labs: Technological Roadmap toward Accelerated Materials and Molecular Discovery

The urgency of finding solutions to global energy, sustainability, and healthcare challenges has motivated rethinking of the conventional chemistry and material science workflows. Self‐driving labs, emerged through integration of disruptive physical and digital technologies, including robotics, additive manufacturing, reaction miniaturization, and artificial intelligence, have the potential to accelerate the pace of materials and molecular discovery by 10–100X. Using autonomous robotic experimentation workflows, self‐driving labs enable access to a larger part of the chemical universe and reduce the time‐to‐solution through an iterative hypothesis formulation, intelligent experiment selection, and automated testing. By providing a data‐centric abstraction to the accelerated discovery cycle, in this perspective article, the required hardware and software technological infrastructure to unlock the true potential of self‐driving labs is discussed. In particular, process intensification as an accelerator mechanism for reaction modules of self‐driving labs and digitalization strategies to further accelerate the discovery cycle in chemical and materials sciences are discussed

Oscillatory three-phase flow reactor for studies of bi-phasic catalytic reactions

A multi-phase flow strategy, based on oscillatory motion of a bi-phasic slug within a fluorinated ethylene propylene (FEP) tubular reactor, under inert atmosphere, is designed and developed to address mixing and mass transfer limitations associated with continuous slug flow chemistry platforms for studies of bi-phasic catalytic reactions. The technique is exemplified with C–C and C–N Pd catalyzed coupling reactions.Novartis-MIT Center for Continuous Manufacturin

Continuous flow solar desorption of CO2 from aqueous amines

Recovery of captured carbon dioxide (CO2) is considered the most energy-intensive stage of postcombustion CO2 capture strategies by aqueous amines. In response, an optically transparent flow reactor with continuous in operando CO2 collection using light-absorbing, graphite-titania composite microparticles is developed for the energy-efficient solar desorption of CO2 from saturated aqueous amine absorbents. The synthesized graphite-titania composite microparticles are demonstrated to be a more effective packing material for continuous CO2 solar desorption in the packed-bed flow reactor compared to other candidates, including titania and carbon black. The effect of continuous and discrete parameters, including irradiance, residence time, amine concentration, and amine chemical structure on the efficiency of solar-enabled CO2 desorption using the developed continuous flow strategy with the graphite-titania composite microparticle packing is studied in detail. Furthermore, the potential for the implementation of a control strategy by adjusting the aqueous amine stream flow rate to achieve constant CO2 desorption efficiency with dynamic solar irradiance is discussed. Finally, the continuous CO2 desorption stability over an extended period of time (12 h) is examined with an average single-pass efficiency of 64%

Peclet Number Dependence of Mass Transfer in Microscale Segmented Gas–Liquid Flow

A detailed understanding of the scaling behavior associated with the fluid flow and the transport of gas molecules from a train of elongated gas plugs into neighboring liquid segments is of great importance for a broad range of microscale applications. The indirect dependence of the parameters affecting the <i>Capillary</i> and <i>Peclet</i> numbers and thereby scaling behavior (i.e., the velocity and length of the gas plugs, and the length of the liquid segments) on the directly adjustable experimental inputs (i.e., flow rate or pressure of each phase) has hindered the systematic investigation of scaling behavior in microscale gas–liquid flows. Here, we take advantage of an image-based feedback strategy that allows us to directly impose Capillary and Peclet numbers. We custom fabricated a long, straight microchannel (width 300 μm, length-to-width ratio 700) in a gas impermeable silicon–glass substrate. We automatically determined the length reduction of initially uniformly sized gas plugs at different positions along the microchannel and elucidated the gas concentration within adjacent liquid segments. In accordance with penetration theory, we analytically estimated the gas–liquid mass transfer time to scale with the Peclet number, <i>Pe</i>, to the power of −0.5. The experimentally measured scaling exponent −0.55 ± 0.5 for carbon dioxide dissolution in methanol and ethanol at <i>Pe</i> = 2060–16500 compared favorably with the analytical prediction and provides a guideline for predicting physical transport for a wide range microscale gas–liquid flow processes