相关论文: Microfluidics for Chemical Synthesis: Flow Chemist…

The effects of elasticity on the break-up of liquid threads in microfluidic cross-junctions is investigated using numerical simulations based on the "lattice Boltzmann models" (LBM). Working at small Capillary numbers, we investigate the…

We consider a situation commonly encountered in microfluidics: two streams of miscible liquids are brought at a junction to flow side by side within a microchannel, allowing solutes to diffuse from one stream to the other and possibly…

Machine learning is rapidly becoming a core technology for scientific computing, with numerous opportunities to advance the field of computational fluid dynamics. In this Perspective, we highlight some of the areas of highest potential…

We propose a simple model to analyze the traffic of droplets in microfluidic ``dual networks''. Such functional networks which consist of two types of channels, namely those accessible or forbidden to droplets, often display a complex…

Acoustically driven mixing of small fluid volumes is reported. Using surface acoustic waves on a mixer chip, conversion of those into bulk waves, and employing wave guiding effects enables us to distribute a set of "virtual sources" for…

Microfluidics has revolutionized control over small volumes through the use of physical barriers. However, the rigidity of these barriers limits flexibility in applications. We present an optofluidic toolbox that leverages structured light…

Synthesis is the automatic construction of a system from its specification. In classical synthesis algorithms, it is always assumed that the system is "constructed from scratch" rather than composed from reusable components. This, of…

Mixing at the microfluidic scale is challenging due to the low Reynolds numbers and often high P\'eclet numbers. Without turbulence, mixing relies solely on diffusion, resulting in slow and inefficient mixing. We demonstrate enhanced mixing…

Microdialysis is a well-established method for in vivo neurochemical measurements of small molecules, with implanted concentric-design probes offering minimized tissue damage and good temporal and spatial resolution. However, the large…

A Flow is a collection of component models ("Agents") which constructs the solution to a complex problem via iterative communication. Flows have emerged as state of the art architectures for code generation, and are the raison d'etre for…

Temperature is a fundamental regulator of chemical and biochemical kinetics, yet capturing nonlinear thermal effects directly from experimental data remains a major challenge due to limited throughput and model flexibility. Recent advances…

Microfluidic valves play a key role within microfluidic systems by regulating fluid flow through distinct microchannels, enabling many advanced applications in medical diagnostics, lab-on-chips, and laboratory automation. While microfluidic…

Chemical reaction engineering is key to industrial might and sustainable chemistry. This will be enabled using smart, efficient catalysts or catalysis ecosystems. This is possible with advanced artificial intelligence and machine learning…

The renewed interest from the scientific community in machine learning (ML) is opening many new areas of research. Here we focus on how novel trends in ML are providing opportunities to improve the field of computational fluid dynamics…

Henrik Bruus is professor of lab-chip systems and theoretical physics at the Technical University of Denmark. In this contribution, he summarizes some of the recent results within theory and simulation of microscale acoustofluidic systems…

Free-surface electrokinetic flows have been attracting increasing attention from the research community over recent times, as attributable to their diverse fields of applications ranging from fluid mixing, particle manipulation to…

Data preprocessing is a fundamental part of any machine learning application and frequently the most time-consuming aspect when developing a machine learning solution. Preprocessing for deep learning is characterized by pipelines that…

Predictive materials synthesis is the primary bottleneck in realizing new functional and quantum materials. Strategies for synthesis of promising materials are currently identified by time-consuming trial and error approaches and there are…

Generating droplets from a continuous stream of fluid requires precise tuning of a device to find optimized control parameter conditions. It is analytically intractable to compute the necessary control parameter values of a…

Due to their nature, using shear thickening fluids (STFs) in engineering applications has sparked an interest in developing energy-dissipating systems, such as damping devices or shock absorbers. The Rheinforce technology allows the design…