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Solar photovoltaics offers a promising avenue for sustainable power generation, with perovskite solar cells gaining significant interest due to their cost effectiveness and remarkable performance. Lead-based perovskites, while possessing superior electron mobility and carrier properties, raise concerns due to environmental and health risks. Substituting lead with tin holds promise. Tin halide perovskites, particularly with iodine as the halide, exhibit lower band gaps, suggesting heightened efficiency. However, managing the crystallization process, crucial for achieving films with desired morphological properties and crystal phase purity, poses a significant challenge for perovskite materials. Although solvent and additive engineering are extensively explored, their specific effects on the colloidal properties of perovskite suspensions received relatively little attention. This review aims to provide an overview of the world of colloids, shedding light on how the manipulation of colloidal properties in perovskite suspensions can exert a substantial influence on the crystallization kinetics of halide perovskite thin films.

The interest in microfluidic applications based on complex fluids is a result of the unique fluid dynamics of these systems, which enable the creation of effective devices for health care or biological and chemical analysis. In this area, processing suspensions of rigid particles in viscoelastic liquids offers a variety of possible applications where the rheology plays a key role.

In article number 20200034, Pietro Ferraro and co‐workers emphasize that early detection in cancer diseases is a key issue. The current state of the art of technology could allow a great opportunity for this purpose, to develop systems for detecting circulating cancer cells (CTC) in the blood. The challenge is to recognize and classify cancer cells and detect them non‐invasively through a lab‐on‐chip device as they flow. Single‐cell holographic phase contrast tomography offers the possibility in the real world to detect CTC in a label‐free mode by means of morphological analyzes when combined with artificial intelligence (AI). The cover summarizes and depicts the main concepts and the technological ingredients necessary to achieve such an ambitious goal, namely the recognition and sorting of cells, 3D‐imaging by microscope and complete morphological analysis of 3D‐phase‐contrast tomograms by AI tools.

Circulating tumor cells (CTCs) are rare tumor cells released from primary, metastatic, or recurrent tumors in the peripheral blood of cancer patients. CTCs isolation from peripheral blood and their molecular characterization represent a new marker in cancer screening, a diagnostic tool called “liquid biopsy” (LB). Compared to traditional tissue biopsy that is invasive and does not reveal tumor heterogeneity, LB is noninvasive and reflects in “real‐time” tumor dynamism and drug sensitivity. In the frame of LB, a new paradigm based on single‐cell and label‐free analysis based on morphological analysis is emerging. Here, we review the latest research developments in this emerging vision of LB. In particular, we survey and discuss recent improvements in microfluidics, imaging label‐free diagnosis and cell classification by artificial intelligence and how to combine them to realize an intelligent platform based on lab‐on‐chip technology. This prospect appears to open up promising and intriguing new scenarios for cancer management through single‐cell analysis that will revolutionize the future of early cancer diagnosis and therapeutic choice with disruptive impact on the society. The most promising approach to liquid biopsy has its roots in the smart integration between label‐free quantitative phase microscopy, accurate manipulation of microfluidic streams, and artificial intelligence. Lab‐on‐a‐chip devices with embedded imaging functions can now rely on robust deep learning architectures to generate accurate classification results from single‐cell analysis of blood flows. Flow engineering allows sorting and controlling the rotation of blood components, thus permitting added‐value high‐throughput tomographic inspection of circulating tumor cells.

In this work, we numerically investigate the dynamics of the growth and impingement of two gas bubbles in a Newtonian liquid in the presence of a rigid spherical particle. The computational analysis is carried out through 3D Arbitrary Lagrangian Eulerian (ALE) Finite Element Method (FEM) simulations. During their growth, as the bubbles start to ‘feel’ each other, they lose their spherical shape, with the side facing the other bubble becoming almost flat. In the liquid layer between the gas inclusions, an essentially biaxial extensional flow takes place. Depending on its initial position with respect to the bubbles, the solid particle can be ‘captured’ by the coalescing bubbles or ‘escape’ them. The effects of the physical and geometrical parameters of the system on such phenomenon are studied. [ABSTRACT FROM AUTHOR]