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Microfluidics have enabled notable advances in molecular biology 1 , 2 , synthetic chemistry 3 , 4 , diagnostics 5 , 6 and tissue engineering 7 . However, there has long been a critical need in the field to manipulate fluids and suspended matter with the precision, modularity and scalability of electronic circuits 8 – 10 . Just as the electronic transistor enabled unprecedented advances in the automatic control of electricity on an electronic chip, a microfluidic analogue to the transistor could enable improvements in the automatic control of reagents, droplets and single cells on a microfluidic chip. Previous works on creating a microfluidic analogue to the electronic transistor 11 – 13 did not replicate the transistor’s saturation behaviour, and could not achieve proportional amplification 14 , which is fundamental to modern circuit design 15 . Here we exploit the fluidic phenomenon of flow limitation 16 to develop a microfluidic element capable of proportional amplification with flow–pressure characteristics completely analogous to the current–voltage characteristics of the electronic transistor. We then use this microfluidic transistor to directly translate fundamental electronic circuits into the fluidic domain, including the amplifier, regulator, level shifter, logic gate and latch. We also combine these building blocks to create more complex fluidic controllers, such as timers and clocks. Finally, we demonstrate a particle dispenser circuit that senses single suspended particles, performs signal processing and accordingly controls the movement of each particle in a deterministic fashion without electronics. By leveraging the vast repertoire of electronic circuit design, microfluidic-transistor-based circuits enable fluidic automatic controllers to manipulate liquids and single suspended particles for lab-on-a-chip platforms. Flow limitation is exploited to develop a microfluidic device exhibiting flow–pressure behaviour analogous to the current–voltage characteristics of an electronic transistor.

During the various stages of shock loading, many transient modes of deformation can activate and deactivate to affect the final state of a material. In order to fundamentally understand and optimize a shock response, researchers seek the ability to probe these modes in real-time and measure the microstructural evolutions with nanoscale resolution. Neither post-mortem analysis on recovered samples nor continuum-based methods during shock testing meet both requirements. High-speed diffraction offers a solution, but the interpretation of diffractograms suffers numerous debates and uncertainties. By atomistically simulating the shock, X-ray diffraction, and electron diffraction of three representative BCC and FCC metallic systems, we systematically isolated the characteristic fingerprints of salient deformation modes, such as dislocation slip (stacking faults), deformation twinning, and phase transformation as observed in experimental diffractograms. This study demonstrates how to use simulated diffractograms to connect the contributions from concurrent deformation modes to the evolutions of both 1D line profiles and 2D patterns for diffractograms from single crystals. Harnessing these fingerprints alongside information on local pressures and plasticity contributions facilitate the interpretation of shock experiments with cutting-edge resolution in both space and time.

Structural metallic materials with interfaces of immiscible materials provide opportunities to design and tailor the microstructures for desired mechanical behavior. Metallic microstructures with plasticity contributors of the FCC and BCC phases show significant promise for damage-tolerant applications due to their enhanced strengths and thermal stability. A fundamental understanding of the dynamic failure behavior is needed to design and tailor these microstructures with desired mechanical responses under extreme environments. This study uses molecular dynamics (MD) simulations to characterize plasticity contributors for various interface microstructures and the damage evolution behavior of FCC/BCC laminate microstructures. This study uses six model Cu/Ta interface systems with different orientation relationships that are as- created, and pre-deformed to understand the modifications in the plasticity contributions and the void nucleation/evolution behavior. The results suggest that pre-existing misfit dislocations and loading orientations (perpendicular to and parallel to the interface) affect the activation of primary and secondary slip systems. The dynamic strengths are observed to correlate with the energy of the interfaces, with the strengths being highest for low-energy interfaces and lowest for high-energy interfaces. However, the presence of pre-deformation of these interface microstructures affects not only the dynamic strength of the microstructures but also the correlation with interface energy.

Screening liters of blood (i.e., apheresis) represents a generalized approach to promote the reliable access to circulating tumor cell clusters (CTCCs), which are known to be highly metastasis‐competent, yet ultrarare. However, no existing CTCC sorting technology has demonstrated high throughput, high yield, low shear stress, and minimal blood dilution simultaneously as required in apheresis. Here, a label‐free method is introduced termed Precision Apheresis for Non‐invasive Debulking of cell Aggregates (PANDA) to continuously isolate CTCCs from undiluted blood to clean buffer through size sorting, processing 1.4 billion cells per second. The cell focusing is optimized within whole blood leveraging secondary transverse flow and margination. The PANDA chip recovers >90% of spiked ≈24 rare HeLa cell clusters from 100 mL undiluted blood samples (equivalent to ≈500 billion blood cells) at 1 L h−1 throughput, with ≤20s device residence time, ≤15 Pa shear stress, and >99.9% return of blood components. The technology lays the groundwork for future routine isolation to increase the recovery of these ultrarare yet clinically significant tumor cell populations from large volumes of blood to advance cancer research, early detection, and treatment. A label‐free method is reported termed Precision Apheresis for Non‐invasive Debulking of cell Aggregates (PANDA) to continuously isolate circulating tumor cell clusters (CTCCs) from undiluted blood to clean buffer through size sorting at 1L h−1 throughput, processing 1.4 billion cells per second. The technology lays the groundwork to increase the recovery of CTCCs from large volumes of blood to advance cancer research, early detection, and treatment.

Lack of rigorous reproducibility and validation are significant hurdles for scientific development across many fields. Materials science, in particular, encompasses a variety of experimental and theoretical approaches that require careful benchmarking. Leaderboard efforts have been developed previously to mitigate these issues. However, a comprehensive comparison and benchmarking on an integrated platform with multiple data modalities with perfect and defect materials data is still lacking. This work introduces JARVIS-Leaderboard, an open-source and community-driven platform that facilitates benchmarking and enhances reproducibility. The platform allows users to set up benchmarks with custom tasks and enables contributions in the form of dataset, code, and meta-data submissions. We cover the following materials design categories: Artificial Intelligence (AI), Electronic Structure (ES), Force-fields (FF), Quantum Computation (QC), and Experiments (EXP). For AI, we cover several types of input data, including atomic structures, atomistic images, spectra, and text. For ES, we consider multiple ES approaches, software packages, pseudopotentials, materials, and properties, comparing results to experiment. For FF, we compare multiple approaches for material property predictions. For QC, we benchmark Hamiltonian simulations using various quantum algorithms and circuits. Finally, for experiments, we use the inter-laboratory approach to establish benchmarks. There are 1281 contributions to 274 benchmarks using 152 methods with more than 8 million data points, and the leaderboard is continuously expanding. The JARVIS-Leaderboard is available at the website: https://pages.nist.gov/jarvis_leaderboard/

Interactions between dislocations and grain boundaries play a major role in controlling the strength and ductility of structural materials. Experimentally, assessing and probing geometric and stress-based criteria at the local level for dislocation transmission through grain boundaries remains challenging. Therefore, there have been many efforts to systematically generate datasets of dislocation-grain boundary interactions (DGI) via computational models such as molecular dynamics simulations. So far, most DGI datasets have focused only on the subset of nominal minimum-energy grain boundary structures, which limits their applicability, especially to materials processed far from equilibrium. We present a comprehensive database of dislocation-grain boundary interactions for edge, screw, and 60° mixed dislocation with 330 and 257  symmetric tilt grain boundaries (total of 587) in FCC Cu consisting of 73 minimum-energy grain boundary structures and 514 metastable structures. The dataset contains the outcomes for 5234 unique interactions for various dislocation types, grain boundary structures, and applied shear stresses.

Background: The approach of teaching has been modified over the years with incorporation of E-learning tools consisting of adaptive tutorials, audiovisual clips, and virtual models. These educational media possess several distinct advantages over traditional didactic models of instruction, including the ability to update material in a timely manner to ensure delivery of the latest evidence-based content to trainees. The study was aimed to assess the effectiveness of the mentioned tools of E-learning in the field of medical science. Aims and Objectives: The aim of the study was to improve understanding and learning of metabolism of biochemistry for first MBBS students. Materials and Methods: Participants were taught the subject of metabolism of carbohydrates by the conventional methods following with a test and then were made to understand the topic by the means of audio-visual presentation and were tested again to achieve data for objective assessment of the E-learning methods of education. Results: The scores of the participants significantly increased after incorporation of E-learning tools in teaching methods. Conclusion: E-learning tools help increase the quality of education and compliance of students, even when dealing with difficult topics. Students become more interested with the subject and improves performance overall.

The global lifestyle of this modern world has become more dependent on petroleum-based products, whose applications are involved almost everywhere. Since a large quantity of oil is being used on a daily basis, the spilling of oil by various means during its storage and transportation has become inevitable. This work focuses on the spilling of oil in a marine environment, generally referred to as an offshore oil spill, in contrast to an onshore oil spill associated with a terrestrial environment. These oil spills not only devastate the natural resources and unsettle the economy, they also jeopardize marine life, as well as human health. The remediation of an oil spill remains very challenging, when the disaster is associated with a large aerial extent. In this context, a sound understanding is required on the origin, seeping, composition and properties of the spilled oil in order to better monitor the spreading of the oil spill. In this manuscript, a detailed list of fundamental queries, which will be required to be addressed at the instance of an oil spill has been deduced, which will be extremely useful for the oil spill respondents as there are no previous studies that exclusively provide the type and nature of data required to be collected, immediately following an oil spill. Furthermore, this manuscript has deduced a list of sensitive and essential plots that will be required in order to analyse and forecast the spreading of an oil spill. An essence of weathering and its associated movement of oil spill has been included.

The dynamic deformation response of metallic materials has contributions from dislocations, deformation twinning, and plastic deformation. The current state-of-art techniques can detail the complex mechanistic history of deformation modes under shock loading in real-time using in situ X-ray diffraction (XRD). However, the capability of these experiments to unravel plasticity contributions is challenging due to limitations in interpreting results and the lack of validation from atomistic simulations. Molecular dynamics (MD) simulations can successfully capture various deformation modes in metals and complement experiments using simulated diffractograms at various stages of evolution. However, the difference in length and time scales of MD simulations and experiments is a substantial obstacle in completing and interpreting in situ diffractograms. Therefore, the existing modeling methods require various approximations to model defect evolution and interaction at the mesoscales. However, while using approximations to correlate the peak broadening behavior to the density of dislocations or the shifts/splitting due to the presence of twins, the interpretations of the plasticity contributions from diffractograms are non-trivial, especially when multiple modes of deformation may be operating. This viewpoint discusses combining a mesoscale modeling method called quasi-coarse-grained dynamics and virtual XRD to characterize the plasticity contributions in BCC metals from slip, twinning, and phase transformation behavior. The combined approach shows promise in bridging the mesoscale gap between the capabilities of atomic-scale simulations and in situ experiments to characterize the dynamic deformation of materials.

Circulating tumor cell (CTC)-based liquid biopsies provide unique opportunities for cancer diagnostics, treatment selection, and response monitoring, but even with advanced microfluidic technologies for rare cell detection the very low number of CTCs in standard 10-mL peripheral blood samples limits their clinical utility. Clinical leukapheresis can concentrate mononuclear cells from almost the entire blood volume, but such large numbers and concentrations of cells are incompatible with current rare cell enrichment technologies. Here, we describe an ultrahigh-throughput microfluidic chip, LPCTC-iChip, that rapidly sorts through an entire leukapheresis product of over 6 billion nucleated cells, increasing CTC isolation capacity by two orders of magnitude (86% recovery with 105 enrichment). Using soft iron-filled channels to act as magnetic microlenses, we intensify the field gradient within sorting channels. Increasing magnetic fields applied to inertially focused streams of cells effectively deplete massive numbers of magnetically labeled leukocytes within microfluidic channels. The negative depletion of antibody-tagged leukocytes enables isolation of potentially viable CTCs without bias for expression of specific tumor epitopes, making this platform applicable to all solid tumors. Thus, the initial enrichment by routine leukapheresis of mononuclear cells from very large blood volumes, followed by rapid flow, high-gradient magnetic sorting of untagged CTCs, provides a technology for noninvasive isolation of cancer cells in sufficient numbers for multiple clinical and experimental applications.