M. Taher A. Saif

What ultimately limits heat removal during boiling, and can the boiling crisis be surpassed? The critical heat flux is traditionally viewed as a terminal threshold beyond which vapor blanketing suppresses heat transfer. However, in strongly subcooled water, a regime known as microbubble emission boiling (MEB) has been observed to sustain heat fluxes exceeding classical limits. Yet its physical origin has remained a subject of intense debate since the 1980s. Here, we show that the hydrodynamic instability underlying the boiling crisis represents a bifurcation point rather than an absolute thermal limit. Under sufficient subcooling, rapid condensation intercepts vapor coalescence, redirecting the postinstability evolution toward high-frequency, collapse-driven convection that continuously renews the surface, a state we identify as condensation-driven oscillatory boiling (COB). Near-wall temperature measurements, velocity fields from intrinsic tracers, and pressure spectra reveal a characteristic oscillatory timescale that quantitatively reproduces the sustained macroscopic heat flux exceeding 1.4 kW cm ⁻² . We derive a dimensionless kinetic criterion, Π < 1, that defines the boundary between film boiling and COB as a competition between condensation and coalescence timescales. Hysteresis tests establish this regime as a reproducibly stable branch of the post-CHF response. This mechanistic reinterpretation resolves the long-standing question of MEB’s origin, framing the boiling crisis as a stable hydrodynamic transition to a high-efficiency transport state and providing a foundation for predicting subcooled boiling at extreme heat fluxes.

Collective cell behaviors emerge from mechanical interactions with the extracellular matrix (ECM), yet the physical principles governing long-range cell-cell communication remain elusive. Existing models assume that neighboring cells couple by strain-stiffening the ECM between them, amplifying contractility through positive feedback. Here we show that pairwise interactions are insufficient. Instead, stable mechanical communication requires opposing mechanical anchors that allow a cell to strain-stiffen the matrix on both sides. Combining ECM strain mapping, direct cell-force measurements, and live-cell imaging, we find that isolated cell pairs generate only weak, stochastic matrix strains without persistent interactions. In contrast, cells supported by opposing neighbors, or rigid beads acting as mechanical anchors, generate large bilateral matrix strains, increase effective matrix stiffness, align collagen fibers, and form stable multicellular networks. To explain these observations, we develop a predictive mechanosensitive theory introducing effective matrix stiffness and a critical contractile force governing the transition from stochastic to persistent interaction. The theory predicts, and experiments confirm, that opposing mechanical anchorage enables cells to exceed the critical force, trigger collective matrix remodeling, and compact the matrix through collagen-fiber buckling. Together, these findings provide a unifying framework for understanding collective force generation in development, wound repair, fibrosis, and tumor progression.

The tumor microenvironment plays a critical role in drug resistance, with extracellular matrix mechanics, cell-cell crosstalk, and transport barriers contributing to poor therapeutic outcomes. Traditional two-dimensional (2D) cultures fail to capture these features, and drug efficacy in 2D often does not translate to three-dimensional (3D) models or in vivo tumors. Here, we present a 3D tumor model integrated with a high-throughput biomechanical sensor array that enables simultaneous measurement of cellular forces and matrix remodeling. The platform, fabricated using a scalable and cost-effective micro-milling approach, supports the parallel generation of multiple tumor constructs within a single dish. To demonstrate feasibility, we formed in vitro tumors using patient-derived pancreatic ductal adenocarcinoma organoids, cancer cells, and stromal fibroblasts. The sensors were then applied to characterize the evolving biophysical properties of these tumors (tissue force and stiffness) and to evaluate responses to chemotherapy drug, Gemcitabine, and the investigational agent, all-trans retinoic acid. Drug responses in 3D tumors were compared with those in 2D cultures. By combining biochemical and biomechanical readouts, this 3D platform provides a more physiologically relevant tumor model and a powerful tool for preclinical drug testing and personalized medicine.

Mechanical forces have recently emerged as critical modulators of neural communication, yet their role in high-level cognitive functions remains poorly understood. Here, we present a biologically inspired spiking neural network model that integrates mechanical tension, vesicle dynamics, and spike-timing-dependent plasticity to examine how tension influences learning, memory, and cognitive operations such as pattern completion, projection, and association. We find that increased tension enhances synaptic efficiency by accelerating vesicle clustering and recovery, resulting in a 67% improvement in memory recall speed and a 17% increase in inter-regional synchrony during projection relative to relaxed states. Conversely, a 20% reduction in tension leads to a 31% decline in memory association performance, highlighting the tension-sensitive accessibility of stored information. The model further reveals that an appropriate balance of inhibition is essential for these tension-driven effects: networks with 20% inhibitory neurons achieve optimal spatial precision in memory encoding and recall, whereas insufficient inhibition allows tension-amplified excitation to spread uncontrollably and degrade recall fidelity. Together, these in silico findings position mechanical tension as a functional neuromodulator and suggest new directions for neuromorphic design and energy-efficient, living computing platforms.

Aquatic animals such as octopuses use soft suction cups to solve the persistent challenge of wet attachment on rough surfaces. Detachment has long been described as smooth drainage governed by a Reynolds-type pressure gradient. Combining spatiotemporal pressure mapping with confocal imaging of the fluid layer between a suction cup-substrate interface, we reveal a two-stage, nonequilibrium pathway for pressure equalization that challenges this conventional view. Suction-induced elastic deformation dynamically remodels the interfacial fluid, producing a self-coupled pressure channel system. Stage I is governed by an outward-moving invasion-percolation suction front with diffusion-like scaling. When internal suction falls below a critical value, the network opens globally, and stage II follows classical Poiseuille drainage. This mechanism defines a self-modifying percolation in which the flow remodels its own pathways, which advances our understanding of biological suction and viscous adhesion and suggests design principles for long-lived wet adhesives and hydrogel microfluidics.

For centuries, the relation between mind and body has intrigued philosophers and scientists. How body affects the mind, and mind affects the body? Since mid-19th century, scientists searched for the “mind” in the anatomy of brain, just as they explored the “body” with Da Vinci’s artistic renditions of muscles. Muscles are considered as contractile force actuators, and neurons as information processors. Here, we will discuss our findings, revealed by a novel MEMS sensor, that neurons are also contractile, both in vivo and in vitro. This contractility leads to tension in axons, a long cable-like structure that connects neurons with each other. We measure the magnitude and time evolution of tension in axons using specially designed MEMS force sensors. We then correlate the tension with neuronal function (firing pattern). We find that without this tension neurons cannot function. Furthermore, we have preliminary evidence of increased neuronal contractility with physical exercise, revealing the first possible link between mind and body. Understanding the critical role of neuron mechanics on neuron function may lead to new therapies against mental diseases including anxiety, depression, dementia, and Alzheimer’s disease.

Neuronal control of skeletal muscle function is ubiquitous across species for locomotion and doing work. In particular, emergent behaviors of neurons in biohybrid neuromuscular systems can advance bioinspired locomotion research. Although recent studies have demonstrated that chemical or optogenetic stimulation of neurons can control muscular actuation through the neuromuscular junction (NMJ), the correlation between neuronal activities and resulting modulation in the muscle responses is less understood, hindering the engineering of high-level functional biohybrid systems. Here, we developed NMJ-based biohybrid crawling robots with optogenetic mouse motor neurons, skeletal muscles, 3D-printed hydrogel scaffolds, and integrated onboard wireless micro–light-emitting diode (μLED)–based optoelectronics. We investigated the coupling of the light stimulation and neuromuscular actuation through power spectral density (PSD) analysis. We verified the modulation of the mechanical functionality of the robot depending on the frequency of the optical stimulation to the neural tissue. We demonstrated continued muscle contraction up to 20 minutes after a 1-minute-long pulsed 2-hertz optical stimulation of the neural tissue. Furthermore, the robots were shown to maintain their mechanical functionality for more than 2 weeks. This study provides insights into reliable neuronal control with optoelectronics, supporting advancements in neuronal modulation, biohybrid intelligence, and automation.

The field of biohybrid robotics focuses on using biological actuators to study the emergent properties of tissues and the locomotion of living organisms. On the basis of models of swimming at small size scales, we designed and fabricated a muscle-powered, flagellate swimmer. We investigate the design of a compliant mechanism based on nonlinear mechanics and its mechanical integration with a muscle ring and motor neurons. We find that within a range of anchor stiffnesses around 1 micronewton per micrometer, the homeostatic tension in muscle is insensitive to stiffness, offering greater design flexibility. The proximity of motor neurons results in a fourfold improvement in muscle contractility. Improved contractility and nonlinear design allow for a peak swimming speed about two orders of magnitude higher than previous biohybrid flagellate swimmers, reaching 0.58 body lengths per minute (86.8 micrometers per second), by a mechanism involving inertia that we verify through flow field imaging. This swimmer opens the door for a class of intermediate–Reynolds number swimmers.

Objective. Optical stimulation of in vitro neurons requires prior transfection with light gated ion channels. This additional step brings complexity and requires optimization. Simplification of the process will ease the undertaking of studies on biological neural networks needing external stimulation. Approach. We constructed a simple platform where embryonic stem cell derived optogenetic neural spheroids, cultured and maintained separately, can be seeded on top of the primary non-optogenetic neuron cultures. Main results. We found that the primary neural network can be stimulated through the spheroids. This allows making investigations like network response dynamics and pharmacological perturbations possible. Significance. Thus, our platform provides an on-demand method to stimulate neural preparations for many different studies.