Cells are basic units of life. There is increasing experimental evidence suggesting that extracellular and intracellular mechanical forces have a profound influence on a wide range of cell behavior such as growth, differentiation, apoptosis (programmed cell death), gene expression, adhesion, and signal transduction. Study of cell mechanics has drawn considerable attention from diverse fields, including biology, physics, biochemistry, bioengineering, and medicine. Our studies of cell mechanics are motivated by three overarching questions: (1) how cells transduce mechanical stimuli into biochemical processes under healthy and diseased conditions? (2) Can disease progression, such as cancer metastasis, be altered with mechanical stimuli? (3) Can cell-cell interaction be engineered to develop new generation of living machines and computers?

For a material sample, smallness may appear in various forms, e.g., physical size, layer thickness of a multilayer system, or grain size in a polycrystalline metal. Materials also have interfaces, such as material/air interface, grain boundaries in a polycrystalline material, interface between layers in a composite material. Smaller the size, higher is the interface to volume ratio. At nano scale, interfaces are abundant, and they play important roles in defining macroscopic properties of materials such as mechanical strength, energy dissipation and conductivity. Interfaces interfere with the mechanisms of deformation and transport, and often generate new mechanisms. For example, when large grains of a crystalline metal are sheared, dislocations (crystal defect) can move through the crystal. Dislocation dynamics results in the plastic deformation in the metal. When the grain size is small, grain boundaries impede the dislocations, and change the deformation characteristics and the strength of the metal. On the other hand, single crystal silicon (most used material in micro electronics and micro machines (MEMS)), is brittle at room temperature, but becomes ductile at high temperatures when dislocation avalanche appears – a phenomenon known as brittle to ductile transition (BDT). At small scale, BDT temperature may decrease due to the dislocation avalanche originating from the free surface of the single crystal sample with large surface to volume ratio, and high flaw tolerance of small samples. We address the questions: (1) How does the small size affect thermo-mechanical properties? What is the interaction between the macroscopic mechanisms of deformation and the interfaces at nano scale?

Neuron cells are responsible for memory, learning and intelligence in animals. Neurons form neuron-neuron or neuro-muscular junctions, called synapses. They exchange information at the synapse by firing (neuro-transmission), using neurotransmitters. During firing, neurotransmitters are released from vesicles that are clustered at the synapse. It has long been understood that vesicle clustering is mediated by biochemical processes in neurons. We found, to our surprise, that neurons generate mechanical tension after forming synapses, and that vesicle clustering depends on the mechanical tension. Clustering vanishes upon releasing neuronal tension by severing the neuron, but is restored when mechanical tension is applied to the severed end.  We are addressing the following questions: (1) How neuron tension is linked with vesicle clustering? (2) What is the origin of tension?

We just started this project with NSF’s Expedition grant (April 2022). It involves 15 investigators from UIUC, Stanford, Northwestern University, University of North Carolina at Greensboro, and Indiana University at Bloomington. We will explore whether living neurons can perform computations, whether they can learn, self-evolve, acquire basic hallmarks of cognition, curiosity and intelligence, and whether these traits can be enhanced by biophysical and mechanical stimulations.

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Cancer deaths are mostly caused by metastasis when cancer cells migrate away from the primary tumor to invade other organs. Tumor growth and metastatic transition of cancer cells are determined by a dynamic crosstalk between the malignant cells and the tumor microenvironment. The latter consists of stromal cells, mostly dominated by cancer associated fibroblasts (CAF) and extracellular matrix (ECM). CAFs generate mechanical contractile force. They remodel the matrix by mechanically pulling and aligning the ECM fibers, and by releasing ECM crosslinkers. Remodeled matrix favors migration of invasive cancer cells. In spite of known contractility, the mechanistic role of CAF force on cancer progression remains elusive. While the current literature views the many participants of tumor microenvironment as interacting emergent entities, it does not identify any potential universal driver that mediates this emergence. And yet, if such a driver can be identified and characterized, then its function can be interrupted to disrupt the circuit of cancer progression. We argue, based on our preliminary evidence, that CAF force can be such a driver. We are currently exploring this FORCE (FORce control of Cancer tumor µEnvironment) hypothesis: CAFs promote metastatic progression through force-dependent release of growth factors for cancer cells, and ECM remodeling. We have developed a novel sensor (Lab Chip, 2019,19 (7), 1153-1161 https://doi.org/10.1039/C8LC01273C) to address these questions. It is now possible to form an in vitro cancer tumor integrated with the sensor (video above), which monitors cell forces, migration, remodeling of ECM in situ as a function of time (see image and video below, Science Advances 7 (15) (2021) eabf2629. https://doi.org/10.1126/sciadv.abf2629).

Industrial revolution of the 19th century marked the onset of the era of machines that transformed societies. However, these machines cannot self-assemble, self-heal, or have inherent intelligence. On the other hand, since the discovery of genes, there is a considerable body of knowledge on engineering living cells. We thus envision future when soft robots will consist of living cells. They will emerge (self-evolve) through interactions between the cells (e.g., neurons, muscles) and engineered scaffolds. These machines have the potential of unprecedented capabilities, as they would carry the footprints of millions of years of evolution. We have demonstrated an autonomous biohybrid swimmer consisting of heart cells and a micro-mechanical flagellum (MEMS structure). Here, the heart cells, placed randomly on the flagellum, self-organize and synchronize their beating by interacting with each other and the soft flagellum. Through these interactions emerges a sperm like swimmer that swims autonomously (video above, Nature Communications, 5, Article number 3081, Jan 17, 2014,  doi:10.1038/ncomms4081).More recently, we demonstrated a biohybrid swimmer propelled by self-assembled muscle tissue, stimulated by neurons (image below, PNAS, 116 (40) 19841-19847, 2019, DOI: 1073/pnas.1907051116). Here, neurons interact with one another forming a network, muscle cells cooperate with each other to form muscle tissue, neurons interact with the muscle tissue to form neurons-muscular junctions to stimulate the muscle and drive the swimmer. These are the first demonstrations of a biohybrid robots emerging from randomly placed cells through hierarchical and complex interactions. We believe, future robots will evolve through such disorder-to-order transitions – a new paradigm for biohybrid machines. We are currently exploring (1) the principles of interaction between cells guided by biophysical microenvironment, (2) advanced biohybrid robots interfaced with flexible electronics, and (3) memory, learning and intelligence in neuro-muscular robots.

Silicon based micro and nanometer scale devices operating at various temperatures are ubiquitous today. However, thermo-mechanical properties of silicon at the small scale and their underlying mechanisms remain elusive. The brittle-to-ductile transition (BDT) is one such property relevant to these devises. Materials can be brittle or ductile depending on temperature. The BDT occurs over a small temperature range. For bulk silicon, the BDT is about 545°C. It is speculated that the BDT temperature of silicon may decrease with size at the nanoscale. However, recent experimental and computational studies have provided inconclusive evidence, and are often contradictory. Potential reasons for the controversy might originate from the lack of an in situ methodology that allows variation of both temperature and sample size. We resolved this controversy by carrying out in situ thermo-mechanical bending tests on single crystal silicon samples with concurrent control of temperature and size. We showed unambiguously that the BDT temperature reduces with sample size. For example, the BDT temperature decreases to 293°C for a sample size 720 nm. We explained the mechanism by which silicon reduces the BDT temperature with decreasing size. We also developed a mechanism-based model to predict the size dependence of BDT in silicon under bending. We recently completed this project in collaboration with Max Planck Institute, Düsseldorf, Germany (Proceedings of the National Academy of Sciences, July 21, 2020 117 (29) 16864-16871).