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Recent studies have reported the experimental discovery that nanoscale specimens of even a natural material, such as diamond, can be deformed elastically to as much as 10% tensile elastic strain at room temperature without the onset of permanent damage or fracture. Computational work combining ab initio calculations and machine learning (ML) algorithms has further demonstrated that the bandgap of diamond can be altered significantly purely by reversible elastic straining. These findings open up unprecedented possibilities for designing materials and devices with extreme physical properties and performance characteristics for a variety of technological applications. However, a general scientific framework to guide the design of engineering materials through such elastic strain engineering (ESE) has not yet been developed. By combining first-principles calculations with ML, we present here a general approach to map out the entire phonon stability boundary in six-dimensional strain space, which can guide the ESE of a material without phase transitions. We focus on ESE of vibrational properties, including harmonic phonon dispersions, nonlinear phonon scattering, and thermal conductivity. While the framework presented here can be applied to any material, we show as an example demonstration that the room-temperature lattice thermal conductivity of diamond can be increased by more than 100% or reduced by more than 95% purely by ESE, without triggering phonon instabilities. Such a framework opens the door for tailoring of thermal-barrier, thermoelectric, and electro-optical properties of materials and devices through the purposeful design of homogeneous or inhomogeneous strains. 

Physics-informed deep learning helps detect unknown internal structures and defects with limited nondestructive measurements. 

Fatigue arising from cyclic straining is a key factor in the degradation of properties of engineered materials and structures. Fatigue can also induce damage and fracture in natural biomaterials, such as bone, and in synthetic biomaterials used in implant devices. However, the mechanisms by which mechanical fatigue leads to deterioration of physical properties and contributes to the onset and progression of pathological states in biological cells have hitherto not been systematically explored. Here we present a general method that employs amplitude-modulated electrodeformation and microfluidics for characterizing mechanical fatigue in single biological cells. This method is capable of subjecting cells to static loads for prolonged periods of time or to large numbers of controlled mechanical fatigue cycles. We apply the method to measure the systematic changes in morphological and biomechanical characteristics of healthy human red blood cells (RBCs) and their membrane mechanical properties. Under constant amplitude cyclic tensile deformation, RBCs progressively lose their ability to stretch with increasing fatigue cycles. Our results further indicate that loss of deformability of RBCs during cyclic deformation is much faster than that under static deformation at the same maximum load over the same accumulated loading time. Such fatigue-induced deformability loss is more pronounced at higher amplitudes of cyclic deformation. These results uniquely establish the important role of mechanical fatigue in influencing physical properties of biological cells. They further provide insights into the accumulated membrane damage during blood circulation, paving the way for further investigations of the eventual failure of RBCs causing hemolysis in various hemolytic pathologies.