Dehydration-induced corrugated folding in Rhapis excelsa plant leaves.

Plant leaves, whose remarkable ability for morphogenesis results in a wide range of petal and leaf shapes in response to environmental cues, have inspired scientific studies as well as the development of engineering structures and devices. Although some typical shape changes in plants and the driving force for such shape evolution have been extensively studied, there remain many poorly understood mechanisms, characteristics, and principles associated with the vast array of shape formation of plant leaves in nature. Here, we present a comprehensive study that combines experiment, theory, and numerical simulations of one such topic-the mechanics and mechanisms of corrugated leaf folding induced by differential shrinking in Rhapis excelsa. Through systematic measurements of the dehydration process in sectioned leaves, we identify a linear correlation between change in the leaf-folding angle and water loss. Building on experimental findings, we develop a generalized model that provides a scaling relationship for water loss in sectioned leaves. Furthermore, our study reveals that corrugated folding induced by dehydration in R. excelsa leaves is achieved by the deformation of a structural architecture-the "hinge" cells. Utilizing such connections among structure, morphology, environmental stimuli, and mechanics, we fabricate several biomimetic machines, including a humidity sensor and morphing devices capable of folding in response to dehydration. The mechanisms of corrugated folding in R. excelsa identified in this work provide a general understanding of the interactions between plant leaves and water. The actuation mechanisms identified in this study also provide insights into the rational design of soft machines.

Grain boundary plasticity initiated by excess volume.

Grain boundaries (GBs) serve not only as strong barriers to dislocation motion, but also as important carriers to accommodate plastic deformation in crystalline solids. During deformation, the inherent excess volume associated with loose atomic packing in GBs brings about a microscopic degree of freedom that can initiate GB plasticity, which is beyond the classic geometric description of GBs. However, identification of this atomistic process has long remained elusive due to its transient nature. Here, we use Au polycrystals to unveil a general and inherent route to initiating GB plasticity via a transient topological transition process triggered by the excess volume. This route underscores the general impact of a microscopic degree of freedom which is governed by a stress-triaxiality-based criterion. Our findings provide a missing perspective for developing a more comprehensive understanding of the role of GBs in plastic deformation.

Phonon stability boundary and deep elastic strain engineering of lattice thermal conductivity.

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.

Microfluidic study of retention and elimination of abnormal red blood cells by human spleen with implications for sickle cell disease.

The spleen clears altered red blood cells (RBCs) from circulation, contributing to the balance between RBC formation (erythropoiesis) and removal. The splenic RBC retention and elimination occur predominantly in open circulation where RBCs flow through macrophages and inter-endothelial slits (IESs). The mechanisms underlying and interconnecting these processes significantly impact clinical outcomes. In sickle cell disease (SCD), blockage of intrasplenic sickled RBCs is observed in infants splenectomized due to acute splenic sequestration crisis (ASSC). This life-threatening RBC pooling and organ swelling event is plausibly triggered or enhanced by intra-tissular hypoxia. We present an oxygen-mediated spleen-on-a-chip platform for in vitro investigations of the homeostatic balance in the spleen. To demonstrate and validate the benefits of this general microfluidic platform, we focus on SCD and study the effects of hypoxia on splenic RBC retention and elimination. We observe that RBC retention by IESs and RBC-macrophage adhesion are faster in blood samples from SCD patients than those from healthy subjects. This difference is markedly exacerbated under hypoxia. Moreover, the sickled RBCs under hypoxia show distinctly different phagocytosis processes from those non-sickled RBCs under hypoxia or normoxia. We find that reoxygenation significantly alleviates RBC retention at IESs, and leads to rapid unsickling and fragmentation of the ingested sickled RBCs inside macrophages. These results provide unique mechanistic insights into how the spleen maintains its homeostatic balance between splenic RBC retention and elimination, and shed light on how disruptions in this balance could lead to anemia, splenomegaly, and ASSC in SCD and possible clinical manifestations in other hematologic diseases.

Artificial intelligence velocimetry and microaneurysm-on-a-chip for three-dimensional analysis of blood flow in physiology and disease.

Understanding the mechanics of blood flow is necessary for developing insights into mechanisms of physiology and vascular diseases in microcirculation. Given the limitations of technologies available for assessing in vivo flow fields, in vitro methods based on traditional microfluidic platforms have been developed to mimic physiological conditions. However, existing methods lack the capability to provide accurate assessment of these flow fields, particularly in vessels with complex geometries. Conventional approaches to quantify flow fields rely either on analyzing only visual images or on enforcing underlying physics without considering visualization data, which could compromise accuracy of predictions. Here, we present artificial-intelligence velocimetry (AIV) to quantify velocity and stress fields of blood flow by integrating the imaging data with underlying physics using physics-informed neural networks. We demonstrate the capability of AIV by quantifying hemodynamics in microchannels designed to mimic saccular-shaped microaneurysms (microaneurysm-on-a-chip, or MAOAC), which signify common manifestations of diabetic retinopathy, a leading cause of vision loss from blood-vessel damage in the retina in diabetic patients. We show that AIV can, without any a priori knowledge of the inlet and outlet boundary conditions, infer the two-dimensional (2D) flow fields from a sequence of 2D images of blood flow in MAOAC, but also can infer three-dimensional (3D) flow fields using only 2D images, thanks to the encoded physics laws. AIV provides a unique paradigm that seamlessly integrates images, experimental data, and underlying physics using neural networks to automatically analyze experimental data and infer key hemodynamic indicators that assess vascular injury.

Digital printing of shape-morphing natural materials.

We demonstrate how programmable shape evolution and deformation can be induced in plant-based natural materials through standard digital printing technologies. With nonallergenic pollen paper as the substrate material, we show how specific geometrical features and architectures can be custom designed through digital printing of patterns to modulate hygrophobicity, geometry, and complex shapes. These autonomously hygromorphing configurations can be "frozen" by postprocessing coatings to meet the needs of a wide spectrum of uses and applications. Through computational simulations involving the finite element method and accompanying experiments, we develop quantitative insights and a general framework for creating complex shapes in eco-friendly natural materials with potential sustainable applications for scalable manufacturing.

Metallization of diamond.

Experimental discovery of ultralarge elastic deformation in nanoscale diamond and machine learning of its electronic and phonon structures have created opportunities to address new scientific questions. Can diamond, with an ultrawide bandgap of 5.6 eV, be completely metallized, solely under mechanical strain without phonon instability, so that its electronic bandgap fully vanishes? Through first-principles calculations, finite-element simulations validated by experiments, and neural network learning, we show here that metallization/demetallization as well as indirect-to-direct bandgap transitions can be achieved reversibly in diamond below threshold strain levels for phonon instability. We identify the pathway to metallization within six-dimensional strain space for different sample geometries. We also explore phonon-instability conditions that promote phase transition to graphite. These findings offer opportunities for tailoring properties of diamond via strain engineering for electronic, photonic, and quantum applications.

Extraction of mechanical properties of materials through deep learning from instrumented indentation.

Instrumented indentation has been developed and widely utilized as one of the most versatile and practical means of extracting mechanical properties of materials. This method is particularly desirable for those applications where it is difficult to experimentally determine the mechanical properties using stress-strain data obtained from coupon specimens. Such applications include material processing and manufacturing of small and large engineering components and structures involving the following: three-dimensional (3D) printing, thin-film and multilayered structures, and integrated manufacturing of materials for coupled mechanical and functional properties. Here, we utilize the latest developments in neural networks, including a multifidelity approach whereby deep-learning algorithms are trained to extract elastoplastic properties of metals and alloys from instrumented indentation results using multiple datasets for desired levels of improved accuracy. We have established algorithms for solving inverse problems by recourse to single, dual, and multiple indentation and demonstrate that these algorithms significantly outperform traditional brute force computations and function-fitting methods. Moreover, we present several multifidelity approaches specifically for solving the inverse indentation problem which 1) significantly reduce the number of high-fidelity datasets required to achieve a given level of accuracy, 2) utilize known physical and scaling laws to improve training efficiency and accuracy, and 3) integrate simulation and experimental data for training disparate datasets to learn and minimize systematic errors. The predictive capabilities and advantages of these multifidelity methods have been assessed by direct comparisons with experimental results for indentation for different commercial alloys, including two wrought aluminum alloys and several 3D printed titanium alloys.

Actuation and locomotion driven by moisture in paper made with natural pollen.

Here we describe the development of a humidity-responsive sheet of paper that is derived solely from natural pollen. Adaptive soft material components of the paper exhibit diverse and well-integrated responses to humidity that promote shape reconfiguration, actuation, and locomotion. This mechanically versatile and nonallergenic paper can generate a cyclically high contractile stress upon water absorption and desorption, and the rapid exchange of water drives locomotion due to hydrodynamic effects. Such dynamic behavior can be finely tuned by adjusting the structure and properties of the paper, including thickness, surface roughness, and processing conditions, analogous to those of classical soapmaking. We demonstrate that humidity-responsive paper-like actuators can mimic the blooming of the Michelia flower and perform self-propelled motion. Harnessing the material properties of bioinspired systems such as pollen paper opens the door to a wide range of sustainable, eco-friendly, and biocompatible material innovation platforms for applications in sensing, actuation, and locomotion.

Mechanical fatigue of human red blood cells.

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.

Deep elastic strain engineering of bandgap through machine learning.

Nanoscale specimens of semiconductor materials as diverse as silicon and diamond are now known to be deformable to large elastic strains without inelastic relaxation. These discoveries harbinger a new age of deep elastic strain engineering of the band structure and device performance of electronic materials. Many possibilities remain to be investigated as to what pure silicon can do as the most versatile electronic material and what an ultrawide bandgap material such as diamond, with many appealing functional figures of merit, can offer after overcoming its present commercial immaturity. Deep elastic strain engineering explores full six-dimensional space of admissible nonlinear elastic strain and its effects on physical properties. Here we present a general method that combines machine learning and ab initio calculations to guide strain engineering whereby material properties and performance could be designed. This method invokes recent advances in the field of artificial intelligence by utilizing a limited amount of ab initio data for the training of a surrogate model, predicting electronic bandgap within an accuracy of 8 meV. Our model is capable of discovering the indirect-to-direct bandgap transition and semiconductor-to-metal transition in silicon by scanning the entire strain space. It is also able to identify the most energy-efficient strain pathways that would transform diamond from an ultrawide-bandgap material to a smaller-bandgap semiconductor. A broad framework is presented to tailor any target figure of merit by recourse to deep elastic strain engineering and machine learning for a variety of applications in microelectronics, optoelectronics, photonics, and energy technologies.

Differential growth and shape formation in plant organs.

Morphogenesis is a phenomenon by which a wide variety of functional organs are formed in biological systems. In plants, morphogenesis is primarily driven by differential growth of tissues. Much effort has been devoted to identifying the role of genetic and biomolecular pathways in regulating cell division and cell expansion and in influencing shape formation in plant organs. However, general principles dictating how differential growth controls the formation of complex 3D shapes in plant leaves and flower petals remain largely unknown. Through quantitative measurements on live plant organs and detailed finite-element simulations, we show how the morphology of a growing leaf is determined by both the maximum value and the spatial distribution of growth strain. With this understanding, we develop a broad scientific framework for a morphological phase diagram that is capable of rationalizing four configurations commonly found in plant organs: twisting, helical twisting, saddle bending, and edge waving. We demonstrate the robustness of these findings and analyses by recourse to synthetic reproduction of all four configurations using controlled polymerization of a hydrogel. Our study points to potential approaches to innovative geometrical design and actuation in such applications as building architecture, soft robotics and flexible electronics.

Controlled molecular self-assembly of complex three-dimensional structures in soft materials.

Many applications in tissue engineering, flexible electronics, and soft robotics call for approaches that are capable of producing complex 3D architectures in soft materials. Here we present a method using molecular self-assembly to generate hydrogel-based 3D architectures that resembles the appealing features of the bottom-up process in morphogenesis of living tissues. Our strategy effectively utilizes the three essential components dictating living tissue morphogenesis to produce complex 3D architectures: modulation of local chemistry, material transport, and mechanics, which can be engineered by controlling the local distribution of polymerization inhibitor (i.e., oxygen), diffusion of monomers/cross-linkers through the porous structures of cross-linked polymer network, and mechanical constraints, respectively. We show that oxygen plays a role in hydrogel polymerization which is mechanistically similar to the role of growth factors in tissue growth, and the continued growth of hydrogel enabled by diffusion of monomers/cross-linkers into the porous hydrogel similar to the mechanisms of tissue growth enabled by material transport. The capability and versatility of our strategy are demonstrated through biomimetics of tissue morphogenesis for both plants and animals, and its application to generate other complex 3D architectures. Our technique opens avenues to studying many growth phenomena found in nature and generating complex 3D structures to benefit diverse applications.

Mechanics of diseased red blood cells in human spleen and consequences for hereditary blood disorders.

In red blood cell (RBC) diseases, the spleen contributes to anemia by clearing the damaged RBCs, but its unique ability to mechanically challenge RBCs also poses the risk of inducing other pathogenic effects. We have analyzed RBCs in hereditary spherocytosis (HS) and hereditary elliptocytosis (HE), two typical examples of blood disorders that result in membrane protein defects in RBCs. We use a two-component protein-scale RBC model to simulate the traversal of the interendothelial slit (IES) in the human spleen, a stringent biomechanical challenge on healthy and diseased RBCs that cannot be directly observed in vivo. In HS, our results confirm that the RBC loses surface due to weakened cohesion between the lipid bilayer and the cytoskeleton and reveal that surface loss may result from vesiculation of the RBC as it crosses IES. In HE, traversing IES induces sustained elongation of the RBC with impaired elasticity and fragmentation in severe disease. Our simulations thus suggest that in inherited RBC disorders, the spleen not only filters out pathological RBCs but also directly contributes to RBC alterations. These results provide a mechanistic rationale for different clinical outcomes documented following splenectomy in HS patients with spectrin-deficient and ankyrin-deficient RBCs and offer insights into the pathogenic role of human spleen in RBC diseases.

Simultaneous polymerization and adhesion under hypoxia in sickle cell disease.

Polymerization and adhesion, dynamic processes that are hallmarks of sickle cell disease (SCD), have thus far been studied in vitro only separately. Here, we present quantitative results of the simultaneous and synergistic effects of adhesion and polymerization of deoxygenated sickle hemoglobin (HbS) in the human red blood cell (RBC) on the mechanisms underlying vasoocclusive pain crisis. For this purpose, we employ a specially developed hypoxic microfluidic platform, which is capable of inducing sickling and unsickling of RBCs in vitro, to test blood samples from eight patients with SCD. We supplemented these experimental results with detailed molecular-level computational simulations of cytoadherence and biorheology using dissipative particle dynamics. By recourse to image analysis techniques, we characterize sickle RBC maturation stages in the following order of the degree of adhesion susceptibility under hypoxia: sickle reticulocytes in circulation (SRs) → sickle mature erythrocytes (SMEs) → irreversibly sickled cells (ISCs). We show that (i) hypoxia significantly enhances sickle RBC adherence; (ii) HbS polymerization enhances sickle cell adherence in SRs and SMEs, but not in ISCs; (iii) SRs exhibit unique adhesion dynamics where HbS fiber projections growing outward from the cell surface create multiple sites of adhesion; and (iv) polymerization stimulates adhesion and vice versa, thereby establishing the bidirectional coupling between the two processes. These findings offer insights into possible mechanistic pathways leading to vasoocclusion crisis. They also elucidate the processes underlying the onset of occlusion that may involve circulating reticulocytes, which are more abundant in hemolytic anemias due to robust compensatory erythropoiesis.

Formation and size distribution of self-assembled vesicles.

When detergents and phospholipid membranes are dispersed in aqueous solutions, they tend to self-assemble into vesicles of various shapes and sizes by virtue of their hydrophobic and hydrophilic segments. A clearer understanding of such vesiculation processes holds promise for better elucidation of human physiology and disease, and paves the way to improved diagnostics, drug development, and drug delivery. Here we present a detailed analysis of the energetics and thermodynamics of vesiculation by recourse to nonlinear elasticity, taking into account large deformation that may arise during the vesiculation process. The effects of membrane size, spontaneous curvature, and membrane stiffness on vesiculation and vesicle size distribution were investigated, and the critical size for vesicle formation was determined and found to compare favorably with available experimental evidence. Our analysis also showed that the critical membrane size for spontaneous vesiculation was correlated with membrane thickness, and further illustrated how the combined effects of membrane thickness and physical properties influenced the size, shape, and distribution of vesicles. These findings shed light on the formation of physiological extracellular vesicles, such as exosomes. The findings also suggest pathways for manipulating the size, shape, distribution, and physical properties of synthetic vesicles, with potential applications in vesicle physiology, the pathobiology of cancer and other diseases, diagnostics using in vivo liquid biopsy, and drug delivery methods.

Isolation of exosomes from whole blood by integrating acoustics and microfluidics.

Exosomes are nanoscale extracellular vesicles that play an important role in many biological processes, including intercellular communications, antigen presentation, and the transport of proteins, RNA, and other molecules. Recently there has been significant interest in exosome-related fundamental research, seeking new exosome-based biomarkers for health monitoring and disease diagnoses. Here, we report a separation method based on acoustofluidics (i.e., the integration of acoustics and microfluidics) to isolate exosomes directly from whole blood in a label-free and contact-free manner. This acoustofluidic platform consists of two modules: a microscale cell-removal module that first removes larger blood components, followed by extracellular vesicle subgroup separation in the exosome-isolation module. In the cell-removal module, we demonstrate the isolation of 110-nm particles from a mixture of micro- and nanosized particles with a yield greater than 99%. In the exosome-isolation module, we isolate exosomes from an extracellular vesicle mixture with a purity of 98.4%. Integrating the two acoustofluidic modules onto a single chip, we isolated exosomes from whole blood with a blood cell removal rate of over 99.999%. With its ability to perform rapid, biocompatible, label-free, contact-free, and continuous-flow exosome isolation, the integrated acoustofluidic device offers a unique approach to investigate the role of exosomes in the onset and progression of human diseases with potential applications in health monitoring, medical diagnosis, targeted drug delivery, and personalized medicine.

Biomechanics of red blood cells in human spleen and consequences for physiology and disease.

Red blood cells (RBCs) can be cleared from circulation when alterations in their size, shape, and deformability are detected. This function is modulated by the spleen-specific structure of the interendothelial slit (IES). Here, we present a unique physiological framework for development of prognostic markers in RBC diseases by quantifying biophysical limits for RBCs to pass through the IES, using computational simulations based on dissipative particle dynamics. The results show that the spleen selects RBCs for continued circulation based on their geometry, consistent with prior in vivo observations. A companion analysis provides critical bounds relating surface area and volume for healthy RBCs beyond which the RBCs fail the "physical fitness test" to pass through the IES, supporting independent experiments. Our results suggest that the spleen plays an important role in determining distributions of size and shape of healthy RBCs. Because mechanical retention of infected RBC impacts malaria pathogenesis, we studied key biophysical parameters for RBCs infected with Plasmodium falciparum as they cross the IES. In agreement with experimental results, surface area loss of an infected RBC is found to be a more important determinant of splenic retention than its membrane stiffness. The simulations provide insights into the effects of pressure gradient across the IES on RBC retention. By providing quantitative biophysical limits for RBCs to pass through the IES, the narrowest circulatory bottleneck in the spleen, our results offer a broad approach for developing quantitative markers for diseases such as hereditary spherocytosis, thalassemia, and malaria.

Three-dimensional manipulation of single cells using surface acoustic waves.

The ability of surface acoustic waves to trap and manipulate micrometer-scale particles and biological cells has led to many applications involving "acoustic tweezers" in biology, chemistry, engineering, and medicine. Here, we present 3D acoustic tweezers, which use surface acoustic waves to create 3D trapping nodes for the capture and manipulation of microparticles and cells along three mutually orthogonal axes. In this method, we use standing-wave phase shifts to move particles or cells in-plane, whereas the amplitude of acoustic vibrations is used to control particle motion along an orthogonal plane. We demonstrate, through controlled experiments guided by simulations, how acoustic vibrations result in micromanipulations in a microfluidic chamber by invoking physical principles that underlie the formation and regulation of complex, volumetric trapping nodes of particles and biological cells. We further show how 3D acoustic tweezers can be used to pick up, translate, and print single cells and cell assemblies to create 2D and 3D structures in a precise, noninvasive, label-free, and contact-free manner.

Cellular normoxic biophysical markers of hydroxyurea treatment in sickle cell disease.

Hydroxyurea (HU) has been used clinically to reduce the frequency of painful crisis and the need for blood transfusion in sickle cell disease (SCD) patients. However, the mechanisms underlying such beneficial effects of HU treatment are still not fully understood. Studies have indicated a weak correlation between clinical outcome and molecular markers, and the scientific quest to develop companion biophysical markers have mostly targeted studies of blood properties under hypoxia. Using a common-path interferometric technique, we measure biomechanical and morphological properties of individual red blood cells in SCD patients as a function of cell density, and investigate the correlation of these biophysical properties with drug intake as well as other clinically measured parameters. Our results show that patient-specific HU effects on the cellular biophysical properties are detectable at normoxia, and that these properties are strongly correlated with the clinically measured mean cellular volume rather than fetal hemoglobin level.