Research
Our work focuses on understanding the mechanics of materials at multiple length scales. We use several computational methods to determine material properties of nanomaterials and biomaterials.
Low Dimensional Materials
One dimensional material, carbyne. A nickel block has enveloped the embedded carbyne chains; insets below the figure show a view of the carbyne chains from above with Ni atoms removed, revealing that the chains have developed kinks. Electron density plot of carbyne in a nickel matrix.
Biomechanics
A multiscale model to study the effect of ECM topography on neuronal cell shape. A flat ECM shows a symmetric change in cell shape. By increasing the surface asperity diameter (๐=0.5, 1 and 2.5 ๐๐), we observe an increase in asymmetry of cell shape. Color indicates deformation.
The structure and periodic unit cell of a collagenous bio-composite with 10 wt% CNT and 20 wt% water.
Charge density distribution around hydroxyapatite unit cell computed using density functional theory.
Nanoscale deformation mechanisims of mineralized collagen fibrils for different stress and water content. Collagen (grey), water (blue) and mineral (yellow) are shown in the figure above.
Wave Mechanics
Schematic showing the inspiration of the tissue scaffold structure from hydroxyapatite in bone, as well as an ultrasound wave propagating through a representative bioinspired scaffold structure. See paper at https://doi.org/10.1016/j.jmbbm.2021.105065
Using Data Science to Find Surface Properties
We use coarse-grained modeling to mimic experimental film topographies and then develop and train a convolutional neural network to predict surface properties. Figure shows example of a polymer surface topography and training of the network. See paper at https://doi.org/10.1557/adv.2020.330
Previous Projects (2015-2020)
Bioinspired Materials
The atomic configuration of hydroxyapatite and the bioinspired geometric design of the scaffold. We use a multiscale approach to predict mechanical properties of bio-inspired scaffolds.
From right to left. Bone structure at macroscale and nanoscale. Nanoscale structure of bone (green: mineral, red: collagen). Ni-graphene nanocomposite show graphene sheets inside Ni matrix, similar to bone nanoscale structure. We use molecular dynamics to predict the interface and mechanical properties of Ni-graphene nanocomposites.
Nanocomposites
Surface texturing at the nanoscale can reduce friction and adhesion. Understanding the deformation mechanism between textured surface and counter surface would help to improve the frictional properties. Using molecular dynamics method surface properties are predicted, this will guide the experiments to design multi-asperity surfaces for tribological applications.
Multiscale modeling of core-shell nanosctructures. Zoomed-in view of continuum region at and near the atomistic region, which is boxed in blue. Atomistic region is shown inside the blue box. Bottom set of figures show core/substrate displacement field for sample exhibiting high substrate deformation and relatively low core deformation and low substrate deformation and high core deformation for higher core radius.
Polymers
PTFE chain at the atomistic scale. Inset shows the change in dihedral angles. PTFE chain interaction with the substrate will determine its adhesion strength and frictional properties. We use molecular dynamics to predict the mechanical and interface properties of PTFE.
Multi-scale modeling of PTFE fibers utilizing atomistic and coarse-grained methods to study PTFE fibers and particles. Columnar particles are colored orange and yellow. Touching fibers are colored blue and cyan. Cylindrical particle with only touching fibers visible. Spindle particles placed perpendicular and only touching fibers visible.