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It is well known that only one, two, three, four, six-fold symmetries are possible in crystalline materials. However, five-fold symmetry can exist in nanosized materials. The example is FCC metals such as silver and copper. Nanoparticles and nanowires of such metals frequently having 5-fold symmetry are composed of strained five twin crystals, i.e. "penta-twin". 

[ Structure of a penta-twinned NW ]

They have unique properties. Their nanoparticles have superior plasmonic properties and catalytic activity. Silver and copper nanowires are the strongest candidate for the next generation transparent electrode with flexibility. Hence, revealing and quantifying the formation mechanism is important and must be done prior to their mass production where one needs to enhance the yield of desired nanomaterials (particle or wire) and to control size and length. 

We are working on the development of dynamic phase-field model to simulate the formation of the penta-twins. We also perform FEM simulations to quantify internal stress state of nanoparticles and electrical conductivity of transparent electrodes. 


The PC-RAM, one of nonvolatile memories (NVMs), uses reversible transition between crystalline and amorphous states (low and high resistance or zero and one) of Ge2Sb2Te5 (GST225), with excellent scalability and reliability compared to other NVMs. Recently, a new application to neuromorphic computing becomes of great interest. The PC-RAM is easier to make many levels of intermediate resistance between zero and one states, which is a good characteristic for mimicking the operation of the synapse in human brains. 

[ PC-RAM: structure and switching mechanism ]

Zero-to-one switching is called reset operation that is done by a short high power pulse (melt and quench). So thermal analysis is the most important for simulation of the reset operation. One-to-zero switching is called set operation that is done by a long low power pulse (annealing). So the crystallization must be simulated. We use an FEA software for reset simulation and phase-field for set simulation. 

[ PC-RAM Simulations: (left) thermal simulation for reset (right) PFM simulation for set  ]

Most of ceramic materials are composed of more than three elements. Moreover, different phases exist with complexity. Predicting complex microstructure from processing conditions and the resulting electrical, mechanical, thermal properties is not an easy subject.  

An example with complex microstructure is a porous SiC sample that is used as a heating element. The sample is prepared by extrusion, drying, and sintering. Currently, we are working on the computational optimization of the geometry of the heating element, the calculation of microstructure-dependent properties (e.g. electrical/thermal conductivity vs. porosity), and the simulation of the sintering process. We use both software packages and our own codes. 

[ SiC heating element for washer fluid heater ]

[ Multi-scale simulation of an SiC heater ]