Highly-Sensitive Surface-Enhanced Raman Spectroscopy (SERS)-based Chemical Sensor using 3D Graphene Foam Decorated with Silver Nanoparticles as SERS substrate.

In this work, a novel platform for surface-enhanced Raman spectroscopy (SERS)-based chemical sensors utilizing three-dimensional microporous graphene foam (GF) decorated with silver nanoparticles (AgNPs) is developed and applied for methylene blue (MB) detection. The results demonstrate that silver nanoparticles significantly enhance cascaded amplification of SERS effect on multilayer graphene foam (GF). The enhancement factor of AgNPs/GF sensor is found to be four orders of magnitude larger than that of AgNPs/Si substrate. In addition, the sensitivity of the sensor could be tuned by controlling the size of silver nanoparticles. The highest SERS enhancement factor of ∼ 5 × 10(4) is achieved at the optimal nanoparticle size of 50 nm. Moreover, the sensor is capable of detecting MB over broad concentration ranges from 1 nM to 100 µM. Therefore, AgNPs/GF is a highly promising SERS substrate for detection of chemical substances with ultra-low concentrations.

Morphological study of the proximal femur: a new method of geometrical assessment using 3-dimensional reverse engineering.

This study presents a new method of using computerized tomography images combined with the reverse engineering technique to obtain and analyse the three-dimensional inner and outer geometry of the proximal cadaveric femur. Three-dimensional models were reconstructed from the computerized tomography images and approximated with 2D and 3D fitting algorithms based on reverse engineering methods. The following parameters were calculated for each femur: femoral head diameter, femoral neck axis, femoral shaft axis, anteversion angle and neck-shaft angle. These data represent the geometry of the studied proximal femur, and can be used for the design of proper size and shape of femoral prostheses and trochanteric nail systems.