First-principles study on the specific heat jump in the glass transition of silica glass and the Prigogine-Defay ratio.

The most important characteristic of glass transition is a jump in the specific heatΔCp. Despite its significance, no standard theory exists to describe it. In this study, first-principles molecular-dynamics simulations are used to describe the glass transition of silica glass. The novel view that state variables are extended to include the equilibrium positions of atoms{R-j}is fully used in analyzing the simulation results. Decomposing the internal energy into three components (structural, phonon, and thermal expansion energies) reveals that the jumpΔCpof silica glass is entirely determined by the component of structural energy. The reason for the smallΔCpis its high glass-transition temperature, which makes the fluctuation in the structural energy insensitive to the temperature change. This significantly affects how the Prigogine-Defay ratioΠis interpreted, which was previously unknown. The ratioΠrepresents the ratio of the total energy change to the contribution of thermal expansion energy at the glass transition. The general property,Π> 1, of glasses indicates that glass transitions occur mainly via the change in the structural energy. Silica glass is an extreme case in that the transition occurs entirely through the change in internal structure, such as the distribution of the bending angle of Si-O-Si bonds.

A tactile sensor using single layer graphene for surface texture recognition.

Tactile sensors capable of texture recognition are essential for artificial skin functions. In this work, we describe a tactile sensor with a single sensor architecture made of single layer graphene that can recognize surface texture based on the roughness of the interacting surface. Resistance changes due to the local deformation of a local area of the single layer graphene are reflected in the resistance of the entire sensor. By introducing microstructures inspired by human finger prints, surface texture was successfully defined through fast Fourier transform analysis, and spatial resolution was easily achievable. This work provides a simple method utilizing a single sensor for surface texture recognition at the level of human sensation without using a matrix architecture which requires high density integration technology with force and vibration sensor elements.

Highly Sensitive Wearable Textile-Based Humidity Sensor Made of High-Strength, Single-Walled Carbon Nanotube/Poly(vinyl alcohol) Filaments.

Textile-based humidity sensors can be an important component of smart wearable electronic-textiles and have potential applications in the management of wounds, bed-wetting, and skin pathologies or for microclimate control in clothing. Here, we report a wearable textile-based humidity sensor for the first time using high strength (∼750 MPa) and ultratough (energy-to-break, 4300 J g-1) SWCNT/PVA filaments via a wet-spinning process. The conductive SWCNT networks in the filaments can be modulated by adjusting the intertube distance by swelling the PVA molecular chains via the absorption of water molecules. The diameter of a SWCNT/PVA filament under wet conditions can be as much as 2 times that under dry conditions. The electrical resistance of a fiber sensor stitched onto a hydrophobic textile increases significantly (by more than 220 times) after water sprayed. Textile-based humidity sensors using a 1:5 weight ratio of SWCNT/PVA filaments showed high sensitivity in high relative humidity. The electrical resistance increases by more than 24 times in a short response time of 40 s. We also demonstrated that our sensor can be used to monitor water leakage on a high hydrophobic textile (contact angle of 115.5°). These smart textiles will pave a new way for the design of novel wearable sensors for monitoring blood leakage, sweat, and underwear wetting.

Determination of the absorbed dose rate to water for the 18-mm helmet of a gamma knife.

PURPOSE: To measure the absorbed dose rate to water of (60)Co gamma rays of a Gamma Knife Model C using water-filled phantoms (WFP). METHODS AND MATERIALS: Spherical WFP with an equivalent water depth of 5, 7, 8, and 9 cm were constructed. The dose rates at the center of an 18-mm helmet were measured in an 8-cm WFP (WFP-3) and two plastic phantoms. Two independent measurement systems were used: one was calibrated to an air kerma (Set I) and the other was calibrated to the absorbed dose to water (Set II). The dose rates of WFP-3 and the plastic phantoms were converted to dose rates for an 8-cm water depth using the attenuation coefficient and the equivalent water depths. RESULTS: The dose rate measured at the center of WFP-3 using Set II was 2.2% and 1.0% higher than dose rates measured at the center of the two plastic phantoms. The measured effective attenuation coefficient of Gamma Knife photon beam in WFPs was 0.0621 cm(-1). After attenuation correction, the difference between the dose rate at an 8-cm water depth measured in WFP-3 and dose rates in the plastic phantoms was smaller than the uncertainty of the measurements. CONCLUSIONS: Systematic errors related to the characteristics of the phantom materials in the dose rate measurement of a Gamma Knife need to be corrected for. Correction of the dose rate using an equivalent water depth and attenuation provided results that were more consistent.

A numerical approach to dose optimization for moving targets using monte carlo simulations.

A novel simulation model for the dose distribution of moving targets for high-energy photons was analyzed using the EGSnrc Monte Carlo simulation. We provide here a fundamental numerical framework for the calculation of doses delivered to moving tissues in respiratory systems with improved accuracy. A spherical object with periodic motions inside a water phantom irradiated with incident photons was taken into consideration. The dose distributions of the target and its surrounding region were calculated for a variety of radiation conditions such as photon energy, beam numbers, and beam orientations as well as the target motions determined by realistic respiratory patterns. To determine the optimal dose, two parameters, the average absorbed dose ratio and dose deviation, were newly defined for the moving targets in the phantom. Optimal conditions were examined for treatment planning on tumors in motions based on the defined parameters. We found that the actual doses delivered to the tumor generally were not correlated to the respiratory patterns. Our quantitative assessment suggests useful guidelines for improved clinical radiotherapy to escalate dose concentration in the tumors by using multiple photon beams.