Carbon-based conductive rubber composite for 3D printed flexible strain sensors

Polymeric-based flexible electronic devices are in high demand due to its wide range of applications. Natural rubber (NR) shows a great potential as matrix phase for flexible conductive polymer composites with its high elasticity and fatigue resistance. In this study, a new 3D printable conductive NR (CNR) composite was developed for strain sensor applications. Different contents of conductive carbon black (CCB) were mixed with NR latex to investigate the effect of the filler content on electrical and mechanical properties of the composites. The best-known CNR composite with the CCB content of 12 phr was selected in order to produce the feedstock for the stereolithography process (SLA). The morphological, electrical, and mechanical properties of cast and 3D-printed samples were investigated and compared. Although the 3D-printed CNR sample had slightly lower conductivity than the cast one, it possessed comparable tensile strength and elongation at break, with values of 12.4 MPa and 703%, respectively. In addition, electrical responses of the CNR samples were investigated to demonstrate the electromechanical property of the material as a strain sensor. The 3D-printed CNR sample exhibited the highest electromechanical sensitivity with a gauge factor (GF) of 361.4 (ε = 210%–300%) and showed good repeatability for 500 cycles. In conclusion, the development of this 3D printable functional material with great sensing capability will pave the way for innovative designs of personalized sensing textiles and other smart wearable devices.     

Sampling, sample treatment and quality assurance issues for the determination of phosphorus species in natural waters and soils

Phosphorus is an important macronutrient and the accurate determination of phosphorus species in environmental matrices such as natural waters and soils is essential for understanding the biogeochemical cycling of the element, studying its role in ecosystem health and monitoring compliance with legislation. This paper provides a critical review of sample collection, storage and treatment procedures for the determination of phosphorus species in environmental matrices. Issues such as phosphorus speciation, the molybdenum blue method, digestion procedures for organic phosphorus species, choice of model compounds for analytical studies, quality assurance and the availability of environmental CRMs for phosphate are also discussed in detail.     

Measurements of Fission and Radioactive Capture Reaction Rates Inside the Fuel of the Ipen/MB-01

This work presents the measures of the nuclear reaction rates along the radial direction of the fuel pellet by irradiation and posterior gamma spectrometry of a thin slice of fuel pellet of UO₂ at 4.3% enrichment. From its irradiation, the rate of radioactive capture and fission had been measured as a function of the radius of the pellet disk using a Ortec GMX HPGe detector. Lead collimators had been used for this purpose. Simulating the fuel pellet in the pin fuel of the IPEN/MB-01 reactor, a thin UO₂ disk is used, being inserted in the interior of a dismountable fuel rod. This fuel rod is then placed in the central position of the IPEN/MB-01 reactor core and irradiated during 1 h under a neutron flux of 5 ×10⁸ n/cm² s. In gamma spectrometry, 10 collimators with different diameters have been used; consequently, the nuclear reactions of radioactive capture that occurs in atoms of ²³⁸U and the fission that occurs on both ²³⁵U and ²³⁸U are measured in function of 10 different regions (diameter of collimator) of the UO₂ fuel pellet disk. Nuclear fission produces different fission products such as ¹⁴³Ce with a yield fission of 5.9% which decay is monitored in this work. Corrections in geometric efficiency due to introduction of collimators on HPGe detection system were estimated using photon transport of MCNP-4C code. Some calculated values of nuclear reaction rate of radioactive capture and fission along the radial direction of the fuel pellet obtained by Monte Carlo methodology, using the MCNP-4C code, are presented and compared to the experimental data showing very good agreement.