Patterned CNT-PDMS nanocomposites for flexible pressure sensors

This paper reports the fabrication process and characterization of a flexible pressure sensor based on polydimethylsiloxane (PDMS) and multi-walled carbon nanotubes (CNT-PDMS). The proposed approach relies on patterned CNT-PDMS nanocomposite strain gauges fabricated with SU-8 microstructures (with the micropatterns) in a low‑cost and simple fabrication process. This nanocomposite polymer is mounted over a PDMS membrane, which, in turn, lies on top of a PDMS diaphragm like structure. This configuration enables the PDMS membrane to bend when pressure is applied, thereby affecting the nanocomposite strain gauges, effectively changing their electrical resistance. Carbon nanotubes have several advantages such as excellent mechanical properties, high electrical conductivity and thermal stability. Furthermore, the measurement range of the proposed sensor can be adapted according to the application by varying the CNTs content and geometry of microstructure. In addition, the sensor’s biocompatibility, low cost and simple fabrication makes it very appealing for biomechanical strain sensing. The sensor’s sensitivity was about 0.073%ΔR/mmHg.

Flexible gastrointestinal motility pressure sensors based on aluminum thin-film strain-gauge arrays

This paper reports on an innovative approach to measuring intraluminal pressure in the upper gastrointestinal (GI) tract, especially monitoring GI motility and peristaltic movements. The proposed approach relies on thin-film aluminum strain gauges deposited on top of a Kapton membrane, which in turn lies on top of an SU-8 diaphragm-like structure. This structure enables the Kapton membrane to bend when pressure is applied, thereby affecting the strain gauges and effectively changing their electrical resistance. The sensor, with an area of 3.4 mm2, is fabricated using photolithography and standard microfabrication techniques (wet etching). It features a linear response (R2 = 0.9987) and an overall sensitivity of 2.6 mV mmHg−1. Additionally, its topology allows a high integration capability. The strain gauges’ responses to pressure were studied and the fabrication process optimized to achieve high sensitivity, linearity, and reproducibility. The sequential acquisition of the different signals is carried out by a microcontroller, with a 10-bit ADC and a sample rate of 250 Hz. The pressure signals are then presented in a user-friendly interface, developed using the Integrated Development Environment software, QtCreator IDE, for better visualization by physicians.

Encapsulation and controlled release of bioactive compounds in lactoferrin-glycomacropeptide nanohydrogels : curcumin and caffeine as model compounds

Curcumin and caffeine (used as lipophilic and hydrophilic model compounds, respectively) were successfully encapsulated in lactoferrin-glycomacropeptide (Lf-GMP) nanohydrogels by thermal gelation showing high encapsulation efficiencies (>90 %). FTIR spectroscopy confirmed the encapsulation of bioactive compounds in Lf-GMP nanohydrogels and revealed that according to the encapsulated compound different interactions occur with the nanohydrogel matrix. The successful encapsulation of bioactive compounds in Lf-GMP nanohydrogels was also confirmed by fluorescence measurements and confocal laser scanning microscopy. TEM images showed that loaded nanohydrogels maintain their spherical shape with sizes of 112 and 126 nm for curcumin and caffeine encapsulated in Lf-GMP nanohydrogels, respectively; in both cases a polydispersity of 0.2 was obtained. The release mechanisms of bioactive compounds through Lf-GMP nanohydrogels were evaluated at pH 2 and pH 7, by fitting the Linear Superimposition Model to the experimental data. The bioactive compounds release was found to be pH-dependent: at pH 2, relaxation is the governing phenomenon for curcumin and caffeine compounds and at pH 7 Ficks diffusion is the main mechanism of caffeine release while curcumin was not released through Lf-GMP nanohydrogels.

Influence of different fibers on the change of pore pressure of self-consolidating concrete exposed to fire

The focus of this paper is given to investigate the effect of different fibers on the pore pressure of fiber reinforced self-consolidating concrete under fire. The investigation on the pore pressure-time and temperature relationships at different depths of fiber reinforced self-consolidating concrete beams was carried out. The results indicated that micro PP fiber is more effective in mitigating the pore pressure than macro PP fiber and steel fiber. The composed use of steel fiber, micro PP fiber and macro PP fiber showed clear positive hybrid effect on the pore pressure reduction near the beam bottom subjected to fire. Compared to the effect of macro PP fiber with high dosages, the effect of micro PP fiber with low fiber contents on the pore pressure reduction is much stronger. The significant factor for reduction of pore pressure depends mainly on the number of PP fibers and not only on the fiber content. An empirical formula was proposed to predict the relative maximum pore pressure of fiber reinforced self-consolidating concrete exposed to fire by considering the moisture content, compressive strength and various fibers. The suggested model corresponds well with the experimental results of other research and tends to prove that the micro PP fiber can be the vital component for reduction in pore pressure, temperature as well spalling of concrete.

Continuous-flow precipitation as a route to prepare highly controlled nanohydroxyapatite

[Excerpt] Hydroxyapatite Ca10(PO4)6(OH)2 (HAp) has been widely used for biomedical purposes because of its exceptional biocompatibility, bioactivity and osteoconductivity [1]. As these properties are directly related to HAp particles characteristics (size, morphology and purity), a very good control of the reaction conditions is required to obtain particles with the desired properties. Usually, HAp is synthesized by wet chemical precipitation in stirred tank batch reactors that often lead to inconsistencies in product specifications due to their low mixing efficiency [2]. (...)

Real-Time decision support using data mining to predict blood pressure critical events in intensive medicine patients

Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%.