Variable temperature FTIR study on the surface acidity of variously treated sulfated zirconias

Fabrication and Characterization of Humidity Sensors Based on Graphene Oxide-PEDOT:PSS Composites on a Flexible Substrate

In this paper, we present a simple, fast, and cost-effective method for the large-scale fabrication of high-sensitivity humidity sensors on flexible substrates. These sensors consist of a micro screen-printed capacitive structure upon which a sensitive layer is deposited. We studied two different structures and three different sensing materials by modifying the concentration of poly(3,4-ethylenedioxythiophene)/polystyrene sulfonate (PEDOT:PSS) in a graphene oxide (GO) solution. The results show that the aggregation of the PEDOT:PSS to the GO can modify its electrical properties, boosting the performance of the capacitive sensors in terms of both resistive losses and sensitivity to relative humidity (RH) changes. Thus, in an area less than 30 mm2, the GO/PEDOT:PSS-based sensors can achieve a sensitivity much higher (1.22 nF/%RH at 1 kHz) than other similar sensors presented in the literature which, together with their good thermal stability, time response, and performance over bending, demonstrates that the manufacturing approach described in this work paves the way for the mass production of flexible humidity sensors in an inexpensive way.

Fabrication of mesoporous lignin-based biosorbent from rice straw and its application for heavy-metal-ion removal

Lignocellulosic biomass offers the most abundant renewable resource in replacing traditional fossil resources. However, it is still a major challenge to directly convert the lignin component into value-added materials. The availability of plentiful hydroxyl groups in lignin macromolecules and its unique three-dimensional structure make it an ideal precursor for mesoporous biosorbents. In this work, we reported an environmentally friendly and economically feasible method for the fabrication of mesoporous lignin-based biosorbent (MLBB) from lignocellulosic biomass through a SO₃ micro-thermal-explosion process, as a byproduct of microcrystalline cellulose. BET analysis reveal the average pore-size distribution of 5.50nm, the average pore value of 0.35cm³/g, and the specific surface area of 186m²/g. The physicochemical properties of MLBB were studied by fourier transform infrared spectroscopy (FTIR), attenuated-total-reflection fourier transform infrared spectroscopy (ATR-FTIR), X-ray photoelectron spectroscopy (XPS), and element analysis. These results showed that there are large amounts of sulfonic functional groups existing on the surface of this biosorbent. Pb(II) was used as a model heavy-metal-ion to demonstrate the technical feasibility for heavy-metal-ion removal. Considering that lignocellulosic biomass is a naturally abundant and renewable resource and SO₃ micro-thermal-explosion is a proven technique, this biosorbent can be easily produced at large scale and become a sustainable and reliable resource for wastewater treatment.

Performance assessment and beamline diagnostics based on evaluation of temporal information from infrared spectral datasets by means of R Environment for statistical analysis

Assessment of the performance and up-to-date diagnostics of scientific equipment is one of the key components in contemporary laboratories. Most reliable checks are performed by real test experiments while varying the experimental conditions (typically, in the case of infrared spectroscopic measurements, the size of the beam aperture, the duration of the experiment, the spectral range, the scanner velocity, etc.). On the other hand, the stability of the instrument response in time is another key element of the great value. Source stability (or easy predictable temporal changes, similar to those observed in the case of synchrotron radiation-based sources working in non top-up mode), detector stability (especially in the case of liquid nitrogen- or liquid helium-cooled detectors) should be monitored. In these cases, recorded datasets (spectra) include additional variables such as time stamp when a particular spectrum was recorded (in the case of time trial experiments). A favorable approach in evaluating these data is building hyperspectral object that consist of all spectra and all additional parameters at which these spectra were recorded. Taking into account that these datasets could be considerably large in size, there is a need for the tools for semiautomatic data evaluation and information extraction. A comprehensive R archive network--the open-source R Environment--with its flexibility and growing potential, fits these requirements nicely. In this paper, examples of practical implementation of methods available in R for real-life Fourier transform infrared (FTIR) spectroscopic data problems are presented. However, this approach could easily be adopted to many various laboratory scenarios with other spectroscopic techniques.