Green Measurements for Software Product Based on Sustainability Dimensions

Software is a central component in the modern world and vastly affects the environment’s sustainability. The demand for energy and resource requirements is rising when producing hardware and software units. Literature study reveals that many studies focused on green hardware; however, limited efforts were made in the greenness of software products. Green software products are necessary to solve the issues and problems related to the long-term use of software, especially from a sustainability perspective. Without a proper mechanism for measuring the greenness of a particular software product executed in a specific environment, the mentioned benefits will not be attained. Currently, there are not enough works to address this problem, and the green status of software products is uncertain and unsure. This paper aims to identify the green measurements based on sustainable dimensions in a software product. The second objective is to reveal the relationships between the elements and measurements through empirical study. The study is conducted in two phases. The first phase is the theoretical phase, where the main components, measurements and practices that influence the sustainability of a software product are identified. The second phase is the empirical study that involved 103 respondents in Malaysia investigating current practices of green software in the industrial environment and further identifying the main sustainability dimensions and measurements and their impact on achieving green software products. This study has revealed seven green measurements of software product: Productivity, Usability, Cost Reduction, Employee Support, Energy Efficiency, Resource Efficiency and Tool Support. The relationships are statistically significant, with a significance level of less than 0.01 (p = 0.000). Thus, the hypothesised relationships were all accepted. The contributions of this study revolve around the research perspectives of the measurements to attain a green software product.     

Single‐wall carbon nanotubes dispersion behavior and its effects on the morphological and mechanical properties of the electrospun nanofibers

The dispersion behavior of single‐walled carbon nanotube (SWCNT) has important effects on morphological and mechanical properties of SWCNT composite nanofibers. The relationship of the dispersion conditions with morphological and mechanical characteristics for SWCNT / polyacrylonitrile (PAN) / polyvinylpyrrolidone (PVP) composite nanofibers have been examined. The SEM and TEM analyses of the nanofibers revealed that the deformation in the nanofiber structures increases with increasing concentration of SWCNTs. Tensile results showed that only 2 wt% SWCNT loading to the electrospun composite nanofibers gave rise to 10‐fold and 3‐fold increase in the tensile modulus and tenacity of nanofiber layers, respectively. Essentially, high mechanical properties and uniform morphology of the composite nanofibers were found at SWCNT concentration of ∼2 wt% due to their stable and individual dispersion. POLYM. COMPOS., 33:1951–1959, 2012. © 2012 Society of Plastics Engineers     

Theoretical and experimental studies on EMI shielding mechanisms of multi-walled carbon nanotubes reinforced high performance composite nanofibers

Electrically conductive composite nanofibers of polyvinylpyrrolidone (PVP) filled with multi-walled carbon nanotubes (MWCNTs) were prepared by electrospinning process. The complex permittivity and electromagnetic interference shielding effectiveness (EMI SE) of all composite nanofibers were measured in the X band frequency range 8.2–12.4 GHz. The electrical conductivity, real and imaginary part of permittivity, and EMI shielding behaviors of the composite nanofibers were reported as function of MWCNTs concentration. Electrical conductivity of MWCNTs/PVP composite nanofiber followed power law model of percolation theory having a percolation threshold ?_c = 0.72 vol% (~1 wt.%) and exponent t = 1.71. The total EMI SE of MWCNTs/PVP composite nanofibers increased up to 42 dB mainly base on the absorption mechanism. The EMI SE measured from experiments was also compared with the approximate value calculated from theoretical model. The obtained theory results confirmed that the selected model presented acceptable performance for evaluating the involved parameters and prediction of the EMI SE of composite nanofibers. The ability of the theoretical model to predict the EMI shielding by reflection and absorption was found to be a function of the frequency, thickness, permittivity, and conductivity.     

Modeling and optimization of electrospun PAN nanofiber diameter using response surface methodology and artificial neural networks

Response surface methodology (RSM) based on a three‐level, three‐variable Box‐Benkhen design (BBD), and artificial neural network (ANN) techniques were compared for modeling the average diameter of electrospun polyacrylonitrile (PAN) nanofibers. The multilayer perceptron (MLP) neural networks were trained by the sets of input–output patterns using a scaled conjugate gradient backpropagation algorithm. The three important electrospinning factors were studied including polymer concentration (w/v%), applied voltage (kV) and the nozzle‐collector distance (cm). The predicted fiber diameters were in agreement with the experimental results in both ANN and RSM techniques. High‐regression coefficient between the variables and the response (R² = 0.998) indicates excellent evaluation of experimental data by second‐order polynomial regression model. The R² value was 0.990, which indicates that the ANN model was shows good fitting with experimental data. Moreover, the RSM model shows much lower absolute percentage error than the ANN model. Therefore, the obtained results indicate that the performance of RSM was better than ANN. The RSM model predicted the 118 nm value of the finest nanofiber diameter at conditions of 10 w/v% polymer concentration, 12 cm of nozzle‐collector distance, and 12 kV of the applied voltage. The predicted value (118 nm) showed only 2.5%, difference with experimental results in which 121 nm at the same setting were observed. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Effect of solution pH and adsorbent concentration on the sensing parameters of TGN‐based electrochemical sensor

The response of trilayer graphene nanoribbon (TGN)‐based ion‐sensitive field‐effect transistor (ISFET) to different pH solutions and adsorption effect on the sensing parameters are analytically studied in this research. The authors propose a TGN‐based sensor to electrochemically detect pH. To this end, absorption effect on the sensing area in the form of carrier concentration, carrier velocity, and conductance variations are investigated. Also, the caused electrical response on TGN as a detection element is analytically proposed, in which significant current decrease of the sensor is observed after exposure to high pH values. In order to verify the accuracy of the model, it is compared with recent reports on pH sensors. The TGN‐based pH sensor exposes higher current compared to that of carbon nanotube (CNT) counterpart for analogous ambient conditions. While, the comparative results demonstrate that the conductance of proposed model is lower than that of monolayer graphene‐counterpart for equivalent pH values. The results confirm that the conductance of the sensor is decreased and V_g‐min is obviously right‐shifted by increasing value of pH. The authors demonstrate that although there is not the experimental evidence reported in the part of literature for TGN sensor, but the model can assist in comprehending experiments involving nanoscale pH sensors.Inspec keywords: adsorption, graphene, ion sensitive field effect transistors, nanoribbons, electrochemical sensors, pH measurement, nanosensors, absorptionOther keywords: adsorbent concentration, TGN‐based electrochemical sensor, trilayer graphene nanoribbon‐based ion‐sensitive field‐effect transistor, adsorption effect, carbon nanotube counterpart, monolayer graphene‐counterpart, nanoscale pH sensors, pH solution effect, TGN‐based pH sensor, ISFET, CNT, C     

Nanofibers (PU and PAN) and nanoparticles (Nanoclay and MWNTs) simultaneous effects on polyurethane foam sound absorption

In this research, simultaneous effects of polyacrylonitrile (PAN) and polyurethane (PU) nanofibers, multi wall carbon nanotubes (MWNTs) and nanoclay incorporation on sound absorption behavior of polyurethane foam were studied. The most important parameters such as nanoparticles content, number and mass per unit area of nanofiber layers and foam thickness were chosen and their influences on sound absorption in a wide band of frequencies were investigated. Applying of both nanoparticles gave rise to considerable improvement in PU foam sound absorption, however in case of MWNTs more satisfied results were observed. Sound absorption tests of simultaneous incorporation of MWNTs and nanoclay showed that the optimized result can be obtained at moderate to high MWNTs percents (0.1–0.15 wt.%) and low percents of nanoclay (0.5 wt.%). On the other hand, by adding PAN or PU nanofiber layers within the PU foam structure, superior sound absorption was achieved. Upper sound absorption by increasing the numbers of nanofiber layers was obtained. Incorporation of PAN nanofiber layers showed a better effect at high mass per unit area (5 g/m²), however the higher sound absorption in case of PU nanofiber layers was observed at low mass per unit area (1 g/m²).