How Reproducible are Surface Areas Calculated from the BET Equation?

Porosity and surface area analysis play a prominent role in modern materials science. At the heart of this sits the Brunauer-Emmett-Teller (BET) theory, which has been a remarkably successful contribution to the field of materials science. The BET method was developed in the 1930s for open surfaces but is now the most widely used metric for the estimation of surface areas of micro- and mesoporous materials. Despite its widespread use, the calculation of BET surface areas causes a spread in reported areas, resulting in reproducibility problems in both academia and industry. To prove this, for this analysis, 18 already-measured raw adsorption isotherms were provided to sixty-one labs, who were asked to calculate the corresponding BET areas. This round-robin exercise resulted in a wide range of values. Here, the reproducibility of BET area determination from identical isotherms is demonstrated to be a largely ignored issue, raising critical concerns over the reliability of reported BET areas. To solve this major issue, a new computational approach to accurately and systematically determine the BET area of nanoporous materials is developed. The software, called "BET surface identification" (BETSI), expands on the well-known Rouquerol criteria and makes an unambiguous BET area assignment possible.fals

Current trend in synthesis, Post-Synthetic modifications and biological applications of Nanometal-Organic frameworks (NMOFs)

Since the early reports of MOFs and their interesting properties, research involving these materials has grown wide in scope and applications. Various synthetic approaches have ensued in view of obtaining materials with optimised properties, the extensive scope of application spanning from energy, gas sorption, catalysis biological applications has meant exponentially evolved over the years. The far‐reaching synthetic and PSM approaches and porosity control possibilities have continued to serve as a motivation for research on these materials. With respect to the biological applications, MOFs have shown promise as good candidates in applications involving drug delivery, BioMOFs, sensing, imaging amongst others. Despite being a while away from successful entry into the market, observed results in sensing, drug delivery, and imaging put these materials on the spot light as candidates poised to usher in a revolution in biology. In this regard, this review article focuses current approaches in synthesis, post functionalization and biological applications of these materials with particular attention on drug delivery, imaging, sensing and BioMOFs

How reproducible are surface areas calculated from the BET equation?

Porosity and surface area analysis play a prominent role in modern materials science. At the heart of this sits the Brunauer-Emmett-Teller (BET) theory, which has been a remarkably successful contribution to the field of materials science. The BET method was developed in the 1930s for open surfaces but is now the most widely used metric for the estimation of surface areas of micro- and mesoporous materials. Despite its widespread use, the calculation of BET surface areas causes a spread in reported areas, resulting in reproducibility problems in both academia and industry. To prove this, for this analysis, 18 already-measured raw adsorption isotherms were provided to sixty-one labs, who were asked to calculate the corresponding BET areas. This round-robin exercise resulted in a wide range of values. Here, the reproducibility of BET area determination from identical isotherms is demonstrated to be a largely ignored issue, raising critical concerns over the reliability of reported BET areas. To solve this major issue, a new computational approach to accurately and systematically determine the BET area of nanoporous materials is developed. The software, called "BET surface identification" (BETSI), expands on the well-known Rouquerol criteria and makes an unambiguous BET area assignment possible

Heat transfer analysis using ANNs with experimental data for air flowing in corrugated channels

The objective of this work is to use artificial neural networks (ANNs) for heat transfer analysis in corrugated channels. A data set evaluated experimentally is prepared for processing with the use of neural networks. Back propagation algorithm, the most common learning method for ANNs, was used in training and testing the network. To solve this algorithm a computer program using C++ has been developed. The accuracy between experimental and ANNs approach results was achieved with a mean absolute relative error less than 4%. (C) 2003 Elsevier Ltd. All rights reserved

Boksörlerde Solunum Fonksiyonlari Ve Anatomik Denglishe

The present study aimed to examine the relationship between lung capacity and balance parameters in professional boxers. Twenty-six professional-level male boxers aged 16-20 years volunteered to participate in the study. The respiratory and balance parameSunulan çalışmada, profesyonel boksörlerde akciğer kapasiteleri ile dEnglishe parametreleri arasındaki ilişkinin incelenmesi amaçlanmıştır. Çalışmaya elit düzeyde mücadele eden, 16-20 yaş arası 26 erkek boksör gönüllü olarak katılmıştır. Sporcuların solu

Finite element modeling of the effect of the ceramic coatings on heat transfer characteristics in thermal barrier applications

The heat transfer characteristics depending upon ceramic coatings in thermal barrier applications have been investigated in this paper. Finite element method (FEM) is used to compute the temperature and stress fields. The effect of the different types of coatings on thermal insulation properties and residual stresses was discussed in terms of the results by FEM. It is evaluated that the best thermal barrier coating systems, which have the lowest residual stresses and high temperature difference, are determined on the interlayer and bond coat of the MgO-ZrO2 coating system with five layers, and also finite element technique can be used to optimize the heat transfer characteristics of the thermal barrier ceramic coatings. (c) 2004 Elsevier Ltd. All rights reserved

Performance prediction for non-adiabatic capillary tube suction line heat exchanger: an artificial neural network approach

This study presents an application of the artificial neural network (ANN) model using the back propagation (BP) learning algorithm to predict the performance (suction line outlet temperature and mass flow rate) of a non-adiabatic capillary tube suction line heat exchanger, basically used as a throttling device in small household refrigeration systems. Comparative studies were made by using an ANN model, experimental results and correlations to predict the performance. These studies showed that the proposed approach could successfully be used for performance prediction for the exchanger. (C) 2004 Elsevier Ltd. All rights reserved

Thermal analysis of high temperature ZrO2 insulation ceramic coatings on Ag tapes used as sheath of Bi-2212 superconducting materials using finite element method

High temperature ZrO2-based insulation ceramic coatings were produced on Ag or AgMg sheathed Bi-2212 superconducting tapes by reel-to-reel sol-gel technique for magnet technology. These coatings are exposed to thermal loadings under annealing conditions. The residual stresses of the coatings with different thickness, as well as changes during thermal cycling were simulated by finite element analysis (FEA). It serves to produce model materials on which properties investigations are carried to better understand the one of industrially produced material. Results showed that the residual stress was the lowest for 1-mum thick coatings compared to that of 2- and 3-mum thick coatings, and the residual stresses increased with increased in coating thickness. (C) 2003 Elsevier Science Ltd. All rights reserved

Application of artificial neural network to predict specific fuel consumption and exhaust temperature for a Diesel engine

The ability of an artificial neural network model, using a back propagation learning algorithm, to predict specific fuel consumption and exhaust temperature of a Diesel engine for various injection timings is studied. The proposed new model is compared with experimental results. The comparison showed that the consistence between experimental and the network results are achieved by a mean absolute relative error less than 2%. It is considered that a well-trained neural network model provides fast and consistent results, making it an easy-to-use tool in preliminary studies for such thermal engineering problems. (c) 2005 Elsevier Ltd. All rights reserved

Faunal content of lower Pliocene Çaybagi Formation and its relationship with depositional environments, Eastern Elazig/Turkey [Alt Pliyosen Çaybagi Formasyonu'nun faunal içerigi ve çökelme ortamlari ile ilişkisi, Elazig Dogusu/Türkiye]

Çaybagi Formation is located in the eastern Taurid Tectonic Unit. The unit was deposited in alluvial fan, fluvial, delta and lacustrine environments. Although alluvial fan and braided river deposits do not contain fossils, low-sinuosity river, delta and lacustrine deposits contain ostracod, gastropod and pelecypod fossils. Kör Tepe, ÇardakdivarTepe, Hacisam Dere and Ziyaret Tepe measured sections that have time and space relationships consist of low-sinuosity river and delta-lacustrine facies and contain Candona, llyocypris, Cyprideis and Heterocypris species of ostracod fossils and Valvata, Lymnaea, Tinyyea, Planorbis, Radix, Gyraulus, Hydrobia, Potomida, Unio, Margaritifera, Anadonta ve Leguminaia species ofmollusc fossils. Moreover, different levels of Ziyaret Tepe and Kör Tepe measured section comprise Charophytes fossils. Environmental features of ostracod and mollusc species are in agreement with sedimentological data of the unit, deposited in fluvial, delta-lacustrine environments during Early Pliocene