Indian Institute of Technology Bombay

About: Indian Institute of Technology Bombay is a education organization based out in Mumbai, India. It is known for research contribution in the topics: Population & Thin film. The organization has 16756 authors who have published 33588 publications receiving 570559 citations.

[3+3] Imine and β-ketoenamine tethered fluorescent covalent-organic frameworks for CO2 uptake and nitroaromatic sensing

Abstract: Imine and β-ketoenamine based covalent-organic frameworks (COFs) are nitrogen rich organic porous materials which offer enhanced affinity for carbon dioxide. In this article, synthesis, gaseous uptake and chemo-sensing properties of four new 2-D COFs with [3+3] structural motifs have been reported. The COFs have been synthesized from readily available C3-symmetric aldehyde and amine building units via Schiff base condensation. Prior to the synthesis, reactivity and structural integrity of the building blocks were appropriated by a fully characterized model Schiff base (TAPB-Benz) obtained from the condensation of 1,3,5-tris(4′-aminophenyl)benzene (TAPB) and benzaldehyde. Reaction of 1,3,5-tris(4′-aminophenyl)benzene (TAPB) and 1,3,5-tris(4′-amino-3′,5′-isopropylphenyl)benzene (iPrTAPB) with 1,3,5-tris(4′-formylphenyl)benzene (TFPB) and 1,3,5-triformylphluroglucinol (TFP) in dry dioxane and acetic acid (cat.) resulted in the formation of crystalline 2-D frameworks, TAPB-TFPB, iPrTAPB-TFPB, TAPB-TFP and iPrTAPB-TFP. The COFs feature permanent porosity with high surface area and carbon dioxide uptake. Among these, iPrTAPB-TFP revealed the highest surface area of 756 m2 g−1 (Brunauer–Emmett–Teller) and 1515 m2 g−1 (Langmuir) and carbon dioxide uptake of 105 mg g−1 (273 K, 1 atm). Notably with 180 mg g−1 (273 K, 1 atm), TAPB-TFP shows the highest CO2 uptake capacity among all the COFs which is also comparable to previously reported high CO2 uptake capacity COFs. Furthermore, due to the inherent fluorescent capability of triphenylbenzene, the COFs are endowed with fluorescence and fluorescence chemo-sensing ability for polynitroaromatic analytes.

SunPy—Python for solar physics

Abstract: This paper presents SunPy (version 0.5), a community-developed Python package for solar physics. Python, a free, cross-platform, general-purpose, high-level programming language, has seen widespread adoption among the scientific community, resulting in the availability of a large number of software packages, from numerical computation (NumPy, SciPy) and machine learning (scikit-learn) to visualization and plotting (matplotlib). SunPy is a data-analysis environment specializing in providing the software necessary to analyse solar and heliospheric data in Python. SunPy is open-source software (BSD licence) and has an open and transparent development workflow that anyone can contribute to. SunPy provides access to solar data through integration with the Virtual Solar Observatory (VSO), the Heliophysics Event Knowledgebase (HEK), and the HELiophysics Integrated Observatory (HELIO) webservices. It currently supports image data from major solar missions (e.g., SDO, SOHO, STEREO, and IRIS), time-series data from missions such as GOES, SDO/EVE, and PROBA2/LYRA, and radio spectra from e-Callisto and STEREO/SWAVES. We describe SunPyʼs functionality, provide examples of solar data analysis in SunPy, and show how Python-based solar data-analysis can leverage the many existing tools already available in Python. We discuss the future goals of the project and encourage interested users to become involved in the planning and development of SunPy.