Photophysical Detection of Singlet Oxygen

The chemical reactivity of singlet oxygen (1O2) (SO) derives from its electronically excited state. Being a unique reactive oxygen species SO takes part in many important atmospheric, biological physical, chemical, and therapeutic process and attracted current research interest. To understand the mechanistic pathways in various process the detection and quantification of SO is very important. The direct method of detection is very challenging due to its highly reactive nature. Only direct method of determination of phosphorescence of SO at 1270 nm has been utilised but that also puts some limitation due to very low luminescence quantum yield. Indirect method using UV–Vis spectrophotometric, fluorescent and chemiluminescent probes has been extensively studied for this purpose. Elucidation of various mechanistic processes improvised the use of sophisticated spectroscopic detection probe for SO have been discussed in a simple and lucid manner in this article through citation of literature examples. Four major spectroscopic methods i.e. spectrophotometry, fluorescence, emission and chemiluminescence are elaborately discussed with special emphasis to chemical probes having high selectivity and sensitivity for SO.

Analysis and Scientific Methodological Recommendations for Reducing the Delay on Railway Crossings

In this research focus on reduces waiting time and safe travel time at a level crossing. Current research interest is the application to improve implementation, reducing the waiting time for motor vehicles at a railroad crossing. At last, got at the level crossing 5% effective result for one improving period.

An efficient sentiment analysis methodology based on long short-term memory networks

Sentiment analysis is the process of determining the sentiment polarity (positivity, neutrality or negativity) of the text. As online markets have become more popular over the past decades, online retailers and merchants are asking their buyers to share their opinions about the products they have purchased. As a result, millions of reviews are generated daily, making it difficult to make a good decision about whether a consumer should buy a product. Analyzing these enormous concepts is difficult and time-consuming for product manufacturers. Deep learning is the current research interest in Natural language processing. In the proposed model, Skip-gram architecture is used for better feature extraction of semantic and contextual information of words. LSTM (long short-term memory) is used in the proposed model for understanding complex patterns in textual data. To improve the performance of the LSTM, weight parameters are optimized by the adaptive particle Swarm Optimization algorithm. Extensive experiments were conducted on four datasets proved that our proposed APSO-LSTM model secured higher accuracy over the classical methods such as traditional LSTM, ANN, and SVM. According to simulation results, the proposed model is outperforming other existing models in different metrics.

Overtemperature-protection intelligent molecular chiroptical photoswitches

Stimuli-responsive intelligent molecular machines/devices are of current research interest due to their potential application in minimized devices. Constructing molecular machines/devices capable of accomplishing complex missions is challenging, demanding coalescence of various functions into one molecule. Here we report the construction of intelligent molecular chiroptical photoswitches based on azobenzene-fused bicyclic pillar[n]arene derivatives, which we defined as molecular universal joints (MUJs). The Z/E photoisomerization of the azobenzene moiety of MUJs induces rolling in/out conformational switching of the azobenzene-bearing side-ring and consequently leads to planar chirality switching of MUJs. Meanwhile, temperature variation was demonstrated to also cause conformational/chiroptical inversion due to the significant entropy change during the ring-flipping. As a result, photo-induced chiroptical switching could be prohibited when the temperature exceeded an upper limit, demonstrating an intelligent molecular photoswitch having over-temperature protection function, which is in stark contrast to the low-temperature-gating effect commonly encountered.

Na7(IO3)(SO4)3: the first noncentrosymmetric alkaline-metal iodate-sulfate with isolated [IO3] and [SO4] units

Metal iodates are of current research interest because of their potential application as nonlinear optical crystals.

A Metal-free Organic Emitter with Aggregation-Induced Phosphorescence

Room temperature phosphorescence (RTP) of metal-free organic molecules is a hot topic of current research interest. RTP can be enhanced through aggregation, crystallization, and the support of polymers and host-guest...

Blended Learning Approach in Graduate Studies: A Bibliometric Analysis from 1997-2021

Research on the blended learning approach in graduate studies has started since 1997. Thereafter, researchers in various subject areas have widely investigated the term blended learning. This paper thus seeks to analyze scientific literature, especially for graduate studies, published on the blended approach. All the literature published about blended approach in graduate studies was gathered using the Scopus database. The data was analyzed using Microsoft Excel. Standard bibliometric analysis was used to create the growth of publications and the citation analysis. A total of 801 documents were found based on the search results. Since 2004, the growth rate of literature on blended learning in graduate studies has accelerated radically. Journal articles and conference papers accounted for most of the publications, which were mostly written in English and Spanish. Most of the studies were conducted in the fields of social science and computer science. E-learning, online learning, collaborative learning and flipped classroom were among the most frequently used keywords. Most of the blended learning research in graduate studies was carried out in the United Kingdom, Australia, and the United States. This paper presents the literature's evolution in the blended learning approach in graduate studies and identifies current research interest and the potential future research direction.

Unravelling the Photoprotective Mechanisms of Nature-Inspired Ultraviolet Filters Using Ultrafast Spectroscopy

There are several drawbacks with the current commercially available ultraviolet (UV) filters used in sunscreen formulations, namely deleterious human and ecotoxic effects. As a result of the drawbacks, a current research interest is in identifying and designing new UV filters. One approach that has been explored in recent years is to use nature as inspiration, which is the focus of this review. Both plants and microorganisms have adapted to synthesize their own photoprotective molecules to guard their DNA from potentially harmful UV radiation. The relaxation mechanism of a molecule after it has been photoexcited can be unravelled by several techniques, the ones of most interest for this review being ultrafast spectroscopy and computational methods. Within the literature, both techniques have been implemented on plant-, and microbial-inspired UV filters to better understand their photoprotective roles in nature. This review aims to explore these findings for both families of nature-inspired UV filters in the hope of guiding the future design of sunscreens.

Dr. Ajaya Bhattarai research works with the future proposed research

I am Dr. Ajaya Bhattarai, an Assistant Professor of Chemistry at Tribhuvan University, Nepal. I have received my M.Sc. degree in Physical Chemistry from Tribhuvan University in 1998 and a Ph.D. degree in Polymer Chemistry from North Bengal University, India in 2010. I have also received the "TWAS Young Scientist Award" in 2008 for Chemistry. I have visited the University of Warsaw, Poland for Post-doctorate research in Nanomaterials as well as Surface Chemistry in 2013 under Erasmus Mundus post-doctoral fellowship of European Commission for nine months. I was at Boston College, the USA for Post-doctorate research in “Theoretical studies of Glass-Forming liquids” under Fulbright fellowship for the year 2018-2019. I have published more than 100 articles in reputed journals. My current research interest is in Polymer Chemistry, Surface Chemistry, and Nanomaterials as well as theoretical studies of Glass-Forming liquids.

Computational Schemes in the Design of Novel Materials for Energy Savings

The current demand for lightweight energy efficient materials in industries to help in addressing the current challenges faced in reducing green house gas emissions is one of the motivations behind innovative material design. This paper has tried to review in particular the importance of the hierarchical multiscale modelling strategy in the design of novel lightweight materials. It also highlights on one of the hierarchical multiscale modelling methodologies from ab-initio level to macro level in predicting macroscopic material behaviour and the impact this simulation strategy will have on the development of innovative materials. It highlights on the limitations of this modelling strategy such as: the unreasonable computational time associated with the relaxation of polymeric chains or entanglements as well as scale bridging approaches between low level and high level models which are areas of current research interest. Keywords: Multiscale modelling, lightweight materials, energy-efficiency, scale bridging, length scale.