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Prediction of molecular energy using Coulomb matrix and Graph Neural Network

Hazra et al. | Feb 01, 2022

Prediction of molecular energy using Coulomb matrix and Graph Neural Network

With molecular energy being an integral element to the study of molecules and molecular interactions, computational methods to determine molecular energy are used for the preservation of time and resources. However, these computational methods have high demand for computer resources, limiting their widespread feasibility. The authors of this study employed machine learning to address this disadvantage, utilizing neural networks trained on different representations of molecules to predict molecular properties without the requirement of computationally-intensive processing. In their findings, the authors determined the Feedforward Neural Network, trained by two separate models, as capable of predicting molecular energy with limited prediction error.

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Analysis of reduction potentials to determine the most efficient metals for electrochemical cell alternatives

Carroll et al. | Jul 10, 2020

Analysis of reduction potentials to determine the most efficient metals for electrochemical cell alternatives

In this study, the authors investigate what metals make the most efficient electrochemical cells, which are batteries that use the difference in electrical potential to generate electricity. Calculations predicted that a cell made of iron and magnesium would have the highest efficiency. Construction of an electrochemical cell of iron and magnesium produced voltages close to the theoretical voltage predicted. These findings are important as work continues towards making batteries with the highest storage efficiency possible.

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Covalently Entrapping Catalase into Calcium Alginate Worm Pieces Using EDC Carbodiimide as a Crosslinker.

Suresh et al. | Mar 31, 2019

Covalently Entrapping Catalase into Calcium Alginate Worm Pieces Using EDC Carbodiimide as a Crosslinker.

Catalase is a biocatalyst used to break down toxic hydrogen peroxide into water and oxygen in industries such as cheese and textiles. Improving the efficiency of catalase would help us to make some industrial products, such as cheese, less expensively. The best way to maintain catalase’s conformation, and thus enhance its activity, is to immobilize it. The primary goal of this study was to find a new way of immobilizing catalase.

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Reduce the harm of acid rain to plants by producing nitrogen fertilizer through neutralization

Xu et al. | Apr 25, 2023

Reduce the harm of acid rain to plants by producing nitrogen fertilizer through neutralization
Image credit: Ave Calvar Martinez, pexels.com

The phenomenon of dying trees and plants in areas affected by acid rain has become increasingly problematic in recent times. Is there any method to efficiently utilize the rainwater and reduce the harmfulness of acid rain or make it beneficial to plants? This study aimed to investigate the potential of neutralizing acid rainwater infiltrating the soil to increase soil pH, produce beneficial salts for plants, and support better plant growth. To test this hypothesis, precipitation samples were collected from six states in the U.S. in 2022, and the pH of the acid rain was measured to obtain a representative pH value for the country. Experiments were then conducted to simulate the neutralization of acid rain and the subsequent change in soil pH levels. To evaluate the effectiveness and feasibility of this method, cat grass was planted in pots of soil soaked with solutions mimicking acid rain, with control and experimental groups receiving neutralizing agents (ammonium hydroxide) or not. Plant growth was measured by analyzing the height of the plants. Results demonstrated that neutralizing agents were effective in improving soil pH levels and that the resulting salts produced were beneficial to the growth of the grass. The findings suggest that this method could be applied on a larger agricultural scale to reduce the harmful effects of acid rain and increase agricultural efficiency.

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Racemic serine is less soluble than pure enantiomers due to stronger intermolecular hydrogen bonds

Ranka et al. | Nov 18, 2021

Racemic serine is less soluble than pure enantiomers due to stronger intermolecular hydrogen bonds

Seeking to develop a better understanding of the chemical and physical properties of amino acids that compose proteins, here the authors investigated the unusual relative insolubility of racemic mixtures of D- and L-serine compared to the solubility of pure D- or L-serine. The authors used a combination of microscopy and temperature measurements alongside previous X-ray diffraction studies to conclude that racemic DL-serine crystals consist of comparatively stronger hydrogen bond interactions compared to crystals of pure enantiomers. These stronger interactions were found to result in the unique release of heat during the crystallization of racemic mixtures.

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Linearity of piezoelectric response of electrospun polymer-based (PVDF) fibers with barium titanate nanoparticles

Nichitiu et al. | Feb 13, 2023

Linearity of piezoelectric response of electrospun polymer-based (PVDF) fibers with barium titanate nanoparticles

Here, seeking to develop an understanding of the properties that determine the viability of piezoelectric flexible materials for applications in electro-mechanical sensors, the authors investigated the effects of the inclusion BaTiO3 nanoparticles in electrospun Polyvinyledene Fluoride. They found the voltage generated had a piecewise linear dependence on the applied force at a few temperatures.

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