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.
In this study, the authors test the effect that the tilt angle of a solar panel has on the amount of energy it generates. This investigation highlights a simple way that people can harvest renewable energy more efficiently and effectively.
Fossil fuels are a limited resource; thus, it is important to explore new sources of energy. The authors examine the ability of switchgrass to produce ethanol and test the effects of pretreatment and grinding on ethanol yield.
Global reliance on extractive energy sources has many downsides, among which are inconsistent supply and consequent price volatility that distress companies and consumers. It is unclear if renewable energy offers stable and affordable solutions to extractive energy sources. The cost of solar energy generation has decreased sharply in recent years, prompting a surge of installations with a range of financing options. Even so, most existing options require upfront payment, making installation inaccessible for towns with limited financial resources. The primary objective of our research is to examine the use of green bonds to finance solar energy systems, as they eliminate the need for upfront capital and enable repayment through revenue generated over time. We hypothesized that if we modeled the usage of green bonds to finance the installation of a solar energy system in New Jersey, then the revenue generated over the system’s lifetime would be enough to repay the bond. After modeling the financial performance of a proposed solar energy-producing carport in Madison, New Jersey, financed with green bonds, we found that revenue from solar energy systems successfully covered the annual green bond payments and enabled the installers to obtain over 50% of the income for themselves. Our research demonstrated green bonds as a promising option for New Jersey towns with limited financial resources seeking to install solar energy systems, thereby breaking down a financial barrier.
As the world moves towards more eco-friendly methods for chemical synthesis, there's a strong interest in employing enzymes in chemical synthetic processes. Here, the authors explore how the activity of enzymes such as trypsin, lipase and nattokinase is affected by the electronic effects of the substrate they are acting on.
Simon and colleagues test how exposure to microwaves affect radish seed germination, either microwaving seeds for ninety seconds or four minutes prior to planting. Surprisingly, the authors found that seeds microwaved for four minutes exhibited 150% increased germination as compared to controls. The authors hypothesize that breakdown of the radish seed coat when exposed to heat may allow seedlings to sprout more efficiently.
The authors compare rates of renewable energy adoption between states that historically vote for democrats versus republicans in presidential elections.
The authors looked at hydrogen gas production and how reaction temperature, concentration and alkaline solution used impacted the overall reaction with silicon. They found that all alkaline solutions tested would be viable options for using silicon waste to produce hydrogen gas to be used a renewable energy source.
