![Integrating microbial fuel cell with sedum green roof for stormwater retention and renewable energy generation](/rails/active_storage/representations/proxy/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBdmtOIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--c8b89554a261ec5cfe764af414a5cabe2f83acb9/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaDdCem9MWm05eWJXRjBTU0lJY0c1bkJqb0dSVlE2QzNKbGMybDZaVWtpRFRZd01IZzJNREErQmpzR1ZBPT0iLCJleHAiOm51bGwsInB1ciI6InZhcmlhdGlvbiJ9fQ==--33b2b080106a274a4ca568f8742d366d42f20c14/Figure1.png)
The authors looked at renewable energy generators and the ability to utilize green roofs as a solution to climate change.
Read More...Integrating microbial fuel cell with sedum green roof for stormwater retention and renewable energy generation
The authors looked at renewable energy generators and the ability to utilize green roofs as a solution to climate change.
Read More...Analyzing the effects of multiple adhesives on elastic collisions and energy loss in a Newton’s Cradle
The energy conservation in a system of objects in collision depends on the elasticity of the objects and environmental factors such as air resistance. One system that relies heavily on elasticity is the Newton’s Cradle. We aimed to determine the extent to which these adhesives serve to mitigate or worsen the chaotic movements and elastic collisions.
Read More...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.
Read More...Use of drone with sodium hydroxide carriers to absorb carbon dioxide from ambient air
In this study, the authors address the current climate concern of high CO2 levels by testing solid forms of hydroxide for CO2 reduction and designing a drone to fly it in ambient air!
Read More...Using Graphene Oxide to Efficiently Filter Particulate Matter at High Concentrations
Air pollution has detrimental effects on both the environment and humans. Here, researchers use graphene oxide to filter particulate matter from the air. Graphene oxide filters performed better than commercially available filters, effectively removing particulate matter from the air.
Read More...Modeling Energy Produced by Solar Panels
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.
Read More...The Effect of Bead Shape and Texture on the Energy Loss Characteristics in a Rotating Capsule
Industrial process are designed to optimize speed, energy use and quality. Some steps involve the translation of product-filled barrels, how far and fast this happens depends on the properties of the product within. This article investigates such properties on a mini-scale, where the roll of bead size, texture and material on the distance travelled by a cylindrical capsule is investigated.
Read More...Artificial Intelligence-Based Smart Solution to Reduce Respiratory Problems Caused by Air Pollution
In this report, Bhardwaj and Sharma tested whether placing specific plants indoors can reduce levels of indoor air pollution that can lead to lung-related illnesses. Using machine learning, they show that plants improved overall indoor air quality and reduced levels of particulate matter. They suggest that plant-based interventions coupled with sensors may be a useful long-term solution to reducing and maintaining indoor air pollution.
Read More...COVID-19 and air pollution in New York City
Did the COVID-19 pandemic and travel restrictions improve air quality? The authors investigate this question in New York City using existing pollution data and forecasting trends.
Read More...Developing a Portable, Reusable, and Inexpensive Magnesium-Air Fuel Cell
One of the greatest challenges we face today is the sustainable production, storage, and distribution of electrical power. One emerging technology with great promise in this area is that of metal-air fuel cells—a long-term and reusable electricity storage system made from a reactive metal anode and a saline solution. In this study the authors tested several different types of metal to determine which was the most suitable for this application. They found that a fuel cell with a magnesium anode was superior to fuel cells made from aluminum or zinc, producing a voltage and current sufficient for real-world applications such as charging a mobile phone.
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