Organizing Data for Energy Research Memo
At this time, you should have completed your data collection for the project. Organize your data into a professionally formatted spreadsheet or spreadsheets, and then provide a final verbal “snapshot” of your data in an Engineering Memo:
- What kind of data is it? (spatial, temporal, multivariate, verbal, etc.) (1-3 sentences)
- How much data do you have? (how many variables, how many columns, rows) (1-3 sentences)
- Why is this amount of data necessary? (3-5 sentences)
- Describe the physical meanings of each of the data types by row and column (for example “column one contains reactor temperature measurements as a function of time …the first ten rows of data contain individual experimental results….”) (use as many sentences as you need)
- Append the full dataset to your memo as a spreadsheet.
Subject: Database Selection for Research on Advanced Materials for Energy Storage and Electric Vehicles
I will examine the database of new electric vehicles and energy storage materials. ,This article analyzes the database and its use in research. Access to a multidisciplinary resource with well-organized material was helpful when choosing a database. The goal is to select databases with high-quality scientific papers and publications and strategically use them to offer relevant information to targeted queries.
Database Selection and Relevance
After careful evaluation, I chose Elsevier’s ScienceDirect database for my study for numerous reasons. First and foremost, the database contains publications from top journals, including “Energy Storage Materials” by Tie et al., “Advanced Technologies for Energy Storage and Electric Vehicles” by Salkuti, and “Advanced Materials for Energy Storage Devices” by Hone and El Ganaoui. These sources explain energy storage, materials, and electric vehicle breakthroughs, and ScienceDirect tackles challenging issues with a broad perspective. I employ electrochemistry, material science, and renewable energy publications from the collection to find diverse perspectives and solutions for the industry. ScienceDirect offers much information regarding energy storage and electric car dimensions, which I appreciate. The database includes fundamental material characteristics, electrochemical parameters, and device performance indicators for research and study.
Type of Data
The sources give the data at microscopic and mesoscopic scales as well. At the macro level, trends, integrating renewable energies into electrical grids, sustainability, and environmental engineering. They follow global or regional policies, energy market dynamics, grid upgrading, etc. According to Hone et al. (2021) and Tie (2019), mesoscopic-scale research is between atomic and macroscopic scales.
Scientific and industrial frameworks led by physicists, engineers, electrochemists, and material scientists underpin all these studies. Renewable energy integration, utility grid modernization, and environmental sustainability are considered while implementing energy storage and electric car technology. These sources provide qualitative and quantitative data. Material content, crystal structure, device settings, and market trends are qualitative data. Market evaluation (investment trend, growth predictions), device performance indicators (voltage profiles, charge-discharge rates), and material attributes are quantitative data. APA