A review on clean energy solutions for better sustainability
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper focuses on clean energy solutions in order to achieve better sustainability, and hence discusses opportunities and challenges from various dimensions, including social, economic, energetic and environmental aspects. It also evaluates the current and potential states and applications of possible clean-energy systems. In the first part of this study, renewable and nuclear energy sources are comparatively assessed and ranked based on their outputs. By ranking energy sources based on technical, economic, and environmental performance criteria, it is aimed to identify the improvement potential for each option considered. The results show that in power generation, nuclear has the highest (7.06/10) and solar photovoltaic (PV) has the lowest (2.30/10). When nonair pollution criteria, such as land use, water contamination, and waste issues are considered, the power generation ranking changes, and geothermal has the best (7.23/10) and biomass has the lowest performance (3.72/10). When heating and cooling modes are considered as useful outputs, geothermal and biomass have approximately the same technical, environmental, and cost performances (as 4.9/10), and solar has the lowest ranking (2/10). Among hydrogen production energy sources, nuclear gives the highest (6.5/10) and biomass provides the lowest (3.6/10) in ranking. In the second part of the present study, multigeneration systems are introduced, and their potential benefits are discussed along with the recent studies in the literature. It is shown that numerous advantages are offered by renewable energy-based integrated systems with multiple outputs, especially in reducing overall energy demand, system cost and emissions while significantly improving overall efficiencies and hence output generation rates. Copyright © 2015 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it