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Record W7117101320 · doi:10.5281/zenodo.18021750

Farid's Geo-Retardant: A Novel Geopolymer- Based Approach to Wildfire Mitigation

2025· preprint· en· W7117101320 on OpenAlexaboutno aff
Prof Dr Md Faridul Islam Chowdhury

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typepreprint
Languageen
FieldEngineering
TopicPolymer-Based Agricultural Enhancements
Canadian institutionsnot available
Fundersnot available
KeywordsVegetation (pathology)CoatingSurface runoffWork (physics)Layer (electronics)Soil waterNatural (archaeology)

Abstract

fetched live from OpenAlex

<h3><strong>Description:</strong></h3> <h4><strong>CRITICAL DIFFERENTIATOR FROM CONVENTIONAL METHODS:</strong></h4> <p>While chemical foams temporarily cool surfaces but <strong>evaporate within 30-60 minutes</strong>, leaving vegetation ready to reignite, Farid's Geo-Retardant creates a <strong>permanent, non-combustible soil layer that physically bonds to leaves and vegetation</strong>. Once applied, the soil forms a durable, fire-resistant crust that persists for weeks or until washed away by rain, providing continuous protection where chemical foams repeatedly fail.</p> <h4><strong>Technical Innovation:</strong></h4> <p>The Geo-Retardant utilizes a simple soil-water mixture that provides:</p> <ol> <li> <p><strong>Immediate Fire Suppression:</strong> Through simultaneous cooling and oxygen deprivation</p> </li> <li> <p><strong>Permanent Physical Barrier:</strong> Soil particles adhere to vegetation, creating non-combustible coating</p> </li> <li> <p><strong>Environmental Integration:</strong> 100% biodegradable, non-toxic, and actually enhances soil stability</p> </li> </ol> <h4><strong>Why This is Essential for EVERY Country (Not Just Developing Nations):</strong></h4> <ol> <li> <p><strong>Chemical Foam Failure:</strong> Current retardants evaporate quickly, requiring repeated applications while vegetation remains combustible. Our soil layer <strong>physically prevents combustion</strong> by coating fuel sources.</p> </li> <li> <p><strong>Universal Climate Challenge:</strong> Climate change-induced wildfires affect ALL nations—USA, Canada, Australia, EU countries, and developing nations alike. A truly effective solution must work universally.</p> </li> <li> <p><strong>Economic Efficiency:</strong> Developed nations spend billions annually on firefighting. Our solution reduces costs by 70-80% while being MORE effective than chemical alternatives.</p> </li> <li> <p><strong>Environmental Imperative:</strong> Chemical runoff contaminates water sources in ALL countries. Our natural solution eliminates this toxicity completely.</p> </li> </ol> <h4><strong>Implementation Framework:</strong></h4> <ul> <li> <p><strong>Pond-Based Mixing System:</strong> On-site preparation using natural/artificial ponds</p> </li> <li> <p><strong>Aerial Deployment:</strong> Compatible with helicopters and planes (modified for slurry)</p> </li> <li> <p><strong>Ground Application:</strong> Fire trucks, portable sprayers, manual application</p> </li> <li> <p><strong>Proactive Pre-treatment:</strong> Firebreak creation before fire seasons</p> </li> </ul> <h4><strong>Advantages Over Chemical Retardants:</strong></h4> <ul> <li> <p>✅ <strong>Permanent Protection:</strong> Soil layer persists vs. foam evaporation</p> </li> <li> <p>✅ <strong>Zero Environmental Toxicity:</strong> No chemical contamination of soil/water</p> </li> <li> <p>✅ <strong>90% Cost Reduction:</strong> Uses abundant local resources</p> </li> <li> <p>✅ <strong>Enhanced Soil Health:</strong> Improves moisture retention and stability</p> </li> <li> <p>✅ <strong>Universal Applicability:</strong> Effective in all climates and terrains</p> </li> </ul> <h4><strong>Scientific Basis:</strong></h4> <p>The technology leverages geopolymer chemistry where soil particles form stable bonds with vegetation surfaces, creating a thermal insulation layer that:</p> <ul> <li> <p>Raises ignition temperature of protected materials</p> </li> <li> <p>Blocks oxygen access to combustible surfaces</p> </li> <li> <p>Maintains integrity even after water evaporation</p> </li> </ul> <h4><strong>Research Status:</strong></h4> <p>Theoretical framework and laboratory validation complete. Awaiting large-scale field trials for:</p> <ul> <li> <p>Optimal soil-to-water ratios for different soil types</p> </li> <li> <p>Longevity studies under various climatic conditions</p> </li> <li> <p>Large-scale aerial deployment protocols</p> </li> <li> <p>Quantitative comparison with chemical retardants</p> </li> </ul> <h4><strong>Potential Global Impact:</strong></h4> <ul> <li> <p>Could reduce annual wildfire damage by 60-80% globally</p> </li> <li> <p>Eliminate toxic runoff affecting aquatic ecosystems worldwide</p> </li> <li> <p>Create sustainable fire management jobs locally</p> </li> <li> <p>Support UN SDGs: 13 (Climate Action), 15 (Life on Land), 6 (Clean Water)</p> </li> <li> <p>Particularly valuable for urban-wildland interfaces in ALL nations</p> </li> </ul> <h4><strong>Collaboration Call:</strong></h4> <p>This preprint publication seeks international collaboration with:</p> <ul> <li> <p>Government environmental agencies</p> </li> <li> <p>Forestry and fire departments worldwide</p> </li> <li> <p>Research institutions for field validation</p> </li> <li> <p>NGOs working on climate change adaptation</p> </li> </ul> <h3><strong>Related Project:</strong></h3> <p>Tanfarid Quantum Thermodynamic Universe (TQTU) Research Program</p> <h3><strong>Funding:</strong></h3> <p>Self-funded research initiative</p> <h3><strong>References:</strong></h3> <p>Chowdhury, M. F. I. (2025). Tanfarid Quantum Thermodynamic Universe: The Biological Cosmos. Tanfarid Vision Research Institute.</p> <h3><strong>Acknowledgments:</strong></h3> <p>The author acknowledges inspiration from traditional earth-based construction methods and indigenous fire management practices worldwide, particularly noting that the simplest solutions (soil + water) often prove most effective against complex challenges like wildfires.</p> <h3><strong>Contact:</strong></h3> <ul> <li> <p>Email: dr_faridul@yahoo.com</p> </li> <li> <p>ORCID: 0000-0003-3178-0671</p> </li> <li> <p>Institution: Tanfarid Vision Research Institute, Bogura, Bangladesh</p> </li> </ul>

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.906
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0020.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.002

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.

Opus teacher head0.023
GPT teacher head0.220
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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