Development of Processes and Catalysts for Biomass to Hydrocarbons at Moderate Conditions: A Comprehensive Review
Bibliographic record
Abstract
This comprehensive review explores recent catalyst advancements for the hydrodeoxygenation (HDO) of aromatic oxygenates derived from lignin, with a specific focus on the selective production of valuable aromatics under moderate reaction conditions. It addresses critical challenges in bio-crude oil upgrading, encompassing issues related to catalyst deactivation from coking, methods to mitigate deactivation, and techniques for catalyst regeneration. The study investigates various oxygenates found in bio-crude oil, such as phenol, guaiacol, anisole, and catechol, elucidating their conversion pathways during HDO. The review emphasizes the paramount importance of selectively generating arenes by directly cleaving C-O bonds while avoiding unwanted ring hydrogenation pathways. A comparative analysis of different bio-crude oil upgrading processes underscores the need to enhance biofuel quality for practical applications. Additionally, the review focuses on catalyst design for HDO. It compares six major catalyst categories, including metal sulfides, transition metals, metal phosphides, nitrides, carbides, and oxides, to provide insights for efficient bio-crude oil upgrading toward sustainable and eco-friendly energy alternatives.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".