Skip to content

Author

Wilhelm Huck

1 paper indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

#large language models Dataset Open access Sep 2026

BigMixSolDB: Extraction of a solubility database in solvent mixtures with an uncertainty-quantified large language model-based pipeline

Supplementary material for the publication "BigMixSolDB: Extraction of a solubility database in solvent mixtures with an uncertainty-quantified large language model-based pipeline". This Zenodo record contains the data and supporting materials for BigMixSolDB, a workflow for extracting experimental solubility data from scientific PDFs. The archive provides the final standardized datasets generated with Docling- and vision-language-model (VLM)-based document-conversion pipelines, curated molecule dictionaries, corpus-screening and deduplication records, model-evaluation outputs, extraction prompts and requests, per-article extraction outputs, and a source-code snapshot. Together, these materials support inspection and reproduction of the extraction, post-processing, filtering, and evaluation procedures described in the accompanying publication. The Docling-derived dataset is the primary BigMixSolDB release because this pipeline achieved the strongest structural coverage and chemical-identity matching in the manuscript benchmarks. The VLM-derived dataset is provided as a complementary output for methodological comparison. Files BigMixSolDB_code.zip: Snapshot of the source code and workflow used to generate, standardize, filter, deduplicate, and evaluate the deposited datasets. The actively maintained repository is also available on GitHub. bigmixsoldb_docling.csv: Final standardized and deduplicated Docling-derived BigMixSolDB dataset. This is the primary curated dataset described in the publication and contains 280,161 retained solubility records from 2,150 represented source DOIs. bigmixsoldb_vlm.csv: Final standardized and deduplicated VLM-derived dataset, containing 231,936 retained records from 2,067 source DOIs. This file is supplied as a complementary pipeline output and methodological comparison rather than as the primary BigMixSolDB release. bigmixsoldb_docling_duplicates.csv and bigmixsoldb_vlm_duplicates.csv: Reports of duplicate groups identified during within- and cross-DOI deduplication. The procedure accounts for normalized pressure, equivalent pressures within 2%, and constrained differences in reported decimal precision. bigmixsoldb_docling_unfiltered.csv and bigmixsoldb_vlm_unfiltered.csv: Unfiltered datasets resulting from parsing the YAML outputs generated by the large language model. doi_counts.csv: Per-DOI comparison of retained coverage in BigMixSolDB against BigSolDB 2.0 and MixtureSolDB. dois.csv: List of publication DOIs retrieved during construction of the BigMixSolDB corpus. excluded_solute_names.txt and excluded_solvent_names.txt: Curated lists of compound names excluded by the molecular-scope filters. extracted_docling.zip and extracted_vlm.zip: Archives of the per-article structured extraction outputs generated with the Docling- and VLM-based pipelines, respectively. These broader extraction outputs are retained to support auditing and alternative downstream filtering. model_evaluation.zip: Validation- and test-set model-evaluation materials used to calculate the precision, recall, and F1 values reported in Table 1 of the publication. The archive contains model outputs, standardized reference and prediction CSV files, per-document error results, aggregate error summaries, and the evaluation prompts for the evaluated proprietary, open-weight, and fine-tuned models. name_to_smiles_docling.json and name_to_smiles_vlm.json: Curated molecule dictionaries used to assign and validate molecular structures in the respective pipelines. These files preserve compound-level provenance and permit users to apply alternative scope criteria. prompt_extraction.txt: Prompt template used to extract structured solubility records from converted document content. prompt_training.txt: Prompt template used in model fine-tuning. removed_dois.txt: Source DOIs excluded during article-level screening because they did not report in-scope experimental molecular solubility or solid-liquid-equilibrium data. requests_docling.jsonl and requests_vlm.jsonl: Batch request records for the Docling- and VLM-based extraction runs, respectively. The final CSV files report temperature in Kelvin and reported pressure in Pascal. Solubility is expressed in fraction-based units, and solvent composition is expressed as mole or mass fraction. A blank pressure denotes that pressure was not explicitly available to the extraction pipeline or present in the source article. The "Requires Review" field is a conservative indicator of potentially difficult source formatting or extraction ambiguity and should not be interpreted as evidence that a record is incorrect. Users should apply additional compound- or task-specific filters where required by their downstream application. Changelog Version 4 This version updates the two final datasets and their respective name-to-SMILES dictionaries. - Canonicalized the curated SMILES in both extraction tracks before generating the deposited CSV files. This changed 141 entries in the Docling name-to-SMILES mapping and 122 entries in the VLM mapping. The revised Docling dataset now has 334 unique non-empty values in both `Solvent 1` and `SMILES_Solvent_1`. - Added normalized compound display names for downstream name-based grouping while retaining the original extracted `Compound Name` values for provenance. - Audited the ternary subset and removed records in which phase-forming solids had been represented as inert solvents or the solute fraction had been folded incorrectly into an inferred third-solvent fraction. The Docling dataset removes 67 rows from DOI `10.1016/j.jct.2017.03.008`, 30 affected rows from DOI `10.1016/j.jct.2025.107514`, and 15 affected rows from DOI `10.1021/je201047m`, for a total of 112 removed rows. The corresponding VLM dataset removes 167 rows across the same three sources. Unaffected records from the latter two sources remain. The final Docling-derived release contains 280,161 records from 2,150 represented source DOIs and 1,668 unique solutes. It comprises 115,203 single-solvent, 161,921 binary-solvent, and 3,037 ternary-solvent records. The binary subset spans 834 unique solvent pairs and 3,352 unique solute-solvent mixture systems. The ternary subset spans 120 unique solvent triples and 146 unique solute-solvent mixture systems. Thus, the binary and ternary subsets together contain 3,498 unique solute-solvent mixture systems. The complementary final VLM-derived release contains 231,936 records from 2,067 represented source DOIs. Version 3 This version updates the deposited data and supporting materials to correspond to the final filtering, deduplication, nomenclature, and evaluation procedures reported in the manuscript. Regenerated both standardized datasets after source-level screening and revised molecular-scope filtering. The curated release is restricted to experimental solubility and solid-liquid-equilibrium measurements for molecular solutes in molecular solvent systems. Papers reporting only liquid-liquid equilibrium, partitioning, extraction efficiency, binodal or cloud-point data, purely computational results, or no original experimental solubility data were excluded. Removed 247 out-of-scope source DOIs before extraction and excluded 17,006 Docling-derived rows under the molecular-scope criteria, including inorganic salt systems and ionic compounds used as solvent components. Added pressure- and precision-aware within- and cross-DOI deduplication. This reduced the filtered Docling dataset from 278,688 to 274,885 rows by removing 4,204 duplicate rows, of which 4,105 were associated with cross-DOI groups and 99 with within-DOI groups. Standardized solvent text fields to one canonical display name per structure-defined solvent identity. Curated common names are used where available and deterministic frequency-based names otherwise. Updated the curated molecule JSON files. The revised records include source DOI provenance, solute or solvent role, molecule type, inclusion status, and structure-retrieval and human-validation metadata. Added the model-evaluation files used to generate the model-comparison results in Table 1, including the validation and test outputs, standardized reference/prediction tables, and aggregate error summaries. Uploaded the duplicate reports and updated DOI coverage information, exclusion lists, and source-screening records to match the regenerated datasets. In this version, the Docling dataset contains 280,273 records from 2,151 represented source DOIs. This comprises of 115,203 single-solvent, 161,921 binary-solvent, and 3,149 ternary-solvent records, with 1,676 unique solutes, 345 unique solvents, 839 binary solvent systems, and 124 ternary solvent systems. Version 2 This version updated the Zenodo repository to match the post-processed and filtered BigMixSolDB release described in the preceding manuscript revision. Replaced the preliminary dataset files with the final filtered Docling-derived BigMixSolDB release containing 299,211 retained solubility entries from 2,301 source DOIs. Corrected the `review_required` flag, which had previously been incorrectly set to `False` for all rows in the deposited dataset. Standardized retained temperature, pressure, solubility, and solvent-composition units. Temperatures are reported in Kelvin, reported pressures in Pascal, solubilities and solvent compositions in fraction-based units. Manually curated solute and solvent name-to-SMILES mappings, corrected erroneous molecular identifiers, resolved ambiguous assignments, and removed rows with missing or invalid required SMILES. The raw extracted dataset can be found in `bigmixsoldb_docling_unfiltered.csv`. A list of molecules that were omitted in our dataset can be found in `excluded_solute_names.txt` and `excluded_solvents.txt`. Post-processing steps and filtering the molecules found in the aforementioned TXT files gives the final dataset present in `bigmixsoldb_docling.csv`. Applied final s

Andrei Voinea, Chiara Thöni, Elija Veenman et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.