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Record W4388199401 · doi:10.1002/ppsc.202300080

Templated Droplet Evaporation‐Based Supraparticles in Environmental Applications

2023· article· en· W4388199401 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueParticle & Particle Systems Characterization · 2023
Typearticle
Languageen
FieldEngineering
TopicNanomaterials and Printing Technologies
Canadian institutionsUniversity of Alberta
FundersScience and Engineering Research BoardDepartment of Science and Technology, Ministry of Science and Technology, IndiaUniversity of Alberta
KeywordsNanotechnologyEvaporationMaterials scienceBiochemical engineeringComputer scienceEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract Designing of innovative technologies for the development of functional materials remain crucial for achieving sustainable technological advancements. In this regard, nanoparticles (NPs) possessing enormous potential properties can be obtained using various facile methods for several applications. Adopting NPs as primitive building blocks can initiate the formation of complex entities named supraparticle (SP) to create several advanced functional materials. Additionally, SPs enable entirely new material characteristics to the system, owing to their individual entities, intrinsic properties such as coupling, spatial arrangement, and co‐localization. Indeed, methods such as template‐induced evaporation‐based assembly of NPs direct the shape, size, and morphology of SPs from their respective colloidal dispersions on a solvent‐repellant solid surface. Therefore, it is important to comprehend the formation of SPs and their structure‐property relationship with respect to practical application. This review presents a brief overview of SPs assembly by outlining the templated‐assisted evaporation‐based methodologies for synthesizing SPs. Further, the effect of various factors on the interaction between colloidal entities, solvent, and substrate, leading to the genesis of SPs is elaborated. Conclusively, specific properties are described and applications of SPs for energy storage, generation, and environmental remediation are reported, which collectively brings many interdisciplinary research fields to the same podium.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.538
Threshold uncertainty score0.907

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.015
GPT teacher head0.211
Teacher spread0.196 · 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