Bisphosphonate Polymeric Ligands on Inorganic Nanoparticles
Bibliographic record
Abstract
The design and synthesis of anchoring groups of bisphosphonate-amine (BP-NH2) are presented for the preparation of polymeric ligands on luminescent nanoparticles (NPs). Such ligands serve as overcoatings to impart colloidal stability and conjugation chemistries. These ligands were placed on quantum dots (QDs), gold nanoparticles (AuNPs), gold nanourchins (AuNUs), and iron oxide NPs (IONPs). The BP-NH2 anchoring groups were coupled to copolymers comprised of amine-terminated poly(ethylene glycol) (NH2-PEG) and poly(isobutylene-alt-maleic anhydride) (PIMA) units via aza-Michael coupling. In all cases, polymer synthesis was done as a one-pot reaction of amine-containing precursors with PIMA. The BP-NH2 anchoring groups provided similar colloidal stability as monophosphonate-amine (MP-NH2) anchoring groups on AuNPs. QDs were found to be more optically stable when coated with BP-NH2 vs MP-NH2 functionalized polymers in high-ionic-strength buffers, such as 5× phosphate-buffered saline (PBS). The versatility of BP–PIMA–PEG as universal NP overcoating chemistry was demonstrated through successful application onto IONPs and AuNUs of various sizes (50, 60, 80, and 100 nm in diameter) via simple ligand exchange reactions. Polymers that were functionalized with azide groups were prepared as substrates suitable for copper-free click chemistry addition of alkyne dyes. Successful coupling of dyes to the azide-copolymer-coated nanoparticles was verified by spectroscopic investigations of near-field resonance energy transfer (RET) interactions. Thus, a series of surface coordinating polymers with affinity to multiple materials were synthesized that yielded nanoparticles exhibiting good colloidal stability and that were amenable to subsequent conjugation reactions.
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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) | 0.000 | 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) | 0.007 | 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".