Carbodiimide/NHS Derivatization of COOH-Terminated SAMs: Activation or Byproduct Formation?
Bibliographic record
Abstract
COOH-terminated self-assembled monolayers (SAMs) are widely used in biosensor technology to bind different amine-containing biomolecules. A covalent amide bond, however, can be achieved only if the carboxylic acids are activated. This activation process usually consists of forming an N-hydroxysuccinimidyl ester (NHS-ester) by consecutively reacting carboxylic acids with a carbodiimide and NHS. Though many papers report using this method,1-8 the experimental conditions vary greatly between them and chemical characterization at this stage is often omitted. Evidence of an efficient activation is therefore rarely shown. Furthermore, recent publications9-11 have highlighted the complexity of this process, with the possible formation of different byproducts. In this paper, we have conducted a study on NHS activation under different conditions with chemical characterization by polarization-modulation infrared reflection-absorption spectroscopy (PM-IRRAS) and time-of-flight secondary ion mass spectroscopy (ToF-SIMS). Our results indicate that the nature of the solvent and carbodiimide and the reactant concentrations play crucial roles in activation kinetics and efficiency.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".