Assembly at the Nanoscale – Toward Functional Nanostructured Materials
Bibliographic record
Abstract
A fundamental challenge in the development of nanotechnology is the assembly of nanoscale building blocks into functional nanostructured materials. A symposium entitled “Assembly at the Nanoscale – Toward Functional Nanostructured Materials” was organized by Cengiz S. Ozkan (University of California, Riverside), Federico Rosei (University of Quebec, Canada), Gregory P. Lopinski (National Research Council, Canada), and Zhong L. Wang (Georgia Institute of Technology), and took place at the 2005 Materials Research Society (MRS) Fall Meeting in Boston, USA. The aim of the symposium was to bring together researchers from chemistry, physics, biology, surface science, and materials science to advance the progress being seen in the engineering of nanoscale assemblies. The scope of the symposium ranged from discussing the properties and characterization of novel nanostructured materials to developing functional multidimensional nanostructures, the applicability of which might range from the life sciences to device engineering. Topics of interest for the symposium were: Surface science studies of 1D and 2D supramolecular assemblies; Properties and applications of self-assembled 3D structures and nanostructures: photonic-bandgap materials, sensors, and nanocomposites; Novel fabrication methodologies: self-assembly strategies, biomimetics, and predictive approaches; Fundamental problems in quantum dots: growth (by self-assembly), physics, top-down fabrication (e.g., lithography, as well as other less conventional approaches); Unconventional approaches to patterning: soft lithography, embossing, dip-pen nanolithography, scanning probe lithography, and template-directed patterning; Organic/inorganic interfaces for molecular and nanoelectronic applications (see Figure 11 ); Nanoscale building blocks (see Figure 22 ) synthesized with colloidal particles, nanowires, nanotubes, quantum dots, block copolymers, and DNA. Electrical characterization data from a resonant tunneling diode based on conjugates of SWNT–ssDNA–SWNT (SWNT=single-walled carbon nanotube). The graph shows the measurement of negative differential resistance. The sketched model of the conjugate shows 9 bases of ssDNA between two conductive SWNTs used in the transfer function calculation. (Image provided by C S. Ozkan.) Novel nanostructures of ZnO synthesized by a solid–vapor-phase process. (Image provided by Z. L. Wang and R. S. Yang.) Overall, we received over 250 contributions for this symposium, and in addition, over a dozen invited talks were delivered by experts from around the world. This special section in this issue of Small includes papers authored by some of the invited speakers and the symposium organizers. The section includes work that is being carried out at the forefront of many of the fields that are listed above. We anticipate that this special issue, together with the proceedings published by the MRS, will provide a comprehensive coverage of current research in nanoscale assembly.
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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) | 0.000 | 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".