Evidence map›Paper›PMID 24163499›Full record

ArticleMRS bulletin2013

Materials by Design-A Perspective From Atoms to Structures.

Markus J Buehler

Abstract read
In one paragraph

Article in MRS bulletin, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
  2. Localization of ZnSoft matter · 2023
    Article
  3. Silk fibroin microgels as a platform for cell microencapsulation.Journal of materials science. Materials in medicine · 2022
    Article
  4. Article
  5. Article
  6. Hybrid Spider Silk with Inorganic Nanomaterials.Nanomaterials (Basel, Switzerland) · 2020
    Review
  7. Sonification basedAPL bioengineering · 2020
    Article
  8. Review
  9. Review
  10. Article
  11. Silk-Its Mysteries, How It Is Made, and How It Is Used.ACS biomaterials science & engineering · 2015
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Markus J BuehlerLaboratory for Atomistic and Molecular Mechanics (LAMM), Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA 02139, USA.

Funding

Models to Predict Protein Biomaterial PerformanceU01EB014976 · NIBIB · TUFTS UNIVERSITY MEDFORD · PI BUEHLER, MARKUS J., KAPLAN, DAVID L. · 2012 to 2020
$5.2M
NIBIB NIH HHS U01 EB014976
6 · The paper itself

Abstract

Biological materials are effectively synthesized, controlled, and used for a variety of purposes-in spite of limitations in energy, quality, and quantity of their building blocks. Whereas the chemical composition of materials in the living world plays a some role in achieving functional properties, the way components are connected at different length scales defines what material properties can be achieved, how they can be altered to meet functional requirements, and how they fail in disease states and other extreme conditions. Recent work has demonstrated this by using large-scale computer simulations to predict materials properties from fundamental molecular principles, combined with experimental work and new mathematical techniques to categorize complex structure-property relationships into a systematic framework. Enabled by such categorization, we discuss opportunities based on the exploitation of concepts from distinct hierarchical systems that share common principles in how function is created, linking music to materials science.

Indexed as

bio-inspiredbiologydesignexperimentmanufacturingmateriomicsmusicnanomechanicsNanotechnologyproteinsimulationtheory

Identifiers

PMID24163499
PMCPMC3806500

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.