ArticleInternational journal of solids and structures2019
Parameters controlling the strength of stochastic fibrous materials.
Article in International journal of solids and structures, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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.
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.
Who cites it
13 citing papers in PubMed.
- Virtual testing methodology to predict the mechanical behavior of collagen hydrogels from nanoarchitecture.Materials today. Bio · 2025Article
- Failure mechanism in stochastic network materials: the competition between fiber and crosslink failure.International journal of solids and structures · 2025Article
- Rupture mechanics of blood clots: Influence of fibrin network structure on the rupture resistance.Acta biomaterialia · 2024Article
- Microstructural Evolution and Failure in Fibrous Network Materials: Failure Mode Transition from the Competition between Bond and Fiber.Materials (Basel, Switzerland) · 2024Article
- Gradient porous structures of mycelium: a quantitative structure-mechanical property analysis.Scientific reports · 2023Article
- Biomechanics, Energetics, and Structural Basis of Rupture of Fibrin Networks.Advanced healthcare materials · 2023Article
- Toughness of Network Materials: Structural Parameters Controlling Damage Accumulation.Journal of the mechanics and physics of solids · 2023Article
- Humidity dependence of fracture toughness of cellulose fibrous networks.Engineering fracture mechanics · 2022Article
- Sharing the Load: Stress Redistribution Governs Fracture of Polymer Double Networks.Macromolecules · 2021Article
- Strength and deformability of fibrin clots: Biomechanics, thermodynamics, and mechanisms of rupture.Acta biomaterialia · 2021Article
- Percolation of collagen stress in a random network model of the alveolar wall.Scientific reports · 2021Article
- Strength of stochastic fibrous materials under multiaxial loading.Soft matter · 2021Article
- Random Fiber Networks With Superior Properties Through Network Topology Control.Journal of applied mechanics · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Many materials of everyday use are fibrous and their strength is important in most applications. In this work we study the dependence of the strength of random fiber networks on structural parameters such as the network density, cross-link density, fiber tortuosity, and the strength of the inter-fiber cross-links. Athermal networks of cellular and fibrous type are considered. We conclude that the network strength scales linearly with the cross-link number density and with the cross-link strength for a broad range of network parameters, and for both types of networks considered. Network strength is independent of fiber material properties and of fiber tortuosity. This information can be used to design fiber networks for specified strength and, generally, to understand the mechanical behavior of fibrous materials.
Identifiers
What OpenQuestion holds
Registered trials
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.