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Combining Finite Element and Machine Learning Methods to Predict Structures of Architectured Interlocking Ceramics
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/adem.200390016openalex-snapshot
Fracture Resistant Structures Based on Topological Interlocking with Non‐planar Contacts
inferredcites →https://doi.org/10.1002/adem.200700111openalex-snapshot
Indentation Behaviour of Interlocked Structures Made of Ice: Influence of the Friction Coefficient
inferredcites →https://doi.org/10.1002/adfm.202108492openalex-snapshot
Bioinspired Stochastic Design: Tough and Stiff Ceramic Systems
inferredcites →https://doi.org/10.1002/adma.201502403openalex-snapshot
Structural Design Elements in Biological Materials: Application to Bioinspiration
inferredcites →https://doi.org/10.1002/adma.201700060openalex-snapshot
Hierarchically Enhanced Impact Resistance of Bioinspired Composites
inferredcites →https://doi.org/10.1002/jcc.24764openalex-snapshot
Deep learning for computational chemistry
inferredcites →https://doi.org/10.1007/978-0-387-84858-7openalex-snapshot
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
inferredcites →https://doi.org/10.1007/978-3-319-07713-0_22openalex-snapshot
Drucker–Prager Criterion
inferredcites →https://doi.org/10.1016/j.actamat.2007.05.005openalex-snapshot
High-temperature mechanical behaviour of flaw tolerant alumina–zirconia multilayered ceramics
inferredcites →https://doi.org/10.1016/j.actbio.2014.03.022openalex-snapshot
Bio-inspired impact-resistant composites
inferredcites →https://doi.org/10.1016/j.applthermaleng.2022.118533openalex-snapshot
Thermal response analysis and parameter prediction of additively manufactured polymers
inferredcites →https://doi.org/10.1016/j.ceramint.2020.03.069openalex-snapshot
Deep and high precision cutting of alumina ceramics by picosecond laser
inferredcites →https://doi.org/10.1016/j.commatsci.2013.07.014openalex-snapshot
Indentation of interlocked assemblies: 3D discrete simulations and experiments
inferredcites →https://doi.org/10.1016/j.compscitech.2014.03.001openalex-snapshot
Numerical investigation of the impact behaviour of bioinspired nacre-like aluminium composite plates
inferredcites →https://doi.org/10.1016/j.conbuildmat.2022.127995openalex-snapshot
Influence of welding sequences on induced residual stress and distortion in pipes
inferredcites →https://doi.org/10.1016/j.csbj.2014.11.005openalex-snapshot
Machine learning applications in cancer prognosis and prediction
inferredcites →https://doi.org/10.1016/j.eml.2020.100844openalex-snapshot
Architectured ceramics with tunable toughness and stiffness
inferredcites →https://doi.org/10.1016/j.ijsolstr.2012.04.035openalex-snapshot
Transverse loading of cellular topologically interlocked materials
inferredcites →https://doi.org/10.1016/j.ijsolstr.2018.08.025openalex-snapshot
Toughness by segmentation: Fabrication, testing and micromechanics of architectured ceramic panels for impact applications
inferredcites →https://doi.org/10.1016/j.jmat.2017.08.002openalex-snapshot
Materials discovery and design using machine learning
inferredcites →https://doi.org/10.1016/j.jmp.2018.03.001openalex-snapshot
A tutorial on Gaussian process regression: Modelling, exploring, and exploiting functions
inferredcites →https://doi.org/10.1016/j.jmrt.2022.04.039openalex-snapshot
A novel systematic numerical approach on determination of heat source parameters in welding process
inferredcites →https://doi.org/10.1016/j.matdes.2019.107627openalex-snapshot
Multilayered architectured ceramic panels with weak interfaces: energy absorption and multi-hit capabilities
inferredcites →https://doi.org/10.1016/j.optlastec.2020.106669openalex-snapshot
Engineered net shaping of alumina ceramics using picosecond laser
inferredcites →https://doi.org/10.1016/j.pmatsci.2007.05.002openalex-snapshot
Biological materials: Structure and mechanical properties
inferredcites →https://doi.org/10.1016/s0263-8223(02)00053-3openalex-snapshot
Post-buckling optimisation of composite stiffened panels using neural networks
inferredcites →https://doi.org/10.1016/s0266-3538(03)00106-4openalex-snapshot
Artificial neural networks applied to polymer composites: a review
inferredcites →https://doi.org/10.1021/ar400279topenalex-snapshot
Bioinspired Layered Materials with Superior Mechanical Performance
inferredcites →https://doi.org/10.1038/s41598-021-84637-4openalex-snapshot
Potential neutralizing antibodies discovered for novel corona virus using machine learning
inferredcites →https://doi.org/10.1038/srep02810openalex-snapshot
Accelerating materials property predictions using machine learning
inferredcites →https://doi.org/10.1038/srep11551openalex-snapshot
A predictive machine learning approach for microstructure optimization and materials design
inferredcites →https://doi.org/10.1039/c8mh00653aopenalex-snapshot
Bioinspired hierarchical composite design using machine learning: simulation, additive manufacturing, and experiment
inferredcites →https://doi.org/10.1073/pnas.1807272115openalex-snapshot
Simultaneous improvements of strength and toughness in topologically interlocked ceramics
inferredcites →https://doi.org/10.1088/1402-4896/aca3daopenalex-snapshot
Machine learning-driven process of alumina ceramics laser machining
inferredcites →https://doi.org/10.1111/jace.13697openalex-snapshot
Thermal Shock Resistance of Laminated ZrB 2 –SiC Ceramic Evaluated by Indentation Technique
inferredcites →https://doi.org/10.1148/rg.2017160130openalex-snapshot
Machine Learning for Medical Imaging
inferredcites →https://doi.org/10.4028/www.scientific.net/amr.47-50.125openalex-snapshot
Experiments and Numerical Simulations of Interlocked Materials
inferredcites →https://doi.org/10.4028/www.scientific.net/kemopenalex-snapshot
Key Engineering Materials
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/adem.202400792openalex-snapshot
Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics
inferred← citeshttps://doi.org/10.1002/adem.202500297openalex-snapshot
From Nature to Engineering: Mortar Volume and Interfacial Mechanics in Bioinspired Ceramics
inferred← citeshttps://doi.org/10.1007/s10338-023-00420-0openalex-snapshot
Accelerating Optimization Design of Bio-inspired Interlocking Structures with Machine Learning
inferred← citeshttps://doi.org/10.1016/j.engappai.2025.111937openalex-snapshot
Machine learning-optimized stochastic Voronoi lattices for enhanced mechanical performance
inferred← citeshttps://doi.org/10.1016/j.jeurceramsoc.2024.03.035openalex-snapshot
Digital precision in engineered ceramics: Tailoring toughness and flexibility through interlocking strategies
inferred← citeshttps://doi.org/10.1088/1361-651x/ad073aopenalex-snapshot
Designing architectured ceramics for transient thermal applications using finite element and deep learning
inferred← citeshttps://doi.org/10.3390/ma17215305openalex-snapshot
A Novel Triad of Bio-Inspired Design, Digital Fabrication, and Bio-Derived Materials for Personalised Bone Repair
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