Materials informatics

Rajan, Krishna

doi:10.1016/s1369-7021(05)71123-8

Cited by 390 publications

(264 citation statements)

References 34 publications

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“…Second, the data sets, features, and prior knowledge in condensed matter systems are significantly smaller than those available to biology and health, communication networks, and finance, where big data science dominates. One therefore needs to consider nuances in the informatics methods for materials science data [58][59][60] and whether the "correct" questions are asked about the data. 61 Black-box application of machine-learning algorithms to small data sets without careful data cleaning and feature selection could also lead to further complexity and minimal understanding of the underlying structure.…”

Section: -3mentioning

confidence: 99%

Research Update: Towards designed functionalities in oxide-based electronic materials

2015

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Section: -3mentioning

confidence: 99%

Research Update: Towards designed functionalities in oxide-based electronic materials

2015

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“…However, informatics-based design using computational intelligence techniques have been successfully used for designing Ti alloys [26][27] and other materials [28][29][30]. Informatics based materials design strategies try to extract the inherent correlation within data and utilize the information for designing novel materials [31]. Statistical as well as computational intelligence based techniques have the capacity to use data as well as imprecise knowledge (expert-knowledge) of a system and derive a model of the system that has the capability to generalise behaviour over a wide range of parameter variability.…”

Section: Introductionmentioning

confidence: 99%

Imprecise knowledge based design and development of titanium alloys for prosthetic applications

Datta

Mahfouf

Zhang

et al. 2016

Journal of the Mechanical Behavior of Biomedical Materials

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Sultana, N. (2015) Imprecise knowledge based design and development of titanium alloys for prosthetic applications.Journal Abstract Imprecise knowledge on the composition-processing-microstructure-property correlation of titanium alloys combined with experimental data are used for developing rule based models for predicting the strength and elastic modulus of titanium alloys. The developed models are used for designing alloys suitable for orthopaedic and dental applications. Reduced Space Searching Algorithm is employed for the multi-objective optimization to find composition, processing and microstructure of titanium alloys suitable for orthopaedic applications. The conflicting requirements attributes of the alloys for this particular purpose are high strength with low elastic modulus, along with adequate biocompatibility and low costs. The 'Pareto' solutions developed through multi-objective optimization show that the preferred compositions for the fulfilling the above objectives lead to β or near β alloys. The concept of decision making employed on the solutions leads to some compositions, which should provide better combination of the required attributes. The experimental development of some of the alloys has been carried out as guided by the model-based design methodology ©2015. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ 2 presented in this research. Primary characterizations of the alloys show encouraging results in terms of the mechanical properties.

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“…For example, quantum-mechanics-based calculation tools are routinely used in the development of structural metals and semiconductors, among other materials [21]. Increasingly, these computational processes are based on new machine learning methods to construct rich models of materials properties [22][23][24]. With such changes, researchers are increasingly in need of new methods for publishing not only references to the data used to derive results but also the models and computational processes that underpin results.…”

Section: Materials Sciencementioning

confidence: 99%