Fischer–Tropsch synthesis with Co/SiO2–Al2O3 catalyst and steady-state modeling using artificial neural networks

Sharma, Bhagwati; Sharma, Mahendra P; Roy, S. K.; Kumar, Suresh; Tendulkar, Shilpa B.; Tambe, Sanjeev S.; Kulkarni, Bhaskar D.

doi:10.1016/s0016-2361(98)00110-0

Cited by 20 publications

(9 citation statements)

References 4 publications

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“…[37], all neural networks applied so far in materials research are of this type. [66][67][68][69][70][71] Figure 5 illustrates an example of a multilayer perceptron.…”

Section: Artifical Neural Networkmentioning

confidence: 99%

Combinatorial and High‐Throughput Materials Science

2007

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There is increasing acceptance of high-throughput technologies for the discovery, development, and optimization of materials and catalysts in industry. Over the years, the relative synchronous development of technologies for parallel synthesis and characterization has been accompanied by developments in associated software and information technologies. This Review aims to provide a comprehensive overview on the state of the art of the field by selected examples. Technologies developed to aid research on complex materials are covered as well as databases, design of experiment, data-mining technologies, modeling approaches, and evolutionary strategies for development. Different methods for parallel synthesis provide single sample libraries, gradient libraries for electronic or optical materials, similar to polymers and catalysts, and products produced through formulation strategies. Many examples illustrate the variety of isolated solutions and document the barely recognized variety of new methods for the synthesis and analysis of almost any material. The Review ends with a summary of success stories and statements on still-present problems and future tasks.

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“…[37], all neural networks applied so far in materials research are of this type. [66][67][68][69][70][71] Figure 5 illustrates an example of a multilayer perceptron.…”

Section: Artifical Neural Networkmentioning

confidence: 99%

Combinatorial and High‐Throughput Materials Science

2007

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“…The use of Co/SiO 2 -Al 2 O 3 (a mixed oxide) for FTS was performed by Sharma et al. (56) It was found that the optimal selectivity to C 5+ resulted.…”

Section: Metal Additive Modified Supportsmentioning

confidence: 99%

Co-Support Compound Formation in Alumina-Supported Cobalt Catalysts

Jongsomjit

Panpranot

Goodwin

2001

Journal of Catalysis

362

201

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“…So‐called multilayer perceptrons are the most common networks of the feed‐forward kind and, according to Ref. 37, all neural networks applied so far in materials research are of this type 66–71. Figure 5 illustrates an example of a multilayer perceptron.…”

Section: Computational Toolsmentioning

confidence: 99%

Vascular Access Simplified. A. H. Davies and C. P. Gibbons (eds). 148×209 mm. Pp. 246. Illustrated. 2007. tfm. Publishing Ltd: Shrewsbury. £30·00

Bockel

2007

British Journal of Surgery

View full text Add to dashboard Cite

There is increasing acceptance of high‐throughput technologies for the discovery, development, and optimization of materials and catalysts in industry. Over the years, the relative synchronous development of technologies for parallel synthesis and characterization has been accompanied by developments in associated software and information technologies. This Review aims to provide a comprehensive overview on the state of the art of the field by selected examples. Technologies developed to aid research on complex materials are covered as well as databases, design of experiment, data‐mining technologies, modeling approaches, and evolutionary strategies for development. Different methods for parallel synthesis provide single sample libraries, gradient libraries for electronic or optical materials, similar to polymers and catalysts, and products produced through formulation strategies. Many examples illustrate the variety of isolated solutions and document the barely recognized variety of new methods for the synthesis and analysis of almost any material. The Review ends with a summary of success stories and statements on still‐present problems and future tasks.

show abstract

Fischer–Tropsch synthesis with Co/SiO2–Al2O3 catalyst and steady-state modeling using artificial neural networks

Cited by 20 publications

References 4 publications

Combinatorial and High‐Throughput Materials Science

Combinatorial and High‐Throughput Materials Science

Co-Support Compound Formation in Alumina-Supported Cobalt Catalysts

Vascular Access Simplified. A. H. Davies and C. P. Gibbons (eds). 148×209 mm. Pp. 246. Illustrated. 2007. tfm. Publishing Ltd: Shrewsbury. £30·00

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