Review and environmental footprint assessment of various formalin production pathways

Puhar, Jan; Krajnc, Damjan; Čuček, Lidija; Vujanović, Annamaria

doi:10.1016/j.jclepro.2022.134537

Cited by 7 publications

(2 citation statements)

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“…41 This technology is implemented in a process called the CAMERE process, which has a TRL of 6-7. 42,43 Depending on the desired syngas ratio, a syngas production method can be selected. For example, an H 2 : CO ratio of 2 : 1 is needed to synthesize Fischer-Tropsch products using cobalt-based catalysts, 44 suggesting POX or RWGS to be the most suitable syngas production methods.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the techno-economic potential of defossilized air-to-syngas pathways

Almajed,

Guerra,

Smith

et al. 2023

Energy Environ. Sci.

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Section: Introductionmentioning

confidence: 99%

Evaluating the techno-economic potential of defossilized air-to-syngas pathways

Almajed,

Guerra,

Smith

et al. 2023

Energy Environ. Sci.

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“…From a scientific and practical point of view, R&D products' readiness, as a basis for estimating their value, is the subject of much debate. Several researchers in the field [6,7] consider readiness from the technological maturity of products. Others [8][9][10] propose substantiating the readiness indicator by modeling the achieved level of satisfaction of R&D products with market needs (marketing, legal, social readiness, etc.).…”

Section: Introductionmentioning

confidence: 99%

Stacking Machine Learning Model for the Assessment of R&D Product’s Readiness and Method for Its Cost Estimation

et al. 2022

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The modern technology universities have the necessary resource and material base for developing and transferring R&D products. However, the cost estimation process is not formalized. There are many methods of estimating the cost of R&D products’ commercialization processes. However, in some cases, we cannot consider any single technique to be the best one as each of them has advantages and disadvantages. In such conditions, all efforts should be made to use a combination of the estimation techniques to arrive at a better cost and quality estimate. The effectiveness of the valuation of R&D products is of particular importance in today’s economy and due to the need to analyze large data sets prepared for transfer from universities to the business environment. This paper presents the model, two methods, and general information technology for R&D products’ readiness level assessment and R&D products’ cost estimation. The article presents the complex method for determining the cost of R&D products, which will allow: increasing the efficiency of the transfer, commercialization, and market launch of R&D products, and promoting the interaction of all components of the national innovation infrastructure, innovations, etc. The need to consider many different indicators when evaluating R&D products has determined the need to use machine learning algorithms. We have designed a new machine learning-based model for the readiness assessment of R&D products, which is based on the principle of “crowd wisdom” and uses a stacking strategy to integrate machine learning methods. It is experimentally established that the new stacking model based on machine learning algorithms that use random forest as a meta-algorithm provides a minimum of a 1.03 times higher RMSE compared to other ensemble strategies.

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