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Article: Quantifying the Separation Complexity of Mixed Plastic Waste Streams with Statistical Entropy: A Plastic Packaging Waste Case Study in Belgium

Nimmegeers, Philippe / Billen, Pieter

ACS sustainable chemistry & engineering. 2021 July 15, v. 9, no. 29

2021

Abstract: Mixed plastic waste streams are to date present in nearly all societies. Depending on the source of the plastic waste stream, the complexity and difficulty to separate and recycle the waste stream differs. In this paper, the concept of statistical ... ...

Abstract	Mixed plastic waste streams are to date present in nearly all societies. Depending on the source of the plastic waste stream, the complexity and difficulty to separate and recycle the waste stream differs. In this paper, the concept of statistical entropy is used to quantify the separation complexity of mixed plastic waste streams. To this end, the recently proposed multilevel statistical entropy analysis method is extended by adding a multiproduct system level. Furthermore, an overview is presented of the research questions that can be addressed by different statistical entropy definitions. The proposed extended method is applied to a plastic packaging waste case study in Belgium for which the data are available in the literature. The results indicate that the method based on statistical entropy allows analyzing the separation complexity of real-life mixed plastic waste streams. More specifically, the multilayer films contribute the most to the separation complexity of the studied plastic packaging waste stream. In addition, it is illustrated how the method can be used to identify key contributors to the separation complexity of mixed plastic waste streams and to evaluate measures to reduce the separation complexity of mixed plastic waste streams.
Keywords	case studies ; entropy ; green chemistry ; plastics ; Belgium
Language	English
Dates of publication	2021-0715
Size	p. 9813-9822.
Publishing place	American Chemical Society
Document type	Article
ISSN	2168-0485
DOI	10.1021/acssuschemeng.1c02404
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Hybrid Prediction-Driven High-Throughput Sustainability Screening for Advancing Waste-to-Dimethyl Ether Valorization.

Fozer, Daniel / Nimmegeers, Philippe / Toth, Andras Jozsef / Varbanov, Petar Sabev / Klemeš, Jiří Jaromír / Mizsey, Peter / Hauschild, Michael Zwicky / Owsianiak, Mikołaj

Environmental science & technology

2023 Volume 57, Issue 36, Page(s) 13449–13462

Abstract: Assessing the prospective climate preservation potential of novel, innovative, but immature chemical production techniques is limited by the high number of process synthesis options and the lack of reliable, high-throughput quantitative sustainability ... ...

Abstract	Assessing the prospective climate preservation potential of novel, innovative, but immature chemical production techniques is limited by the high number of process synthesis options and the lack of reliable, high-throughput quantitative sustainability pre-screening methods. This study presents the sequential use of data-driven hybrid prediction (ANN-RSM-DOM) to streamline waste-to-dimethyl ether (DME) upcycling using a set of sustainability criteria. Artificial neural networks (ANNs) are developed to generate
MeSH term(s)	Prospective Studies ; Climate ; High-Throughput Screening Assays ; Methyl Ethers ; Sewage
Chemical Substances	dimethyl ether (AM13FS69BX) ; Methyl Ethers ; Sewage
Language	English
Publishing date	2023-08-29
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1520-5851
ISSN (online)	1520-5851
DOI	10.1021/acs.est.3c01892
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Comparing design of experiments and optimal experimental design techniques for modelling the microbial growth rate under static environmental conditions.

Akkermans, Simen / Nimmegeers, Philippe / Van Impe, Jan F

Food microbiology

2018 Volume 76, Page(s) 504–512

Abstract: Building secondary models that describe the growth rate as a function of multiple environmental conditions is often very labour intensive and costly. As such, the current research aims to assist in decreasing the required experimental effort by studying ... ...

Abstract	Building secondary models that describe the growth rate as a function of multiple environmental conditions is often very labour intensive and costly. As such, the current research aims to assist in decreasing the required experimental effort by studying the efficacy of both design of experiments (DOE) and optimal experimental designs (OED) techniques. This is the first research in predictive microbiology (i) to make a comparison of these techniques based on the (relative) model prediction uncertainty of the obtained models and (ii) to compare OED criteria for the design of experiments with static (instead of dynamic) environmental conditions. A comparison of the DOE techniques demonstrated that the inscribed central composite design and full factorial design were most suitable. Five conventional and two tailor made OED criteria were tested. The commonly used D-criterion performed best out of the conventional designs and almost equally well as the best of the dedicated criteria. Moreover, the modelling results of the D-criterion were less dependent on the experimental variability and differences in the microbial response than the two selected DOE techniques. Finally, it was proven that solving the optimisation of the D-criterion can be made more efficient by considering the sensitivities of the growth rate relative to its value as Jacobian matrix instead of the sensitivities of the cell density measurements.
MeSH term(s)	Bacteria/chemistry ; Bacteria/growth & development ; Kinetics ; Models, Biological ; Research Design
Language	English
Publishing date	2018-06-07
Publishing country	England
Document type	Comparative Study ; Journal Article
ZDB-ID	50892-5
ISSN	1095-9998 ; 0740-0020
ISSN (online)	1095-9998
ISSN	0740-0020
DOI	10.1016/j.fm.2018.05.010
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: A tutorial on uncertainty propagation techniques for predictive microbiology models: A critical analysis of state-of-the-art techniques.

Akkermans, Simen / Nimmegeers, Philippe / Van Impe, Jan F

International journal of food microbiology

2018 Volume 282, Page(s) 1–8

Abstract: Building mathematical models in predictive microbiology is a data driven science. As such, the experimental data (and its uncertainty) has an influence on the final predictions and even on the calculation of the model prediction uncertainty. Therefore, ... ...

Abstract	Building mathematical models in predictive microbiology is a data driven science. As such, the experimental data (and its uncertainty) has an influence on the final predictions and even on the calculation of the model prediction uncertainty. Therefore, the current research studies the influence of both the parameter estimation and uncertainty propagation method on the calculation of the model prediction uncertainty. The study is intended as well as a tutorial to uncertainty propagation techniques for researchers in (predictive) microbiology. To this end, an in silico case study was applied in which the effect of temperature on the microbial growth rate was modelled and used to make simulations for a temperature profile that is characterised by variability. The comparison of the parameter estimation methods demonstrated that the one-step method yields more accurate and precise calculations of the model prediction uncertainty than the two-step method. Four uncertainty propagation methods were assessed. The current work assesses the applicability of these techniques by considering the effect of experimental uncertainty and model input uncertainty. The linear approximation was demonstrated not always to provide reliable results. The Monte Carlo method was computationally very intensive, compared to its competitors. Polynomial chaos expansion was computationally efficient and accurate but is relatively complex to implement. Finally, the sigma point method was preferred as it is (i) computationally efficient, (ii) robust with respect to experimental uncertainty and (iii) easily implemented.
MeSH term(s)	Algorithms ; Bacteria/chemistry ; Bacteria/growth & development ; Computer Simulation ; Microbiological Techniques/standards ; Models, Theoretical ; Monte Carlo Method
Language	English
Publishing date	2018-05-29
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	87122-9
ISSN	1879-3460 ; 0168-1605
ISSN (online)	1879-3460
ISSN	0168-1605
DOI	10.1016/j.ijfoodmicro.2018.05.027
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ab Jg. 2022: Lesesaal (EG)

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Article ; Online: Transition metal-free approach for late-stage benzylic C(sp

Zhang, Yu / Sahoo, Prakash Kumar / Ren, Peng / Qin, Yuman / Cauwenbergh, Robin / Nimmegeers, Philippe / SivaRaman, Gandhi / Van Passel, Steven / Guidetti, Andrea / Das, Shoubhik

Chemical communications (Cambridge, England)

2022 Volume 58, Issue 81, Page(s) 11454–11457

Abstract: We report a transition metal-free approach for the regioselective functionalization of benzylic C( ... ...

Abstract	We report a transition metal-free approach for the regioselective functionalization of benzylic C(sp
MeSH term(s)	Carboxylic Acids ; Catalysis ; Esterification ; Ethers/chemistry ; Transition Elements
Chemical Substances	Carboxylic Acids ; Ethers ; Transition Elements
Language	English
Publishing date	2022-10-11
Publishing country	England
Document type	Journal Article
ZDB-ID	1472881-3
ISSN	1364-548X ; 1359-7345 ; 0009-241X
ISSN (online)	1364-548X
ISSN	1359-7345 ; 0009-241X
DOI	10.1039/d2cc02661a
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Using Recyclable Materials Does Not Necessarily Lead to Recyclable Products: A Statistical Entropy-Based Recyclability Assessment of Deli Packaging

Moyaert, Cristina / Fishel, Yanou / Van Nueten, Lorenz / Cencic, Oliver / Rechberger, Helmut / Billen, Pieter / Nimmegeers, Philippe

ACS sustainable chemistry & engineering. 2022 Aug. 30, v. 10, no. 36

2022

Abstract: The increasing attention to reduce plastic waste drives the design of products containing fewer plastics. Deli packaging is such a product, ranging from solely plastic packaging to relatively new paperboard-plastic composites. In this research, the main ... ...

Abstract	The increasing attention to reduce plastic waste drives the design of products containing fewer plastics. Deli packaging is such a product, ranging from solely plastic packaging to relatively new paperboard-plastic composites. In this research, the main objective is to quantify the recyclability of different deli packaging types and evaluate the effectiveness of recycling instructions. Therefore, we combine statistical entropy calculations (for the compositional complexity) with energy calculations from generic sorting and separation processes (i.e., the energy required to separate the products into their chemical substances). Deli packaging samples have been collected, categorized, weighed, and dismantled. The results indicate that the use of paperboard may be slightly better than using solely plastics when one evaluates on a product-level basis. However, since the product types are likely to disturb each other’s waste streams, the analysis should be extended to the whole waste stream in order to fully gauge their impact. Recycling instructions for consumers were found to, in some cases, increase the complexity of monostreams (i.e., plastic and paperboard fractions after dismantling). Although this is evident, for the first time, we develop and apply simple quantitative metrics to describe innate recyclability. The methodology allows one to support design-for-recycling decisions for more complicated systems.
Keywords	energy ; entropy ; green chemistry ; paperboard ; wastes
Language	English
Dates of publication	2022-0830
Size	p. 11719-11725.
Publishing place	American Chemical Society
Document type	Article
ISSN	2168-0485
DOI	10.1021/acssuschemeng.2c04076
Database	NAL-Catalogue (AGRICOLA)

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Article: Bioproduction of the Recombinant Sweet Protein Thaumatin: Current State of the Art and Perspectives.

Joseph, Jewel Ann / Akkermans, Simen / Nimmegeers, Philippe / Van Impe, Jan F M

Frontiers in microbiology

2019 Volume 10, Page(s) 695

Abstract: There is currently a worldwide trend to reduce sugar consumption. This trend is mostly met by the use of artificial non-nutritive sweeteners. However, these sweeteners have also been proven to have adverse health effects such as dizziness, headaches, ... ...

Abstract	There is currently a worldwide trend to reduce sugar consumption. This trend is mostly met by the use of artificial non-nutritive sweeteners. However, these sweeteners have also been proven to have adverse health effects such as dizziness, headaches, gastrointestinal issues, and mood changes for aspartame. One of the solutions lies in the commercialization of sweet proteins, which are not associated with adverse health effects. Of these proteins, thaumatin is one of the most studied and most promising alternatives for sugars and artificial sweeteners. Since the natural production of these proteins is often too expensive, biochemical production methods are currently under investigation. With these methods, recombinant DNA technology is used for the production of sweet proteins in a host organism. The most promising host known today is the methylotrophic yeast,
Language	English
Publishing date	2019-04-08
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2587354-4
ISSN	1664-302X
ISSN	1664-302X
DOI	10.3389/fmicb.2019.00695
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Comparing design of experiments and optimal experimental design techniques for modelling the microbial growth rate under static environmental conditions

Akkermans, Simen / Nimmegeers, Philippe / Van Impe, Jan F

Food microbiology. 2018 Dec., v. 76

2018

Abstract	Building secondary models that describe the growth rate as a function of multiple environmental conditions is often very labour intensive and costly. As such, the current research aims to assist in decreasing the required experimental effort by studying the efficacy of both design of experiments (DOE) and optimal experimental designs (OED) techniques. This is the first research in predictive microbiology (i) to make a comparison of these techniques based on the (relative) model prediction uncertainty of the obtained models and (ii) to compare OED criteria for the design of experiments with static (instead of dynamic) environmental conditions.A comparison of the DOE techniques demonstrated that the inscribed central composite design and full factorial design were most suitable. Five conventional and two tailor made OED criteria were tested. The commonly used D-criterion performed best out of the conventional designs and almost equally well as the best of the dedicated criteria. Moreover, the modelling results of the D-criterion were less dependent on the experimental variability and differences in the microbial response than the two selected DOE techniques. Finally, it was proven that solving the optimisation of the D-criterion can be made more efficient by considering the sensitivities of the growth rate relative to its value as Jacobian matrix instead of the sensitivities of the cell density measurements.
Keywords	environmental factors ; experimental design ; labor ; microbial growth ; models ; predictive microbiology ; uncertainty
Language	English
Dates of publication	2018-12
Size	p. 504-512.
Publishing place	Elsevier Ltd
Document type	Article
ZDB-ID	50892-5
ISSN	1095-9998 ; 0740-0020
ISSN (online)	1095-9998
ISSN	0740-0020
DOI	10.1016/j.fm.2018.05.010
Database	NAL-Catalogue (AGRICOLA)

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Z 4306: Show issues

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Article: A tutorial on uncertainty propagation techniques for predictive microbiology models: A critical analysis of state-of-the-art techniques

Akkermans, Simen / Jan F. Van Impe / Philippe Nimmegeers

International journal of food microbiology. 2018 Oct. 03, v. 282

2018

Abstract	Building mathematical models in predictive microbiology is a data driven science. As such, the experimental data (and its uncertainty) has an influence on the final predictions and even on the calculation of the model prediction uncertainty. Therefore, the current research studies the influence of both the parameter estimation and uncertainty propagation method on the calculation of the model prediction uncertainty. The study is intended as well as a tutorial to uncertainty propagation techniques for researchers in (predictive) microbiology. To this end, an in silico case study was applied in which the effect of temperature on the microbial growth rate was modelled and used to make simulations for a temperature profile that is characterised by variability. The comparison of the parameter estimation methods demonstrated that the one-step method yields more accurate and precise calculations of the model prediction uncertainty than the two-step method. Four uncertainty propagation methods were assessed. The current work assesses the applicability of these techniques by considering the effect of experimental uncertainty and model input uncertainty. The linear approximation was demonstrated not always to provide reliable results. The Monte Carlo method was computationally very intensive, compared to its competitors. Polynomial chaos expansion was computationally efficient and accurate but is relatively complex to implement. Finally, the sigma point method was preferred as it is (i) computationally efficient, (ii) robust with respect to experimental uncertainty and (iii) easily implemented.
Keywords	case studies ; mathematical models ; microbial growth ; Monte Carlo method ; prediction ; predictive microbiology ; researchers ; temperature profiles ; uncertainty
Language	English
Dates of publication	2018-1003
Size	p. 1-8.
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	87122-9
ISSN	1879-3460 ; 0168-1605
ISSN (online)	1879-3460
ISSN	0168-1605
DOI	10.1016/j.ijfoodmicro.2018.05.027
Database	NAL-Catalogue (AGRICOLA)

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Z 4383: Show issues

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Article ; Online: Extending Multilevel Statistical Entropy Analysis towards Plastic Recyclability Prediction

Philippe Nimmegeers / Alexej Parchomenko / Paul De Meulenaere / Dagmar R. D’hooge / Paul H. M. Van Steenberge / Helmut Rechberger / Pieter Billen

Sustainability, Vol 13, Iss 3553, p

2021 Volume 3553

Abstract: Multilevel statistical entropy analysis (SEA) is a method that has been recently proposed to evaluate circular economy strategies on the material, component and product levels to identify critical stages of resource and functionality losses. However, the ...

Abstract	Multilevel statistical entropy analysis (SEA) is a method that has been recently proposed to evaluate circular economy strategies on the material, component and product levels to identify critical stages of resource and functionality losses. However, the comparison of technological alternatives may be difficult, and equal entropies do not necessarily correspond with equal recyclability. A coupling with energy consumption aspects is strongly recommended but largely lacking. The aim of this paper is to improve the multilevel SEA method to reliably assess the recyclability of plastics. Therefore, the multilevel SEA method is first applied to a conceptual case study of a fictitious bag filled with plastics, and the possibilities and limitations of the method are highlighted. Subsequently, it is proposed to extend the method with the computation of the relative decomposition energies of components and products. Finally, two recyclability metrics are proposed. A plastic waste collection bag filled with plastic bottles is used as a case study to illustrate the potential of the developed extended multilevel SEA method. The proposed extension allows us to estimate the recyclability of plastics. In future work, this method will be refined and other potential extensions will be studied together with applications to real-life plastic products and plastic waste streams.
Keywords	statistical entropy analysis ; recycling ; plastic waste ; waste management ; resource efficiency ; circular economy ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Language	English
Publishing date	2021-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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