XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 1017
Buchmann, M., Schach, E., Tolosana-Delgado, R.,
Leißner, T., Astoveza, J., Kern, M., Möckel, R.,
Ebert, D., Rudolph, M., van den Boogaart, K.,
Peuker, U., 2018. Evaluation of Magnetic Separation
Efficiency on a Cassiterite-Bearing Skarn Ore by
Means of Integrative SEM-Based Image and XRF–
XRD Data Analysis. Minerals 8, 390. doi: 10.3390
/min8090390.
Fernandes, I.B., Rudolph, M., Hassanzadeh, A.,
Bachmann, K., Meskers, C., Peuker, U., Reuter, M.A.,
2021. The quantification of entropy for multicompo-
nent systems: Application to microwave-assisted com-
minution. Miner. Eng. 170, 107016. doi: 10.1016
/j.mineng.2021.107016.
Martínez, O.V., Omar Velazquez Martinez, van den
Boogaart, K.G., K.G. van den Boogaart, K. G. Van
Den Bogaart, Lundström, M., Santasalo-Aarnio,
A., Reuter, M.A., Rodrigo Serna Guerrero, Serna-
Guerrero, R., 2019. Statistical entropy analysis
as tool for circular economy: Proof of concept by
optimizing a lithium-ion battery waste sieving sys-
tem. J. Clean. Prod. 212, 1568–1579. doi: 10.1016
/j.jclepro.2018.12.137.
Parchomenko, A., Nelen, D., Gillabel, J., Vrancken, K.C.,
Rechberger, H., 2021. Resource effectiveness of the
European automotive sector—a statistical entropy
analysis over time. Resour. Conserv. Recycl. 169, 105558.
doi: 10.1016/j.resconrec.2021.105558.
Parchomenko, A., Nelen, D., Gillabel, J., Vrancken,
K.C., Rechberger, H., 2020. Evaluation of the
resource effectiveness of circular economy strate-
gies through multilevel Statistical Entropy Analysis.
Resour. Conserv. Recycl. 161, 104925. doi: 10.1016
/j.resconrec.2020.104925.
Peuker, U.A., van den Boogaart, K.G., Rudolph, M.,
Tolosana-Delgado, R., 2020. The entropy of inter-
grown particle mixtures—a contribution to holistic
flowsheet simulation, in: IMPC 2020. Presented at
the International Mineral Processing Congress, Cape
Town.
Rechberger, H., 2001. An entropy based method to evalu-
ate hazardous inorganic substance balances of waste
treatment systems. Waste Manag. Res. 19, 186–192.
doi: 10.1177/0734242x0101900210.
Rechberger, H., Brunner, P.H., 2002. A New, Entropy Based
Method To Support Waste and Resource Management
Decisions. Environ. Sci. Technol. 36, 809–816. doi:
10.1021/es010030h.
Rechberger, H., Graedel, T.E., 2002. The contempo-
rary European copper cycle: statistical entropy
analysis. Ecol. Econ. 42, 59–72. doi: 10.1016
/s0921-8009(02)00102-7.
Schach, E., Buchmann, M., Tolosana-Delgado, R.,
Leißner, T., Kern, M., Gerald van den Boogaart, K.,
Rudolph, M., Peuker, U.A., 2019. Multidimensional
characterization of separation processes—Part 1:
Introducing kernel methods and entropy in the con-
text of mineral processing using SEM-based image
analysis. Miner. Eng. 137, 78–86. doi: 10.1016
/j.mineng.2019.03.026.
Schach, E., Buchwald, T., Leißner, T., Peuker, U., Delgado,
R.T., 2024. Concepts of entropy for raw materi-
als. Powder Technol. 435, 119398. doi: 10.1016
/j.powtec.2024.119398.
Shannon, C.E., 1948. The Mathematical Theory of
Communication.
Sobantka, A., Pons, M.-N., Zessner, M., Rechberger,
H., 2014a. Implementation of Extended Statistical
Entropy Analysis to the Effluent Quality Index of the
Benchmarking Simulation Model No. 2. Water 6,
86–103. doi: 10.3390/w6010086.
Sobantka, A., Thaler, S., Zessner, M., Rechberger, H.,
2014b. Extended statistical entropy analysis for the
evaluation of nitrogen budgets in Austria. Int. J.
Environ. Sci. Technol. 11, 1947–1958. doi: 10.1007/
s13762-013-0401-2.
Velázquez-Martinez, O., Kontomichalou, A., Santasalo-
Aarnio, A., Reuter, M., Karttunen, A.J., Karppinen,
M., Serna-Guerrero, R., 2020. A recycling pro-
cess for thermoelectric devices developed with
the support of statistical entropy analysis. Resour.
Conserv. Recycl. 159, 104843. doi: 10.1016
/j.resconrec.2020.104843.
Velazquez-Martinez, O., Valio, J., Santasalo-Aarnio, A.,
Reuter, M.A., Serna-Guerrero, R., 2019. A critical
review of lithium-ion battery recycling processes from
a circular economy perspective. Batteries 5, 68. doi:
10.3390/batteries5040068
Buchmann, M., Schach, E., Tolosana-Delgado, R.,
Leißner, T., Astoveza, J., Kern, M., Möckel, R.,
Ebert, D., Rudolph, M., van den Boogaart, K.,
Peuker, U., 2018. Evaluation of Magnetic Separation
Efficiency on a Cassiterite-Bearing Skarn Ore by
Means of Integrative SEM-Based Image and XRF–
XRD Data Analysis. Minerals 8, 390. doi: 10.3390
/min8090390.
Fernandes, I.B., Rudolph, M., Hassanzadeh, A.,
Bachmann, K., Meskers, C., Peuker, U., Reuter, M.A.,
2021. The quantification of entropy for multicompo-
nent systems: Application to microwave-assisted com-
minution. Miner. Eng. 170, 107016. doi: 10.1016
/j.mineng.2021.107016.
Martínez, O.V., Omar Velazquez Martinez, van den
Boogaart, K.G., K.G. van den Boogaart, K. G. Van
Den Bogaart, Lundström, M., Santasalo-Aarnio,
A., Reuter, M.A., Rodrigo Serna Guerrero, Serna-
Guerrero, R., 2019. Statistical entropy analysis
as tool for circular economy: Proof of concept by
optimizing a lithium-ion battery waste sieving sys-
tem. J. Clean. Prod. 212, 1568–1579. doi: 10.1016
/j.jclepro.2018.12.137.
Parchomenko, A., Nelen, D., Gillabel, J., Vrancken, K.C.,
Rechberger, H., 2021. Resource effectiveness of the
European automotive sector—a statistical entropy
analysis over time. Resour. Conserv. Recycl. 169, 105558.
doi: 10.1016/j.resconrec.2021.105558.
Parchomenko, A., Nelen, D., Gillabel, J., Vrancken,
K.C., Rechberger, H., 2020. Evaluation of the
resource effectiveness of circular economy strate-
gies through multilevel Statistical Entropy Analysis.
Resour. Conserv. Recycl. 161, 104925. doi: 10.1016
/j.resconrec.2020.104925.
Peuker, U.A., van den Boogaart, K.G., Rudolph, M.,
Tolosana-Delgado, R., 2020. The entropy of inter-
grown particle mixtures—a contribution to holistic
flowsheet simulation, in: IMPC 2020. Presented at
the International Mineral Processing Congress, Cape
Town.
Rechberger, H., 2001. An entropy based method to evalu-
ate hazardous inorganic substance balances of waste
treatment systems. Waste Manag. Res. 19, 186–192.
doi: 10.1177/0734242x0101900210.
Rechberger, H., Brunner, P.H., 2002. A New, Entropy Based
Method To Support Waste and Resource Management
Decisions. Environ. Sci. Technol. 36, 809–816. doi:
10.1021/es010030h.
Rechberger, H., Graedel, T.E., 2002. The contempo-
rary European copper cycle: statistical entropy
analysis. Ecol. Econ. 42, 59–72. doi: 10.1016
/s0921-8009(02)00102-7.
Schach, E., Buchmann, M., Tolosana-Delgado, R.,
Leißner, T., Kern, M., Gerald van den Boogaart, K.,
Rudolph, M., Peuker, U.A., 2019. Multidimensional
characterization of separation processes—Part 1:
Introducing kernel methods and entropy in the con-
text of mineral processing using SEM-based image
analysis. Miner. Eng. 137, 78–86. doi: 10.1016
/j.mineng.2019.03.026.
Schach, E., Buchwald, T., Leißner, T., Peuker, U., Delgado,
R.T., 2024. Concepts of entropy for raw materi-
als. Powder Technol. 435, 119398. doi: 10.1016
/j.powtec.2024.119398.
Shannon, C.E., 1948. The Mathematical Theory of
Communication.
Sobantka, A., Pons, M.-N., Zessner, M., Rechberger,
H., 2014a. Implementation of Extended Statistical
Entropy Analysis to the Effluent Quality Index of the
Benchmarking Simulation Model No. 2. Water 6,
86–103. doi: 10.3390/w6010086.
Sobantka, A., Thaler, S., Zessner, M., Rechberger, H.,
2014b. Extended statistical entropy analysis for the
evaluation of nitrogen budgets in Austria. Int. J.
Environ. Sci. Technol. 11, 1947–1958. doi: 10.1007/
s13762-013-0401-2.
Velázquez-Martinez, O., Kontomichalou, A., Santasalo-
Aarnio, A., Reuter, M., Karttunen, A.J., Karppinen,
M., Serna-Guerrero, R., 2020. A recycling pro-
cess for thermoelectric devices developed with
the support of statistical entropy analysis. Resour.
Conserv. Recycl. 159, 104843. doi: 10.1016
/j.resconrec.2020.104843.
Velazquez-Martinez, O., Valio, J., Santasalo-Aarnio, A.,
Reuter, M.A., Serna-Guerrero, R., 2019. A critical
review of lithium-ion battery recycling processes from
a circular economy perspective. Batteries 5, 68. doi:
10.3390/batteries5040068