XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 2293
model strategies in the contest of mineral-water interfaces
are currently underway in our group.
ACKNOWLEDGMENTS
This work has been conducted in the frame of the indus-
trial chair MULTIMINE funded by ArcelorMittal, Région
Grand Est, Metz Métropole and Université de Lorraine.
REFERENCES
Bartók, A.P., Kondor, R. and Csányi, G. 2013, On rep-
resenting chemical environments. Phys. Rev. B,
87:184115.
Behler, J., and Parrinello, M. 2007, Generalized neural-
network representation of high-dimensional potential-
energy surfaces. Phys. Rev. Lett., 98:146401.
Bernstein, N., Csányi, G. and Deringer, V. L. 2019, De
novo exploration and self-guided learning of potential-
energy surfaces. npj Computational Materials, 5(1).
Calvo, G., Mudd, G., Valero, A. and Valero, A. 2016,
Decreasing Ore Grades in Global Metallic Mining: A
Theoretical Issue or a Global Reality? Resources, 5, 36.
Chipfunhu, D., Zanin, M. and Grano, S. 2011, The
dependency of the critical contact angle for flotation
on particle size – modelling the limits of fine particle
flotation. Minerals Engineering, 24(1):50–57.
Cisneros, G.A., Wikfeldt, K.T., Ojamäe, L., Lu, J., Xu, Y.,
Torabifard, H., Bartók, A.P., Csányi, G., Molinero, V.
and Paesani, F. 2016, Modeling molecular interactions
in water: From pairwise to many-body potential energy
functions. Chemical Reviews, 116(13):7501–7528.
Drautz, R. 2019, Atomic cluster expansion for accurate
and transferable interatomic potentials. Phys. Rev. B,
99:014104.
Erbil, H. Y. 2014, The debate on the dependence of appar-
ent contact angles on drop contact area or three-
phase contact line: A review. Surface Science Reports,
69(4):325–365.
Farrokhpay, S., Filippov, L. and Fornasiero, D. 2020,
Flotation of fine particles: A review. Mineral Processing
and Extractive Metallurgy Review, 42(7):473–483.
Feng, D. and Nguyen, A. V. 2017, Contact angle varia-
tion on single floating spheres and its impact on the
stability analysis of floating particles. Colloids and
Surfaces A: Physicochemical and Engineering Aspects,
520:442–447.
Foucaud, Y., Badawi, M., Filippov, L.O., Filippova, I.V.
and Lebègue, S. 2018, Surface Properties of Fluorite in
Presence of Water: An Atomistic Investigation. J. Phys.
Chem. B, 122(26):6829–6836.
Figure 8. Scheme used to save computational cost over the MLFF training. (a) The system is trained separately and (b)
eventually merged in a database which in turn can be used as a data set for further, specific training
model strategies in the contest of mineral-water interfaces
are currently underway in our group.
ACKNOWLEDGMENTS
This work has been conducted in the frame of the indus-
trial chair MULTIMINE funded by ArcelorMittal, Région
Grand Est, Metz Métropole and Université de Lorraine.
REFERENCES
Bartók, A.P., Kondor, R. and Csányi, G. 2013, On rep-
resenting chemical environments. Phys. Rev. B,
87:184115.
Behler, J., and Parrinello, M. 2007, Generalized neural-
network representation of high-dimensional potential-
energy surfaces. Phys. Rev. Lett., 98:146401.
Bernstein, N., Csányi, G. and Deringer, V. L. 2019, De
novo exploration and self-guided learning of potential-
energy surfaces. npj Computational Materials, 5(1).
Calvo, G., Mudd, G., Valero, A. and Valero, A. 2016,
Decreasing Ore Grades in Global Metallic Mining: A
Theoretical Issue or a Global Reality? Resources, 5, 36.
Chipfunhu, D., Zanin, M. and Grano, S. 2011, The
dependency of the critical contact angle for flotation
on particle size – modelling the limits of fine particle
flotation. Minerals Engineering, 24(1):50–57.
Cisneros, G.A., Wikfeldt, K.T., Ojamäe, L., Lu, J., Xu, Y.,
Torabifard, H., Bartók, A.P., Csányi, G., Molinero, V.
and Paesani, F. 2016, Modeling molecular interactions
in water: From pairwise to many-body potential energy
functions. Chemical Reviews, 116(13):7501–7528.
Drautz, R. 2019, Atomic cluster expansion for accurate
and transferable interatomic potentials. Phys. Rev. B,
99:014104.
Erbil, H. Y. 2014, The debate on the dependence of appar-
ent contact angles on drop contact area or three-
phase contact line: A review. Surface Science Reports,
69(4):325–365.
Farrokhpay, S., Filippov, L. and Fornasiero, D. 2020,
Flotation of fine particles: A review. Mineral Processing
and Extractive Metallurgy Review, 42(7):473–483.
Feng, D. and Nguyen, A. V. 2017, Contact angle varia-
tion on single floating spheres and its impact on the
stability analysis of floating particles. Colloids and
Surfaces A: Physicochemical and Engineering Aspects,
520:442–447.
Foucaud, Y., Badawi, M., Filippov, L.O., Filippova, I.V.
and Lebègue, S. 2018, Surface Properties of Fluorite in
Presence of Water: An Atomistic Investigation. J. Phys.
Chem. B, 122(26):6829–6836.
Figure 8. Scheme used to save computational cost over the MLFF training. (a) The system is trained separately and (b)
eventually merged in a database which in turn can be used as a data set for further, specific training