Three-Dimensional and Lamellar Graphene Oxide Membranes …
105
strengthen the π–π attraction, yielding exceptional stability [116]. The search for
new host materials is, therefore, a current area of research that demands further
investigation.
From design to the experimental realization of large-scale GO/rGO membranes,
computational studies are helping to understand and improve protocols, methods,
and applications. If the production of such membranes is still a challenge, it would
be impracticable without the guidance of atomic-scale simulations. Only at this
level, we can understand some of the factors driving water permeance and pollutant rejection rates. Simulations have also been used as predictive tools for new and
improved materials, determining their structural resistance and selectivity properties even before experiments—saving both scientists’ money and time. However,
these simulations can be quite expensive, using substantial computational resources.
Data mining algorithms, such as machine learning (ML) and deep learning (DL),
can also extract useful knowledge on new materials, geometries, and functionalizations, creating structure–property maps that play a key role in accelerated materials
discovery [117, 118]. Some of its advantages are (i) the huge database with several
properties of countless materials and (ii) the speed with which this huge amount of
data can be processed to find the best candidates. Inverse design, where data-driven
materials with pre-defined target properties are proposed, has emerged as an important numerical tool in recent years by shading some light in hidden information of
materials [119]. GO/rGO-based membranes can certainly take advantage of these
powerful tools to find a more efficient and safe path.
Despite the extraordinary advancements in the last few years, there is one final
barrier to overcome: the industrial scale production. As we have shown, this horizon
is not so far for GO/rGO membranes. However, there are still some obstacles. For
lamellar GO/rGO, the construction is often by self-stacking nanosheets. Ideally,
this method allows for a simple assembly and facilitates the scaling up both by the
thickness and surface area. But the cost associated with building up uniform, welldefined layered structures can be disadvantageous in large-scale scenarios. In this
way, 3D GO/rGO can stand as a cheaper option. The problem is the scaling, which
is still far from industrial needs. One possible solution is to find a material that can
combine the low cost of 3D GO/rGO and the self-assembly control from lamellar
structures, the last great challenge.
References and Future Readings
1. WWAP and UNESCO (2019) The United Nations world water development report 2019:
leaving no one behind, United Nations Educational, Scientific and Cultural Organization
2. Eliasson J (2015) The rising pressure of global water shortages. Nature 517:6
3. WWAP and UNESCO (2017) The United Nations world water development report, 2017:
Wastewater: an untapped resource; executive summary, United Nations Educational, Scientific
and Cultural Organization
105
strengthen the π–π attraction, yielding exceptional stability [116]. The search for
new host materials is, therefore, a current area of research that demands further
investigation.
From design to the experimental realization of large-scale GO/rGO membranes,
computational studies are helping to understand and improve protocols, methods,
and applications. If the production of such membranes is still a challenge, it would
be impracticable without the guidance of atomic-scale simulations. Only at this
level, we can understand some of the factors driving water permeance and pollutant rejection rates. Simulations have also been used as predictive tools for new and
improved materials, determining their structural resistance and selectivity properties even before experiments—saving both scientists’ money and time. However,
these simulations can be quite expensive, using substantial computational resources.
Data mining algorithms, such as machine learning (ML) and deep learning (DL),
can also extract useful knowledge on new materials, geometries, and functionalizations, creating structure–property maps that play a key role in accelerated materials
discovery [117, 118]. Some of its advantages are (i) the huge database with several
properties of countless materials and (ii) the speed with which this huge amount of
data can be processed to find the best candidates. Inverse design, where data-driven
materials with pre-defined target properties are proposed, has emerged as an important numerical tool in recent years by shading some light in hidden information of
materials [119]. GO/rGO-based membranes can certainly take advantage of these
powerful tools to find a more efficient and safe path.
Despite the extraordinary advancements in the last few years, there is one final
barrier to overcome: the industrial scale production. As we have shown, this horizon
is not so far for GO/rGO membranes. However, there are still some obstacles. For
lamellar GO/rGO, the construction is often by self-stacking nanosheets. Ideally,
this method allows for a simple assembly and facilitates the scaling up both by the
thickness and surface area. But the cost associated with building up uniform, welldefined layered structures can be disadvantageous in large-scale scenarios. In this
way, 3D GO/rGO can stand as a cheaper option. The problem is the scaling, which
is still far from industrial needs. One possible solution is to find a material that can
combine the low cost of 3D GO/rGO and the self-assembly control from lamellar
structures, the last great challenge.
References and Future Readings
1. WWAP and UNESCO (2019) The United Nations world water development report 2019:
leaving no one behind, United Nations Educational, Scientific and Cultural Organization
2. Eliasson J (2015) The rising pressure of global water shortages. Nature 517:6
3. WWAP and UNESCO (2017) The United Nations world water development report, 2017:
Wastewater: an untapped resource; executive summary, United Nations Educational, Scientific
and Cultural Organization