تحت رعاية صاحب السمو الشيخ محمد بن زايد آل نهيان، رئيس دولة الإمارات العربية المتحدة

Under The Patronage of H.H. Sheikh Mohamed Bin Zayed Al Nahyan President Of The United Arab Emirates

4-7 November 2024

Abu Dhabi, UAE

Youth Innovation Session

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  • 02 October

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15:30

02 October

15:30 - 15:45

0 hr 15 Mins

Novel Nanomaterial - enhanced membrane to remove oil from wastewater

In addressing critical environmental challenges, innovative membrane technologies have emerged as powerful solutions for various applications:

Firstly, the novel “3D Hierarchical Nanoporous Graphene Membrane for Efficient Oil/Water Separation” presents an exciting breakthrough in oil-water separation. This membrane leverages the exceptional properties of graphene to create a structured nanoporous membrane that outperforms conventional methods. This breakthrough membrane represents a golden opportunity for efficiently treating industrial oily wastewater, marking a significant step toward environmental sustainability.

Secondly, the study on “Enhanced Oily Wastewater Treatment using Green and Sustainable Membranes” introduces a significant advancement in wastewater treatment. By incorporating environmentally friendly and sustainable membrane materials, this research not only improves treatment efficiency but also promotes responsible environmental practices. It underscores the importance of sustainability in addressing pollution issues.

Thirdly, the work on “Biodegradable Poly Lactic Acid (PLA) Mixed Matrix Membranes for Efficient Oil-Water Separation” focuses on biodegradable materials for membrane development. By combining Poly Lactic Acid (PLA) with nanomaterials, this research pioneers a sustainable solution for efficient oil-water separation. This innovation not only addresses the challenge of oil-contaminated wastewater but also aligns with eco-friendly practices.

Lastly, our study “Hydrophobic Polyethersulfone/Iron Oxide-Oleylamine Ultrafiltration Membranes for Efficient Water-in-Oil Emulsion Separation” focused on the recently advanced membrane technology that is a game-changer in protecting oceans from catastrophic oil spills caused by offshore oil exploration and transportation. It excels in efficiently separating oil from water, offers cost-effective alternatives to traditional cleanup methods, and minimizes environmental damage while aligning with responsible environmental practices.

In each of these studies, the incorporation of novel materials and innovative approaches has the potential to revolutionize the respective fields of oil-water separation and wastewater treatment. These advancements offer environmentally responsible solutions with improved efficiency, highlighting the crucial role of membrane technology in safeguarding our environment.

Session Panelists:

Dr. Shadi Hasan

Director, Center for Membranes & Advanced Water Technology

Khalifah University

Eng. Farah Abuhatab

Research Associate

Khalifah University

Farah Abuhantash

PhD, Student

Khalifah University

Yazan Abuhasheesh

PhD Candidate

Khalifah University

Back

Monday 02 October 2023

15:30 - 15:45

Novel Nanomaterial - enhanced membrane to remove oil from wastewater

In addressing critical environmental challenges, innovative membrane technologies have emerged as powerful solutions for various applications:

Firstly, the novel “3D Hierarchical Nanoporous Graphene Membrane for Efficient Oil/Water Separation” presents an exciting breakthrough in oil-water separation. This membrane leverages the exceptional properties of graphene to create a structured nanoporous membrane that outperforms conventional methods. This breakthrough membrane represents a golden opportunity for efficiently treating industrial oily wastewater, marking a significant step toward environmental sustainability.

Secondly, the study on “Enhanced Oily Wastewater Treatment using Green and Sustainable Membranes” introduces a significant advancement in wastewater treatment. By incorporating environmentally friendly and sustainable membrane materials, this research not only improves treatment efficiency but also promotes responsible environmental practices. It underscores the importance of sustainability in addressing pollution issues.

Thirdly, the work on “Biodegradable Poly Lactic Acid (PLA) Mixed Matrix Membranes for Efficient Oil-Water Separation” focuses on biodegradable materials for membrane development. By combining Poly Lactic Acid (PLA) with nanomaterials, this research pioneers a sustainable solution for efficient oil-water separation. This innovation not only addresses the challenge of oil-contaminated wastewater but also aligns with eco-friendly practices.

Lastly, our study “Hydrophobic Polyethersulfone/Iron Oxide-Oleylamine Ultrafiltration Membranes for Efficient Water-in-Oil Emulsion Separation” focused on the recently advanced membrane technology that is a game-changer in protecting oceans from catastrophic oil spills caused by offshore oil exploration and transportation. It excels in efficiently separating oil from water, offers cost-effective alternatives to traditional cleanup methods, and minimizes environmental damage while aligning with responsible environmental practices.

In each of these studies, the incorporation of novel materials and innovative approaches has the potential to revolutionize the respective fields of oil-water separation and wastewater treatment. These advancements offer environmentally responsible solutions with improved efficiency, highlighting the crucial role of membrane technology in safeguarding our environment.

Session Panelists:

Dr. Shadi Hasan

Director, Center for Membranes & Advanced Water Technology

Khalifah University

Eng. Farah Abuhatab

Research Associate

Khalifah University

Farah Abuhantash

PhD, Student

Khalifah University

Yazan Abuhasheesh

PhD Candidate

Khalifah University

16:00

02 October

16:00 - 16:15

0 hr 15 Mins

Identifying the best photocatalysts for Green Hydrogen Production using computational screening

Converting solar energy into valuable fuels has been established as an intriguing strategy to shift traditional fossil fuels towards cleaner, more sustainable energy sources,. In this regard, green hydrogen generation via H2O (or H2S splitting) has consistently drawn attention in both academia and industry. However, seeking robust photocatalysts to achieve higher visible-light conversion efficiency, quantum yields, and selectivity remains a pressing challenge, as a priori, there are thousands of materials that need to be investigated.

Theoretical calculations and high-throughput modeling approaches are becoming indispensable tools for the design of materials with desired properties, as they provide an understanding of the connection between their structural features and their performance, while also providing physical insights into the key properties and mechanisms, thus complementing the experiments and guiding the effective design of photocatalysts.

The team at the RICH center has been working on using computational modeling to guide the design of the best photocatalysts for green hydrogen production. We have been using quantum calculations and machine learning as supporting tools for understanding and searching novel materials for clean energy applications, focusing on hydrogen evolution reaction (HER) from H2S splitting and water splitting. We started the process by calculating the simple key properties any photocatalytic material considered for hydrogen production should have. After it, we used some other screening procedures until we shortlisted the ones that can have an outstanding performance, some of them never tested experimentally. We are currently synthesizing and testing them at the RICH lab, with the goal of scaling up the best ones for testing at industrial conditions.

This contribution specifically focuses on the following interconnected themes:

  • Understanding the performance of cadmium-sulfide photocatalyst for H2S splitting.
  • Screening single transition metal doped sulfide-based co-catalyst for H2S splitting and H2O splitting.
  • Machine Learning-assisted large-scale screening metal sulfide photocatalysts for hydrogen generation

First, we investigated the adsorption and dissociation of H2S on perfect and defective CdS surfaces using DFT calculations. This marks the beginning of our journey in computational modeling, aiming at understanding the relationship between the fundamental properties of the photocatalysts and their performance in photocatalysis. We analyze the electronic properties and surface reactivity in order to provide quantum insights into the photocatalytic activity of CdS-based materials for hydrogen evolution.

Then, we extended our DFT calculations to screen possible transition metals as co-catalysts doped on CdS surfaces for HER. We analyzed the structural stability, electronic properties and adsorption energies of various surfaces to identify promising candidates for future experimental testing. Our results not only provide a fundamental understanding of the role of transition metal doping in enhancing the HER activity of CdS, but also offer valuable guidance for the rational design and optimization of transition metal-doped photocatalysts for hydrogen evolution.

Finally, we employed ML algorithms to assist in a large-scale screening (high-throughput method) for metal sulfide photocatalysts with optimal stability and activity in HER. Geometric, electronic, and energyrelated features were used for training. We were able to predict the structural stability and H adsorption energies over +1,000 unique adsorption structures and identify 10 potential metal sulfide lattices with optimal stability, band gap, and catalytic activity for HER. These candidate materials can be further studied by computational simulations or experiments, and potentially used in photocatalytic HER applications. Such integration of different levels of modeling techniques provides a direct link between the molecular structure of photocatalysts and their catalytic performance that can assist in the optimal design of the synthesis of desired photocatalysts.

The modeling work also applied to some of the experimental works developed at the Research and Innovation Center on CO2 and Hydrogen (RICH) in a complementary manner. These studies have demonstrated the crucial relationships between the fundamental properties of photocatalysts and their stability, catalytic activity and selectivity. Key descriptors have been identified for the design and synthesis of proper semiconductors, aiming at inspiring further simulation and experimental works of tailoring photocatalysts design for HER so that the best ones are scaled up for green hydrogen production directly using solar energy.

Furthermore, the integration of theoretical calculations and machine learning techniques has proven to be a powerful approach to accelerate novel materials discovery at a lower research cost. 

Session Panelists:

Dr. Lourdes Vega

Director of the Research and Innovation Center on CO2 and Hydrogen (RICH)

Khalifah University

Dr. Yuting Li

post-doctoral researcher

Khalifah University

Dr. Daniel Bahamon Garcia

senior research scientist

Khalifah University

Dr. Samar Al Jitan

post-doctoral researcher

Khalifah University

Reem Al Sakkaf

research engineer

Khalifah University

Jaber Almarri

BSc student

Khalifah University

Back

Monday 02 October 2023

16:00 - 16:15

Identifying the best photocatalysts for Green Hydrogen Production using computational screening

Converting solar energy into valuable fuels has been established as an intriguing strategy to shift traditional fossil fuels towards cleaner, more sustainable energy sources,. In this regard, green hydrogen generation via H2O (or H2S splitting) has consistently drawn attention in both academia and industry. However, seeking robust photocatalysts to achieve higher visible-light conversion efficiency, quantum yields, and selectivity remains a pressing challenge, as a priori, there are thousands of materials that need to be investigated.

Theoretical calculations and high-throughput modeling approaches are becoming indispensable tools for the design of materials with desired properties, as they provide an understanding of the connection between their structural features and their performance, while also providing physical insights into the key properties and mechanisms, thus complementing the experiments and guiding the effective design of photocatalysts.

The team at the RICH center has been working on using computational modeling to guide the design of the best photocatalysts for green hydrogen production. We have been using quantum calculations and machine learning as supporting tools for understanding and searching novel materials for clean energy applications, focusing on hydrogen evolution reaction (HER) from H2S splitting and water splitting. We started the process by calculating the simple key properties any photocatalytic material considered for hydrogen production should have. After it, we used some other screening procedures until we shortlisted the ones that can have an outstanding performance, some of them never tested experimentally. We are currently synthesizing and testing them at the RICH lab, with the goal of scaling up the best ones for testing at industrial conditions.

This contribution specifically focuses on the following interconnected themes:

  • Understanding the performance of cadmium-sulfide photocatalyst for H2S splitting.
  • Screening single transition metal doped sulfide-based co-catalyst for H2S splitting and H2O splitting.
  • Machine Learning-assisted large-scale screening metal sulfide photocatalysts for hydrogen generation

First, we investigated the adsorption and dissociation of H2S on perfect and defective CdS surfaces using DFT calculations. This marks the beginning of our journey in computational modeling, aiming at understanding the relationship between the fundamental properties of the photocatalysts and their performance in photocatalysis. We analyze the electronic properties and surface reactivity in order to provide quantum insights into the photocatalytic activity of CdS-based materials for hydrogen evolution.

Then, we extended our DFT calculations to screen possible transition metals as co-catalysts doped on CdS surfaces for HER. We analyzed the structural stability, electronic properties and adsorption energies of various surfaces to identify promising candidates for future experimental testing. Our results not only provide a fundamental understanding of the role of transition metal doping in enhancing the HER activity of CdS, but also offer valuable guidance for the rational design and optimization of transition metal-doped photocatalysts for hydrogen evolution.

Finally, we employed ML algorithms to assist in a large-scale screening (high-throughput method) for metal sulfide photocatalysts with optimal stability and activity in HER. Geometric, electronic, and energyrelated features were used for training. We were able to predict the structural stability and H adsorption energies over +1,000 unique adsorption structures and identify 10 potential metal sulfide lattices with optimal stability, band gap, and catalytic activity for HER. These candidate materials can be further studied by computational simulations or experiments, and potentially used in photocatalytic HER applications. Such integration of different levels of modeling techniques provides a direct link between the molecular structure of photocatalysts and their catalytic performance that can assist in the optimal design of the synthesis of desired photocatalysts.

The modeling work also applied to some of the experimental works developed at the Research and Innovation Center on CO2 and Hydrogen (RICH) in a complementary manner. These studies have demonstrated the crucial relationships between the fundamental properties of photocatalysts and their stability, catalytic activity and selectivity. Key descriptors have been identified for the design and synthesis of proper semiconductors, aiming at inspiring further simulation and experimental works of tailoring photocatalysts design for HER so that the best ones are scaled up for green hydrogen production directly using solar energy.

Furthermore, the integration of theoretical calculations and machine learning techniques has proven to be a powerful approach to accelerate novel materials discovery at a lower research cost. 

Session Panelists:

Dr. Lourdes Vega

Director of the Research and Innovation Center on CO2 and Hydrogen (RICH)

Khalifah University

Dr. Yuting Li

post-doctoral researcher

Khalifah University

Dr. Daniel Bahamon Garcia

senior research scientist

Khalifah University

Dr. Samar Al Jitan

post-doctoral researcher

Khalifah University

Reem Al Sakkaf

research engineer

Khalifah University

Jaber Almarri

BSc student

Khalifah University

  • 02 October

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