The scientist turning Dune’s ‘water harvesting’ into reality

Sustainable Development Goals (SDGs): Artificial Intelligence Offers Solution to Water Scarcity

Access to clean water is becoming an increasing problem as the world population grows and the planet warms. By 2025, half the world’s population could be living in areas facing water scarcity, and more than two billion people already live in areas with inadequate water supply, according to UNICEF. However, artificial intelligence (AI) could provide a solution to this crisis.

The Potential of AI in Water Production

Recent technological advancements have enabled the desalination of seawater, but this process is expensive and limited to coastal areas. Scientists have also explored Atmospheric Water Harvesting, which involves collecting dew or harvesting water from fog using nets. However, a new AI-enhanced system developed by Atoco shows promise in drawing water from the air, even in arid regions.

1. MOF-303: A Breakthrough Material

Atoco’s system utilizes a water-absorbing compound called MOF-303 (metal-organic framework). This material, designed with the help of AI, has a highly complex atomic structure that allows it to “trap” water molecules. MOF-303 is an adsorbent, meaning it traps water on its surface. It has an exceptionally large surface area within a small volume, maximizing its ability to capture and release water molecules.

2. The Role of AI

AI played a crucial role in the development of MOF-303. Atoco’s R&D scientists collaborated with researchers from the University of California Berkeley, using AI to accelerate the discovery of new compounds with the right structure to capture water from the air. AI assistants acted as virtual research groups, conducting literature reviews, mining valuable information, and performing virtual experiments. This significantly sped up the research process and allowed for the identification of promising molecular structures.

3. Addressing the Water Crisis

Atoco’s AI-enhanced system has the potential to address the water crisis by providing access to water in arid and water-stressed regions. Current Atmospheric Water Harvesting systems are limited to foggy or humid areas, but Atoco’s system can work even in areas with minimal water in the air. The company envisions deploying “water harvester” devices at a village scale, with a tonne of MOF-303 capable of delivering hundreds of litres of water for approximately five years.

Conclusion

The use of AI in water production offers hope in tackling the global water crisis. By harnessing advanced materials like MOF-303, it becomes possible to extract drinkable water from the air, even in arid regions. This technology aligns with the Sustainable Development Goals (SDGs), particularly Goal 6: Clean Water and Sanitation. Atoco aims to deploy its first generation of “water harvester” devices within the next one to two years, bringing us one step closer to ensuring access to clean and sustainable water for all.

SDGs, Targets, and Indicators

1. SDG 6: Clean Water and Sanitation

   • Target 6.1: By 2030, achieve universal and equitable access to safe and affordable drinking water for all.
   • Indicator 6.1.1: Proportion of population using safely managed drinking water services.
   • Indicator 6.1.2: Proportion of population with access to safely managed sanitation services.

2. SDG 9: Industry, Innovation, and Infrastructure

   • Target 9.5: Enhance scientific research, upgrade the technological capabilities of industrial sectors in all countries, in particular developing countries, including, by 2030, encouraging innovation and substantially increasing the number of research and development workers per 1 million people and public and private research and development spending.
   • Indicator 9.5.1: Research and development expenditure as a proportion of GDP.

3. SDG 13: Climate Action

   • Target 13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters in all countries.
   • Indicator 13.1.1: Number of deaths, missing persons, and directly affected persons attributed to disasters per 100,000 population.

Analysis

1. SDG 6: Clean Water and Sanitation

   The article addresses the issue of access to clean water, which is a key aspect of SDG 6. It highlights the increasing problem of water scarcity and the potential of artificial intelligence to produce drinkable, clean water from the air. This aligns with Target 6.1 of achieving universal and equitable access to safe and affordable drinking water for all. The article also mentions the use of MOF-303, a water-absorbing compound, which can be considered as an indicator for measuring progress towards this target.

2. SDG 9: Industry, Innovation, and Infrastructure

   The article discusses the role of artificial intelligence in developing new compounds for water harvesting. This relates to SDG 9, which focuses on promoting innovation and upgrading technological capabilities. The use of AI in the research and development process aligns with Target 9.5, which aims to encourage innovation and increase research and development spending. The article implies that AI has helped scientists find new molecular structures, which can be considered as an indicator for measuring progress towards this target.

3. SDG 13: Climate Action

   The article mentions the potential of AI-enhanced systems to draw water from the air, even in arid regions. This can contribute to strengthening resilience and adaptive capacity to climate-related hazards and natural disasters, which is a key aspect of SDG 13. While the article does not explicitly mention any indicators related to this target, the development and deployment of such systems can be considered as indicators for measuring progress towards this target.

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Fuente: uk.news.yahoo.com

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