Things aren't great, but there are a few positive signs, we promise. Climate news hasn't been great in 2025. Global greenhouse-gas emissions hit record highs (again). This year is set to be either the second or third warmest on record. Climate-fueled disasters like wildfires in California and flooding in Indonesia and Pakistan devastated communities and caused billions in damage. In addition to these worrying indicators of our continued contributions to climate change and their obvious effects, the world's largest economy has made a sharp U-turn on climate policy this year.

Directed energy is "the ability to create a high amount of energy in a controlled volume at a given distance in order to trigger physical reactions to study the interaction between the energy and the matter," says Dr. Chaouki Kasmi, who is the Chief Researcher at DERC, which is part of the Abu Dhabi government's Advanced Technology Research Council. The research at DERC reflects the multitude of applications that are possible using directed energy, but the research projects have at least one thing in common: the goal of solving real-world scientific or technical challenges. For example, one of DERC's recent developments is a landmine detection system – the ground-penetrating radar - designed to help developing or previously war-torn countries detect and neutralize unexploded landmines. They have their sights set much higher and further with projects focused on using lasers for communications on land, to the moon, and even underwater--truly making the entire world a better place with directed energy technology. "The disruptive innovation that we are bringing today is how we can make it affordable for developing countries. The idea is to create a technology that could really help solve a worldwide problem at low cost. And this is very important for us as we would like to have the system deployed at scale," says Dr. Kasmi.

Maëva Ghonda is a scientist born in Kinshasa, the great capital city of the Democratic Republic of Congo (DRC). Maëva is the editor-in-chief of the IEEE Quantum Computing Newsletter, the host of the Quantum AI Series Podcast, and the chair of the Quantum AI Institute. As a research scientist, her work is centered on technological innovations -- i.e. Quantum Computing, Artificial Intelligence and Machine Learning -- to tackle challenges in Pharma and Healthcare (e.g. Maëva Ghonda's passion for quantum computing ignited while working as Joint Quantum Institute Scholar.

Catalysts are materials that trigger or speed up chemical reactions.

But deep learning has limitations, especially when it comes to predicting highly complex chemical interactions—a necessary part of finding materials …

Hongliang Xin, an associate professor of chemical engineering in the College of Engineering, and his collaborators have devised a new artificial intelligence framework that can accelerate discovery of materials for important technologies, such as fuel cells and carbon capture devices. Titled "Infusing theory into deep learning for interpretable reactivity prediction," their paper in the journal Nature Communications details a new approach called TinNet--short for theory-infused neural network--that combines machine-learning algorithms and theories for identifying new catalysts. Catalysts are materials that trigger or speed up chemical reactions. TinNet is based on deep learning, also known as a subfield of machine learning, which uses algorithms to mimic how human brains work. The 1996 victory of IBM's Deep Blue computer over world chess champion Garry Kasparov was one of the first advances in machine learning.

Hongliang Xin, an associate professor of chemical engineering in the College of Engineering, and his collaborators have devised a new artificial intelligence framework that can accelerate discovery of materials for important technologies, such as fuel cells and carbon capture devices. Titled "Infusing theory into deep learning for interpretable reactivity prediction," their paper in the journal Nature Communications details a new approach called TinNet -- short for theory-infused neural network -- that combines machine-learning algorithms and theories for identifying new catalysts. Catalysts are materials that trigger or speed up chemical reactions. TinNet is based on deep learning, also known as a subfield of machine learning, which uses algorithms to mimic how human brains work. The 1996 victory of IBM's Deep Blue computer over world chess champion Garry Kasparov was one of the first advances in machine learning.

An increasing number of countries, companies and regions are embracing sustainable energy generation and the landscape is rapidly evolving. Here are 6 renewable energy trends to watch in the coming year. Renewable energy is booming in China.Getty Energy storage plays an important role in balancing power supply and demand, and is key to tackling the intermittency issues of renewable energy. Pairing a storage system with a renewable energy source ensures a smooth and steady power supply, even when weather conditions are not optimal for energy generation. Batteries are the most common storage devices used in renewable energy systems and their use is increasing on both the residential and grid-wide scale.

Organizations are looking at how AI and IoT can reduce cost, drive efficiencies, and enhance competitive advantage and support emerging business models. It is also clearly observed that some technical innovations from the mainstream of the IT world, or from other industries, are creating opportunities to leverage technology that did not exist previously in the industry. The industry has, in the past, pursued a siloed approach to applications and technologies. This is characterized by the separation of the engineering and operations groups from IT, and the use of stand-alone, best-of-breed applications within the overall scope of IT. As ubiquitous connectivity continues to permeate technology sectors, an increasing need to unite energy technologies, operational technologies (such as sensors and smart devices) and IT (such as big data, advanced analytics and asset performance management [APM]) with consumer technologies (such as social and mobile) is observed in the industry.

LONDON -- The government is putting cutting edge technologies such as artificial intelligence (AI), 5G wireless internet, "smart" energy technology, and robotics at the heart of its new post-Brexit industrial strategy. Theresa May is set to launch the government's "Modern Industrial Strategy" on Monday at a regional meeting of the cabinet in the North West. The Prime Minister announced in a release on Sunday evening that the strategy would be focused around ten key strategic pillars, the first of which is: "Investing in science, research, and innovation." The government says that a £4.7 billion increase in research & development (R&D) funding announced in last year's Autumn Statement is central to the new industrial strategy. This investment will go to areas such as AI, "smart" energy technology, robotics, and 5G wireless, the only specific industries name-checked in the release.