In density functional theory, the charge density is the core attribute of atomic systems from which all chemical properties can be derived.

To address this, we leverage parametric modular structure to learn component-level surrogates, enabling cheaper high-fidelity simulation. We use a neural network to model the stored potential energy in a component given boundary conditions.

Every day, 50,000 mattresses are tossed in the trash in the United States. A relative of penicillin could be the cure. Breakthroughs, discoveries, and DIY tips sent six days a week. Shopping for a new mattress can be stressful--this is something you plan to sleep on for years to come, after all. But your old one can be its own problem for the environment .

Wild fluctuations in the price of gold continued on Wednesday as geopolitical tensions reignited after the US downed an Iranian drone . The precious metal, which is seen as a so-called safe haven for investors in times of uncertainty, shot back above $5,000 (£3,650) an ounce following days of sharp falls. Gold prices had been propelled to record highs by rapid changes in US trade policy, ongoing geopolitical uncertainty and conflict and central banks increasing their purchases of bullion. Wednesday's jump, to $5,061 per ounce, left the price of gold around 80% higher than the same time a year ago. A US military spokesman confirmed the Iranian drone had been shot down after it aggressively approached an American aircraft carrier in the Arabian Sea. Tehran has not commented on Tuesday's incident.

In a pine forest on Michigan's Upper Peninsula, the only active nickel mine in the US is nearing the end of its life. At a time when carmakers want the metal for electric-vehicle batteries, nickel concentration at Eagle Mine is falling and could soon drop too low to warrant digging. Demand for nickel, copper, and rare earth elements is rapidly increasing amid the explosive growth of metal-intensive data centers, electric cars, and renewable energy projects. But producing these metals is becoming harder and more expensive because miners have already exploited the best resources. Here's how biotechnology could help . What we've been getting wrong about AI's truth crisis What would it take to convince you that the era of truth decay we were long warned about--where AI content dupes us, shapes our beliefs even when we catch the lie, and erodes societal trust in the process--is now here?

The performance of machine learning surrogates is critically dependent on data quality and quantity. This presents a major challenge, as high-fidelity (HF) data is often scarce and computationally expensive to acquire, while low-fidelity (LF) data is abundant but less accurate. To address this data-scarcity problem, we develop a probabilistic multi-fidelity surrogate framework based on generative transfer learning. We employ a normalizing flow (NF) generative model as the backbone, which is trained in two phases: (i) the NF is first pretrained on a large LF dataset to learn a probabilistic forward model; (ii) the pretrained model is then fine-tuned on a small HF dataset, allowing it to correct for LF-HF discrepancies via knowledge transfer. To relax the dimension-preserving constraint of standard bijective NFs, we integrate surjective (dimension-reducing) layers with standard coupling blocks. This architecture enables learned dimension reduction while preserving the ability to train with exact likelihoods. The resulting surrogate provides fast probabilistic predictions with quantified uncertainty and significantly outperforms LF-only baselines while using fewer HF evaluations. We validate the approach on a reinforced concrete slab benchmark, combining many coarse-mesh (LF) simulations with a limited set of fine-mesh (HF) simulations. The proposed model achieves probabilistic predictions with HF accuracy, demonstrating a practical path toward data-efficient, generative AI-driven surrogates for complex engineering systems. Email address: David.Barajas-Solano@pnnl.gov (David Barajas-Solano) Introduction High-fidelity (HF) computer modeling using discretization schemes such as the finite elements (FE) method provides a rigorous framework for analyzing and predicting the behavior of complex engineering systems.

The specialized crops could save farmers millions. A swarm of desert locusts fly after an aircraft sprayed pesticide in Meru, Kenya in 2021. Breakthroughs, discoveries, and DIY tips sent six days a week. Swarms of locusts devouring a farmer's livelihood might sound apocalyptic, but major locust infestations are a regular problem in agricultural communities around the world. These locust swarms--dense, droning packs of certain grasshopper species--can cover hundreds of square miles, and the insects consume vast amounts of vegetation and threaten global agriculture.

Chemist Omar Yaghi invented materials called MOFs, a few grams of which have the surface area of a football field. In school, we learn about the Stone Age, the Bronze Age - and we are currently in a silicon age characterised by computers and phones. What might define the next age? Omar Yaghi at the University of California, Berkeley, thinks a family of materials he helped pioneer in the 1990s has a good shot. They are metal-organic frameworks (MOFs), and working out how to make them earned him a share of the 2025 Nobel prize in chemistry .