Inspired by biological systems, materials scientists have long sought to harness self-assembly to build nanomaterials. The challenge: the process seemed random and notoriously difficult to predict.

Solve two Atwood machine problems step by step, including the effects of friction and an inclined plane. Learn how to set up free-body diagrams, apply Newton’s laws, and avoid common mistakes in ...

Tessellations aren’t just eye-catching patterns—they can be used to crack complex mathematical problems. By repeatedly ...

Exotic hypothetical particles known as axions could potentially be produced inside a nuclear reactor, something The Big Bang ...

Artificial intelligence is changing how we predict river flow—but a new study led by researchers at the University of British ...

Calculating the maximum force between two electric charges! ⚡🔋 In this video, we’ll break down how to calculate the maximum force between two point charges using Coulomb’s Law. Understand the ...

On the telecommunications side, 6G remains firmly in its study phase. On the AI side, demand is real and growing.

It took 125 years, but in 2025 a team of mathematicians discovered the solution to a long-puzzling problem about the ...

Abstract: In recent years, deep learning-based methods have been introduced for solving inverse scattering problems (ISPs), but most of them heavily rely on large training datasets and suffer from ...

Abstract: Solving Maxwell's equations is crucial in various fields, like electromagnetic scattering and antenna design optimization. Physics-informed neural networks (PINNs) have shown powerful ...

Ramanujan’s elegant formulas for calculating pi, developed more than a century ago, have unexpectedly resurfaced at the heart of modern physics. Researchers at IISc discovered that the same ...