In materials science, particularly in the study of glasses, the intermediate range order (IRO) is one of the most intriguing research areas owing to its significant influence over the physical properties of glasses.
By modifying the genomes of plants and microorganisms, synthetic biologists can design biological systems that meet a specification, such as producing valuable chemical compounds, making bacteria sensitive to light, or programming ...
Strongly interacting systems play an important role in quantum physics and quantum chemistry. Stochastic methods such as Monte Carlo simulations are a proven method for investigating such systems. However, these methods reach ...
An international research team from Innsbruck and Geneva has, for the first time, probed the dimensional crossover for ultracold quantum matter. In the regime between one and two dimensions, the quantum particles perceive ...
Quantum many-body systems are things such as atomic nuclei that consist of many tiny particles moving in complex ways. This makes it extremely difficult to predict how the systems behave as the particles interact. To study ...
A new automated workflow developed by scientists at Lawrence Berkeley National Laboratory (Berkeley Lab) has the potential to allow researchers to analyze the products of their reaction experiments in real time, a key capability ...
Entanglement is a widely studied quantum physics phenomenon, in which two particles become linked in such a way that the state of one affects the state of another, irrespective of the distance between them. When studying ...
Conventional nuclear measurement techniques, such as Monte Carlo simulations, are known for their extensive computational demands and prolonged processing times, especially when applied to unconventional reservoirs characterized ...
Ammonia (NH3) is an important molecule with many applications. The end product of the famed Haber–Bosch process, it is commonly synthesized to capture nitrogen for fertilizers, and is used for refrigeration, in cleaning ...
Generative AI techniques, machine learning, and simulations give researchers new opportunities to identify environmentally friendly metal-organic framework materials.
