Results 91 to 100 of about 5,223 (263)

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Machine Learning Approach to Analyze the Heavy Quark Diffusion Coefficient in Relativistic Heavy Ion Collisions. [PDF]

Entropy (Basel), 2023
Guo R, Li Y, Chen B.
europepmc   +1 more source

Chiral symmetry and heavy-ion collisions [PDF]

Journal of Physics G: Nuclear and Particle Physics, 2008
Plenary talk at Quark Matter 2008: 20th International Conference on Ultra-Relativistic Nucleus Nucleus Collisions (QM 2008), Jaipur, India, 4-10 Feb ...
openaire   +2 more sources

Challenges and enablers in fluidization technology

AIChE Journal, EarlyView.
Abstract Gas–solid fluidized beds provide excellent heat and mass transfer for high‐throughput operations from coating to catalytic conversion and underpin emerging low‐carbon technologies. Yet industrial reliability, scale‐up, and control lag scientific understanding, particularly as finer, stickier, and more variable feedstocks increasingly challenge
J. Ruud van Ommen, Jia Wei Chew
wiley   +1 more source

The Spectrum of Low-p_TJ/ψ in Heavy-Ion Collisions in a Statistical Two-Body Fractal Model. [PDF]

Entropy (Basel), 2023
Ding H, Cheng L, Dai T, Wang E, Zhang WN.   +4 more
europepmc   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

An Experimental Review on Heavy-Flavor v2 in Heavy-Ion Collision

Advances in High Energy Physics, 2016
For over a decade now, the primary purpose of relativistic heavy-ion collisions at the Relativistic Heavy-Ion Collider (RHIC) and the Large Hadron Collider (LHC) has been to study the properties of QCD matter under extreme conditions—high temperature and
Md. Nasim, Roli Esha, Huan Zhong Huang
doaj   +1 more source

Hydrodynamic attractors in heavy ion collisions: a review. [PDF]

Eur Phys J C Part Fields, 2022
Soloviev A.
europepmc   +1 more source

Heavy ion collisions

Annual Review of Nuclear and Particle Science, 2018
Heavy ion collisions quickly form a droplet of quark-gluon plasma (QGP) with a remarkably small viscosity. We give an accessible introduction to how to study this smallest and hottest droplet of liquid made on Earth and why it is so interesting. The physics of heavy ion collisions ranges from highly energetic quarks and gluons described by perturbative
Busza, Wit, Rajagopal, Krishna, Van Der Schee, Wilke   +2 more
openaire   +1 more source

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source