Results 51 to 60 of about 137,804 (303)

Towards Defect Phase Diagrams: From Research Data Management to Automated Workflows

Advanced Engineering Materials, EarlyView.
A research data management infrastructure is presented for the systematic integration of heterogeneous experimental and simulation data required for defect phase diagrams. The approach combines openBIS with a companion application for large‐object storage, automated metadata extraction, provenance tracking and federated data access, thereby supporting ...
Khalil Rejiba, Sang‐Hyeok Lee, Christina Gasper, Martina Freund, Sandra Korte‐Kerzel, Ulrich Kerzel   +5 more
wiley   +1 more source

Thermodynamics of Fluid Elements in the Context of Turbulent Isothermal Self-Gravitating Molecular Clouds in Virial Equilibrium

Universe
In this paper, we continue the study of the thermodynamics of fluid elements in isothermal turbulent self-gravitating systems, presented by molecular clouds. We build the model again on the hypothesis that, locally, the turbulent kinetic energy per fluid
Sava D. Donkov, Ivan Zhivkov Stefanov, Valentin Kopchev   +2 more
doaj   +1 more source

CS, HC3N and CH3CCH multi-line analyses towards starburst galaxies. The evolution of cloud structures in the central regions of galaxies

, 2010
We aim to study the properties of the dense molecular gas towards the inner few 100 pc of four nearby starburst galaxies dominated both by photo dissociation regions (M82) and large-scale shocks (NGC253, IC342 and Maffei2), and to relate the chemical and
Aladro, Rebeca, Bayet, Estelle, Martin, Sergio, Martin-Pintado, Jesus, Mauersberger, Rainer   +4 more
core   +1 more source

Enhancing Low‐Temperature Performance of Sodium‐Ion Batteries via Anion‐Solvent Interactions

Advanced Functional Materials, EarlyView.
DOL is introduced into electrolytes as a co‐solvent, increasing slat solubility, ion conductivity, and the de‐solvent process, and forming an anion‐rich solvent shell due to its high interaction with anion. With the above virtues, the batteries using this electrolyte exhibit excellent cycling stability at low temperatures. Abstract Sodium‐ion batteries
Cheng Zheng, Qian Yao, Yanan Sun, Hongyu Lv, Zhongchao Bai, Guoliang Zhang, Nana Wang, Jian Yang   +7 more
wiley   +1 more source

The Correlation Between Dust and Gas Contents in Molecular Clouds

The Astronomical Journal
Molecular clouds are regions of dense gas and dust in space where new stars and planets are born. There is a strong correlation between the distribution of dust and molecular gas in molecular clouds.
Rui-Zhi Li, Bing-Qiu Chen, Guang-Xing Li, Bo-Ting Wang, Hao-Ming Ren, Qi-Ning Guo   +5 more
doaj   +1 more source

Understanding the Kinetic Energy Deposition within Molecular Clouds

The Astrophysical Journal, 2023
According to the structures traced by ^13 CO spectral lines within ^12 CO molecular clouds (MCs), we investigate the contributions of their internal gas motions and relative motions to the total velocity dispersions of ^12 CO MCs. Our samples of 2851 ^12
Lixia Yuan, Ji Yang, Fujun Du, Yang Su, Shaobo Zhang, Qing-Zeng Yan, Yan Sun, Xin Zhou, Xuepeng Chen, Hongchi Wang, Zhiwei Chen   +10 more
doaj   +1 more source

Galaxy chemical evolution models: The role of molecular gas formation [PDF]

, 2017
In our classical grid of multiphase chemical evolution models, star formation in the disc occurs in two steps: first, molecular gas forms, and then stars are created by cloud-cloud collisions or interactions of massive stars with the surrounding ...
Ascasibar, Yago, Díaz, Angeles I., Díaz, Ángeles I., Gibson, Brad K., Mollá, Mercedes   +4 more
core   +2 more sources

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Molecular Clouds as Cosmic Ray Laboratories

, 2011
We will here discuss how the gamma-ray emission from molecular clouds can be used to probe the cosmic ray flux in distant regions of the Galaxy and to constrain the highly unknown cosmic ray diffusion coefficient. In particular we will discuss the GeV to
Aharonian, Felix A., Casanova, Sabrina, Fukui, Yasuo, Gabici, Stefano, Jones, David I., Kawamura, Akiko, Onishi, Toshikazu, Rowell, Gavin, Sano, Hidetoshi, Torii, Kazufumi, Volpe, Francesca, Yamamoto, Hiroaki   +11 more
core   +1 more source

Evolving Molecular Cloud Structure and the Column Density Probability Distribution Function [PDF]

, 2014
The structure of molecular clouds can be characterized with the probability distribution function (PDF) of the mass surface density. In particular, the properties of the distribution can reveal the nature of the turbulence and star formation present ...
Sills, Alison, Wadsley, James, Ward, Rachel L.   +2 more
core   +1 more source