Results 161 to 170 of about 2,364,994 (254)

Unveiling Mechanisms of SEI Formation and Sodium Loss in Sodium Batteries via Interface Reactor Sampling

Advanced Science, EarlyView.
An “Interface Reactor” strategy boosts simulation stability by 2–3 orders of magnitude, enabling stable 100 ns molecular dynamics of electrode‐electrolyte interfaces. Distinct SEI formation mechanisms are revealed: mixed co‐formation in carbonates versus surface‐energy‐controlled NaF crystallization in ethers. Metadynamics simulations further elucidate
Zhoulin Liu, Ziliang Wang, Zherui Chen, Jianchun Sha, Fengzijun Pan, Pingyang Zhang, Yinghe Zhang   +6 more
wiley   +1 more source

Faster and more accurate assessment of differential transcript expression with Gibbs sampling and edgeR v4. [PDF]

NAR Genom Bioinform
Baldoni PL, Chen L, Smyth GK.
europepmc   +1 more source

GSMC: Combining Parallel Gibbs Sampling with Maximal Cliques for Hunting DNA Motif. [PDF]

J Comput Biol, 2017
Pei C, Wang SL, Fang J, Zhang W.
europepmc   +1 more source

Structural change in the forward discount: a Bayesian analysis of forward rate unbiasedness hypothesis [PDF]

Using Bayesian methods, we reexamine the empirical evidence from Sakoulis et al. (2010) regarding structural breaks in the forward discount for G-7 countries.
Yi-Chi Chen, Wei-Choun Yu
core  

Intrinsic Phonons as a Dynamic Control Knob for Catalytic Reactivity in 2D Materials

Advanced Science, EarlyView.
Intrinsic phonon excitations are demonstrated to serve as a dynamic control knob for catalytic reactivity in 2D materials. Mode‐selective lattice vibrations reconstruct the electronic structure, lower oxygen evolution reaction barriers, establishing a phonon‐engineering paradigm for dynamically regulating electrocatalysis beyond conventional static ...
Kai Ren, Feifan Wang, Yong‐Wei Zhang, Tianyang Liu, Liangzhi Kou, Yu Jing   +5 more
wiley   +1 more source

Gibbs sampling with JAGS: behind the scenes

, 2017
Gibbs sampling is a Bayesian inference technique that is used in various scientific domains to generate samples from a certain posterior probability density function, given experimental data.
Coro G
core  

Metal Active‐Site Exposure via Ligand Engineering Boosts CO2‐to‐Ethylene Conversion on Cu18 Nanoclusters

Advanced Science, EarlyView.
Through quantitative ligand stripping of [Cu18H17(PR3)10]+ nanoclusters via intramolecular interaction modulation, selectivity for CO2 electroreduction to C2H4 is significantly enhanced. The weakly coordinating ligand triggers dual‐ligand stripping (FEC2H4 = 70.59%), whereas the strongly coordinating ligand results in single‐ligand retention (FEC2H4 ...
Ziqi Chen, Yang Zuo, Yu Zhu, Shuo Zhang, Along Ma, Shiyin Yang, Zhengmao Yin, Xiaoshuang Ma, Shuxin Wang   +8 more
wiley   +1 more source

Identification of differentially expressed molecular functions associated with breast cancer using Gibbs sampling. [PDF]

Oncol Lett, 2017
Zhou G, Lu MQ, Li DJ, Gao BA, Guo R.
europepmc   +1 more source

Neural network approximations to posterior densities: an analytical approach [PDF]

In Hoogerheide, Kaashoek and Van Dijk (2002) the class of neural networksampling methods is introduced to sample from a target (posterior)distribution that may be multi-modal or skew, or exhibit strong correlationamong the parameters.
Hoogerheide, L.F., Dijk, H.K. van, Kaashoek, J.F.   +2 more
core  

Bond‐Competition‐Driven Enhancement of Surface Basicity and Interfacial Interaction to Boost Photocatalytic Syngas Production

Advanced Science, EarlyView.
A synergetic surface bond competition−hybridization approach was developed to synthesize high‐performance CO2 adsorbents and syngas production photocatalysts via the sulfurization‐driven control of surface basicity and interfacial coupling. The ZnIn2S4−sulfur‐doped MgO/MgAl2O4 nanocomposites showed outstanding photocatalytic efficiency for production ...
Dong Wook Lee, Wenjing Dong, Nam Hee Kwon, Taehoon Kim, In Young Kim, Yun Kyung Jo, Xiaoyan Jin, Ajayan Vinu, Yufei Zhao, Seong‐Ju Hwang   +9 more
wiley   +1 more source