scholarly journals Machine Learning Prediction of Metal‐Organic Framework Guest Accessibility from Linker and Metal Chemistry

Author(s):  
Rémi Pétuya ◽  
Samantha Durdy ◽  
Dmytro Antypov ◽  
Michael W Gaultois ◽  
Neil G Berry ◽  
...  
2021 ◽  
Author(s):  
Rémi Pétuya ◽  
Samantha Durdy ◽  
Dmytro Antypov ◽  
Michael W Gaultois ◽  
Neil G Berry ◽  
...  

2020 ◽  
Vol 78 (5) ◽  
pp. 427
Author(s):  
Chengzhi Cai ◽  
Lifeng Li ◽  
Xiaomei Deng ◽  
Shuhua Li ◽  
Hong Liang ◽  
...  

Nanomaterials ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 467 ◽  
Author(s):  
Wenyuan Yang ◽  
Hong Liang ◽  
Feng Peng ◽  
Zili Liu ◽  
Jie Liu ◽  
...  

The Monte Carlo and molecular dynamics simulations are employed to screen the separation performance of 6013 computation-ready, experimental metal–organic framework membranes (CoRE-MOFMs) for 15 binary gas mixtures. After the univariate analysis, principal component analysis is used to reduce 44 performance metrics of 15 mixtures to a 10-dimension set. Then, four machine learning algorithms (decision tree, random forest, support vector machine, and back propagation neural network) are combined with k times repeated k-fold cross-validation to predict and analyze the relationships between six structural feature descriptors and 10 principal components. Based on the linear correlation value R and the root mean square error predicted by the machine learning algorithm, the random forest algorithm is the most suitable for the prediction of the separation performance of CoRE-MOFMs. One descriptor, pore limiting diameter, possesses the highest weight importance for each principal component index. Finally, the 30 best CoRE-MOFMs for each binary gas mixture are screened out. The high-throughput computational screening and the microanalysis of high-dimensional performance metrics can provide guidance for experimental research through the relationships between the multi-structure variables and multi-performance variables.


2021 ◽  
Author(s):  
Jintong Liu ◽  
Jing Huang ◽  
Lei Zhang ◽  
Jianping Lei

We review the general principle of the design and functional modulation of nanoscaled MOF heterostructures, and biomedical applications in enhanced therapy.


2020 ◽  
Author(s):  
Jesse Park ◽  
Brianna Collins ◽  
Lucy Darago ◽  
Tomce Runcevski ◽  
Michael Aubrey ◽  
...  

<b>Materials that combine magnetic order with other desirable physical attributes offer to revolutionize our energy landscape. Indeed, such materials could find transformative applications in spintronics, quantum sensing, low-density magnets, and gas separations. As a result, efforts to design multifunctional magnetic materials have recently moved beyond traditional solid-state materials to metal–organic solids. Among these, metal–organic frameworks in particular bear structures that offer intrinsic porosity, vast chemical and structural programmability, and tunability of electronic properties. Nevertheless, magnetic order within metal–organic frameworks has generally been limited to low temperatures, owing largely to challenges in creating strong magnetic exchange in extended metal–organic solids. Here, we employ the phenomenon of itinerant ferromagnetism to realize magnetic ordering at <i>T</i><sub>C</sub> = 225 K in a mixed-valence chromium(II/III) triazolate compound, representing the highest ferromagnetic ordering temperature yet observed in a metal–organic framework. The itinerant ferromagnetism is shown to proceed via a double-exchange mechanism, the first such observation in any metal–organic material. Critically, this mechanism results in variable-temperature conductivity with barrierless charge transport below <i>T</i><sub>C</sub> and a large negative magnetoresistance of 23% at 5 K. These observations suggest applications for double-exchange-based coordination solids in the emergent fields of magnetoelectrics and spintronics. Taken together, the insights gleaned from these results are expected to provide a blueprint for the design and synthesis of porous materials with synergistic high-temperature magnetic and charge transport properties. </b>


2019 ◽  
Author(s):  
Timothée Stassin ◽  
Ivo Stassen ◽  
Joao Marreiros ◽  
Alexander John Cruz ◽  
Rhea Verbeke ◽  
...  

A simple solvent- and catalyst-free method is presented for the synthesis of the mesoporous metal-organic framework (MOF) MAF-6 (RHO-Zn(eIm)2) based on the reaction of ZnO with 2-ethylimidazole vapor at temperatures ≤ 100 °C. By translating this method to a chemical vapor deposition (CVD) protocol, mesoporous crystalline films could be deposited for the first time entirely from the vapor phase. A combination of PALS and Kr physisorption measurements confirmed the porosity of these MOF-CVD films and the size of the MAF-6 supercages (diam. ~2 nm), in close agreement with powder data and calculations. MAF-6 powders and films were further characterized by XRD, TGA, SEM, FTIR, PDF and EXAFS. The exceptional uptake capacity of the mesoporous MAF-6 in comparison to the microporous ZIF-8 is demonstrated by vapor-phase loading of a molecule larger than the ZIF-8 windows.


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