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The Journal of Physical Chemistry C, ISSN 1932-7447, 11/2019
Journal Article
International Journal of Quantum Chemistry, ISSN 0020-7608, 04/2016, Volume 116, Issue 8, pp. 569 - 572
Journal Article
ChemPhysChem, ISSN 1439-4235, 01/2014, Volume 15, Issue 1, pp. 61 - 63
One small step: Various Monte Carlo moves are utilized to generate optimal, user‐desired MTV‐MOF structures during a single simulation run. 
density functional calculations | metal‐organic frameworks | functional groups | computational chemistry | monte carlo | metal-organic frameworks | DESIGN | CARBON-DIOXIDE CAPTURE | METHANE STORAGE | PHYSICS, ATOMIC, MOLECULAR & CHEMICAL | CHEMISTRY, PHYSICAL | ZEOLITES | HYDROGEN STORAGE
Journal Article
Nature Communications, ISSN 2041-1723, 12/2017, Volume 8, Issue 1, pp. 1539 - 10
Journal Article
Science, ISSN 0036-8075, 8/2013, Volume 341, Issue 6148, pp. 882 - 885
We determined the heterogeneous mesoscale spatial apportionment of functional groups in a series of multivariate metal-organic frameworks (MTV-MOF-5)... 
Simulations | Crystal lattices | Adsorption | Isotherms | Spectral bands | REPORTS | Materials | Molecular dynamics | Materials science | Lattice energy | Functional groups | REDOR NMR | ECHO DOUBLE-RESONANCE | NMR-SPECTROSCOPY | MULTIDISCIPLINARY SCIENCES | Metals | Organic chemicals
Journal Article
Nature Chemistry, ISSN 1755-4330, 10/2012, Volume 4, Issue 10, pp. 810 - 816
During the formation of metal-organic frameworks (MOFs), metal centres can coordinate with the intended organic linkers, but also with solvent molecules. In... 
Thermodynamics | Carbon Dioxide - chemistry | Quantum Theory | Adsorption | Metals - chemistry | Organic Chemicals - chemistry | Monte Carlo Method
Journal Article
ISSN 2050-7488, 2/2019, Volume 7, Issue 6, pp. 279 - 2716
Performance limit is an important metric that can determine the commercial feasibility of a given class of materials. Here, an artificial neural network is... 
Journal Article
Journal of Materials Chemistry. A, Materials for Energy and Sustainability, ISSN 2050-7488, 01/2019, Volume 7, Issue 6, pp. 2709 - 2716
Performance limit is an important metric that can determine the commercial feasibility of a given class of materials. Here, an artificial neural network is... 
Methane | Work capacity | Storage | Computer simulation | Neural networks | Feasibility studies | Artificial neural networks | Performance prediction | Zeolite | Zeolites
Journal Article
Journal of Physical Chemistry. C, ISSN 1932-7447, 10/2017, Volume 121, Issue 44
Among various class of materials, metal organic frameworks (MOFs) are one of the most promising candidates for CO2 capture from flue gases. In particular,... 
Journal Article
ISSN 1463-9076, 5/2017, Volume 19, Issue 18, pp. 11639 - 11644
Metal-organic framework (MOF) and graphene oxide (GO) composite materials (MOF/GO) have been regarded as promising for separation applications due to their... 
Journal Article
by Shao, Yihan and Gan, Zhengting and Epifanovsky, Evgeny and Gilbert, Andrew T.B and Wormit, Michael and Kussmann, Joerg and Lange, Adrian W and Behn, Andrew and Deng, Jia and Feng, Xintian and Ghosh, Debashree and Goldey, Matthew and Horn, Paul R and Jacobson, Leif D and Kaliman, Ilya and Khaliullin, Rustam Z and Kuś, Tomasz and Landau, Arie and Liu, Jie and Proynov, Emil I and Rhee, Young Min and Richard, Ryan M and Rohrdanz, Mary A and Steele, Ryan P and Sundstrom, Eric J and Woodcock, H. Lee and Zimmerman, Paul M and Zuev, Dmitry and Albrecht, Ben and Alguire, Ethan and Austin, Brian and Beran, Gregory J. O and Bernard, Yves A and Berquist, Eric and Brandhorst, Kai and Bravaya, Ksenia B and Brown, Shawn T and Casanova, David and Chang, Chun-Min and Chen, Yunqing and Chien, Siu Hung and Closser, Kristina D and Crittenden, Deborah L and Diedenhofen, Michael and DiStasio, Robert A and Do, Hainam and Dutoi, Anthony D and Edgar, Richard G and Fatehi, Shervin and Fusti-Molnar, Laszlo and Ghysels, An and Golubeva-Zadorozhnaya, Anna and Gomes, Joseph and Hanson-Heine, Magnus W.D and Harbach, Philipp H.P and Hauser, Andreas W and Hohenstein, Edward G and Holden, Zachary C and Jagau, Thomas-C and Ji, Hyunjun and Kaduk, Benjamin and Khistyaev, Kirill and Kim, Jaehoon and Kim, Jihan and King, Rollin A and Klunzinger, Phil and Kosenkov, Dmytro and Kowalczyk, Tim and Krauter, Caroline M and Lao, Ka Un and Laurent, Adèle D and Lawler, Keith V and Levchenko, Sergey V and Lin, Ching Yeh and Liu, Fenglai and Livshits, Ester and Lochan, Rohini C and Luenser, Arne and Manohar, Prashant and Manzer, Samuel F and Mao, Shan-Ping and Mardirossian, Narbe and Marenich, Aleksandr V and Maurer, Simon A and Mayhall, Nicholas J and Neuscamman, Eric and Oana, C. Melania and Olivares-Amaya, Roberto and O'Neill, Darragh P and Parkhill, John A and Perrine, Trilisa M and Peverati, Roberto and Prociuk, Alexander and Rehn, Dirk R and Rosta, Edina and Russ, Nicholas J and Sharada, Shaama M and Sharma, Sandeep and Small, David W and Sodt, Alexander and ...
Molecular Physics, ISSN 0026-8976, 01/2015, Volume 113, Issue 2, pp. 184 - 215
Journal Article
Journal of Computational Chemistry, ISSN 0192-8651, 12/2016, Volume 37, Issue 32, pp. 2808 - 2815
Journal Article
ACS Nano, ISSN 1936-0851, 09/2015, Volume 9, Issue 9, pp. 9314 - 9321
Journal Article
Advanced Materials, ISSN 0935-9648, 2016, Volume 28, Issue 32, pp. 7020 - 7028
Journal Article
The Journal of Physical Chemistry C, ISSN 1932-7447, 10/2016, Volume 120, Issue 41, pp. 23500 - 23510
Using grand canonical Monte Carlo simulations, computational screening of hundreds of pure silica zeolites were conducted to identify materials that show... 
CRYSTALLINE POROUS MATERIALS | STRUCTURE-PROPERTY RELATIONSHIPS | MATERIALS SCIENCE, MULTIDISCIPLINARY | CHEMISTRY, PHYSICAL | NANOSCIENCE & NANOTECHNOLOGY | POTENTIAL FUNCTIONS | METAL-ORGANIC FRAMEWORKS | CARBON-DIOXIDE CAPTURE | EQUILIBRIUM | LIQUID WATER | GAS | SHAPE SELECTIVITY | SEPARATION
Journal Article
Journal Article