228,754 Works

PERMOS DATABASE - BOREHOLE TEMPERATURE DATA FROM THE SWISS PERMAFROST MONITORING NETWORK

Swiss Permafrost Monitoring Network (PERMOS)
Instruments: thermistor chains

Swiss national forest inventory - Result table No. 197769

M. Huber, M. Keller, R. Meile, A. Herold-Bonardi, U.-B. Brändli, B. Vidondo, S. Speich, B. Traub, C. Fischer, F. Cioldi, E. Rösler & M. Abegg

Forest Type NFI

Christian Ginzler & Lars Waser
This dataset presents an remote sensing based approach for a countrywide mapping of broadleaved and coniferous trees in Switzerland with a spatial resolution of 3 m. The classification approach incorporates a random forest classifier, explanatory variables from multispectral aerial imagery and a Digital Terrain Model (DTM) from Airborne Laser Scanning (ALS) data, digitized training polygons and independent validation data from the National Forest Inventory (NFI). Whereas high model overall accuracies (0.99) and kappa (0.98) were...

Unified theory of thermal transport in crystals and disordered solids

Francesco Mauri, Michele Simoncelli & Nicola Marzari
Crystals and glasses exhibit fundamentally different heat conduction mechanisms: the periodicity of crystals allows for the excitation of propagating vibrational waves that carry heat, as first discussed by Peierls; in glasses, the lack of periodicity breaks Peierls' picture and heat is mainly carried by the coupling of vibrational modes, often described by a harmonic theory introduced by Allen and Feldman. Anharmonicity or disorder are thus the limiting factors for thermal conductivity in crystals or glasses;...

Ab initio thermodynamics of liquid and solid water: supplemental materials

Edgar Engel, Jörg Behler, Bingqing Cheng, Christoph Dellago & Michele Ceriotti
Thermodynamic properties of liquid water as well as hexagonal (Ih) and cubic (Ic) ice are predicted based on density functional theory at the hybrid-functional level, rigorously taking into account quantum nuclear motion, anharmonic fluctuations and proton disorder. This is made possible by combining advanced free energy methods and state-of-the-art machine learning techniques. The ab initio description leads to structural properties in excellent agreement with experiments, and reliable estimates of the melting points of light and...

Data-driven design and synthesis of metal-organic frameworks for wet flue gas CO2 capture

Kyriakos C. Stylianou, Peter George Boyd, Thomas D. Daff, Berend Smit, Richard Bounds, Tom K. Woo, Seyed Mohamad Moosavi, Jorge A. R. Navarro, Jeffrey A. Reimer, Arunraj Chidambaram, Pascal Schouwink & Andrzej Gładysiak
In this entry is a database of 324,426 hypothetical Metal-Organic Frameworks (MOFs) that were used in a study to screen potential carbon dioxide scrubbers. Using a method to assemble these materials with topological blueprints, we only selected materials that could be accurately represented with the MEPO-QEq charge generation method. By ensuring that the electrostatic potential is accurately represented in these materials, screening for CO2 adsorption properties would result very few false positives/negatives. The atom-centered charges...

The Influence of Intrinsic Framework Flexibility on Adsorption in Nanoporous Materials (Data Download)

Sudi Jawahery, Peter G. Boyd, Berend Smit, Matthew Witman, Maciej Haranczyk, Sanliang Ling & Ben Slater
Project Abstract: For applications of metal-organic frameworks (MOFs) such as gas storage and separation, flexibility is often seen as a parameter that can tune material performance. In this work we aim to determine the optimal flexibility for the shape selective separation of similarly sized molecules (e.g., Xe/Kr mixtures). To obtain systematic insight into how the flexibility impacts this type of separation we develop a simple analytical model that predicts a material's Henry regime adsorption and...

Machine learning meets volcano plots: Computational discovery of cross-coupling catalysts

O. Anatole Von Lilienfeld, Benjamin Meyer, Clémence Corminboeuf, Boodsarin Sawatlon & Stefan Niklaus Heinen
The application of modern machine learning to challenges in atomistic simulation is gaining attraction. We present new machine learning models that can predict the energy of the oxidative addition process between a transition metal complex and a substrate for C-C cross-coupling reaction. In turn, this quantity can be used as a descriptor to estimate the activity of homogeneous catalysts using molecular volcano plots. The versatility of this approach is illustrated for vast libraries of organometallic...

Generating carbon schwarzites via zeolite-templating

Igor A. Baburin, Efrem Braun, Davide M. Proserpio, Seyed Mohamad Moosavi, Yongjin Lee, Rocio Mercado, Senja Barthel & Berend Smit
Zeolite-templated carbons (ZTCs) comprise a relatively recent material class synthesized via the chemical vapor deposition of a carbon-containing precursor on a zeolite template, followed by the removal of the template. We have developed a theoretical framework to generate a ZTC model from any given zeolite structure, which we show can successfully predict the structure of known ZTCs. We use our method to generate a library of ZTCs from all known zeolites, to establish criteria for...

In Silico Design of 2D and 3D Covalent Organic Frameworks for Methane Storage Applications

Berend Smit, Rocio Mercado, Rueih-Sheng Fu, Leopold Talirz, Aliaksandr V. Yakutovich & Maciej Haranczyk
Here we present 69,840 covalent organic frameworks (COFs) assembled in silico from a set of 666 distinct organic linkers into 2D-layered and 3D configurations. We investigate the feasibility of using these frameworks for methane storage by using grand-canonical Monte Carlo (GCMC) simulations to calculate their deliverable capacities (DCs). From these calculations, we predict that the best structure in the database is linker91_C_linker91_C_tbd, a structure composed of carbon-carbon bonded triazine linkers in the tbd topology. This...

Capturing chemical intuition in synthesis of metal-organic frameworks

Kyriakos C. Stylianou, Seyed Mohamad Moosavi, Leopold Talirz, Maciej Haranczyk, Arunraj Chidambaram & Berend Smit
We report a methodology using machine learning to capture chemical intuition from a set of (partially) failed attempts to synthesize a metal organic framework. We define chemical intuition as the collection of unwritten guidelines used by synthetic chemists to find the right synthesis conditions. As (partially) failed experiments usually remain unreported, we have reconstructed a typical track of failed experiments in a successful search for finding the optimal synthesis conditions that yields HKUST-1 with the...

Evaluating charge equilibration methods to generate electrostatic fields in nanoporous materials

Amber K. Mace, Seda Keskin, Ozge Kadioglu, Peter G. Boyd, Daniele Ongari & Berend Smit
Charge equilibration (Qeq) methods can estimate the electrostatic potential of molecules and periodic frameworks by assigning point charges to each atom, using only a small fraction of the resources needed to compute density functional (DFT)-derived charges. This makes possible, for example, the computational screening of thousands of microporous structures to assess their performance for the adsorption of polar molecules. Recently, different variants of the original Qeq scheme were proposed to improve the quality of the...

In Silico Design of 2D and 3D Covalent Organic Frameworks for Methane Storage Applications

Aliaksandr V. Yakutovich, Leopold Talirz, Berend Smit, Maciej Haranczyk, Rocio Mercado & Rueih-Sheng Fu
Here we present 69,840 covalent organic frameworks (COFs) assembled in silico from a set of 666 distinct organic linkers into 2D-layered and 3D configurations. We investigate the feasibility of using these frameworks for methane storage by using grand-canonical Monte Carlo (GCMC) simulations to calculate their deliverable capacities (DCs). From these calculations, we predict that the best structure in the database is linker91_C_linker91_C_tbd, a structure composed of carbon-carbon bonded triazine linkers in the tbd topology. This...

High-throughput computational screening of nanoporous adsorbents for CO 2 capture from natural gas

Alexander F. Zurhelle, Li-Chiang Lin, Jihan Kim, Sondre Schnell, Berend Smit, Efrem Braun, Wouter Thijssen & Joshua A. Thompson
With the growth of natural gas as an energy source, upgrading CO2-contaminated supplies has become increasingly important. Here we develop a single metric that captures how well an adsorbent performs the separation of CH4 and CO2, and we then use this metric to computationally screen tens of thousands of all-silica zeolites. We show that the most important predictors of separation performance are the CO2 heat of adsorption (Qst, CO2) and the CO2 saturation loading capacity....

The geometric blueprint of perovskites

Marina R. Filip & Feliciano Giustino
Perovskite minerals form an essential component of the Earth’s mantle, and synthetic crystals are ubiquitous in electronics, photonics, and energy technology. The extraordinary chemical diversity of these crystals raises the question of how many and which perovskites are yet to be discovered. Here we show that the “no-rattling” principle postulated by Goldschmidt in 1926, describing the geometric conditions under which a perovskite can form, is much more effective than previously thought and allows us to...

Ab initio electronic structure of liquid water: Molecular dynamics snapshots

Giacomo Miceli, Alfredo Pasquarello, Francesco Ambrosio & Wei Chen
This entry provides the snapshots of liquid water generated with ab initio molecular dynamics using rVV10 density functional at room temperature. Nuclear quantum effects are taken into account through path-integral molecular dynamics simulations.

Two-dimensional materials from high-throughput computational exfoliation of experimentally known compounds

Giovanni Pizzi, Nicola Marzari, Philippe Schwaller, Nicolas Mounet, Ivano E. Castelli, Thibault Sohier, Antimo Marrazzo, Davide Campi, Andrea Cepellotti, Marco Gibertini & Andrius Merkys
Two-dimensional (2D) materials have emerged as promising candidates for next-generation electronic and optoelectronic applications. Yet, only a few dozens of 2D materials have been successfully synthesized or exfoliated. Here, we search for novel 2D materials that can be easily exfoliated from their parent compounds. Starting from 108423 unique, experimentally known three-dimensional compounds we identify a subset of 5619 that appear layered according to robust geometric and bonding criteria. High-throughput calculations using van-der-Waals density-functional theory, validated...

Barcodes for nanoporous materials

Kathryn Hess, S. Mohamad Moosavi, Paweł Dłotko, Senja D. Barthel, Yongjin Lee & Berend Smit
In most applications of nanoporous materials the pore structure is as important as the chemical composition as a determinant of performance. For example, one can alter performance in applications like carbon capture or methane storage by orders of magnitude by only modifying the pore structure. For these applications it is therefore important to identify the optimal pore geometry and use this information to find similar materials. However, the mathematical language and tools to identify materials...

Predicting Product Distribution of Propene Dimerization in Nanoporous Materials (Data Download)

Berend Smit & Yifei Michelle Liu
Project abstract: In this work, a theoretical framework is developed to explain and predict changes in the product distribution of the propene dimerization reaction, which yields a mixture of C6 olefin isomers, resulting from the use of different porous materials as catalysts. The MOF-74 class of materials has shown promise in catalyzing the dimerization of propene with high selectivity for valuable linear olefin products. We show that experimentally observed changes in the product distribution can...

Synthesis of Metal-Organic Frameworks: capturing chemical intuition

Kyriakos C. Stylianou, Leopold Talirz, Maciej Haranczyk, Seyed Mohamad Moosavi, Arunraj Chidambaram & Berend Smit
We report a methodology using machine learning to capture chemical intuition from a set of (partially) failed attempts to synthesize a metal organic framework. We define chemical intuition as the collection of unwritten guidelines used by synthetic chemists to find the right synthesis conditions. As (partially) failed experiments usually remain unreported, we have reconstructed a typical track of failed experiments in a successful search for finding the optimal synthesis conditions that yields HKUST-1 with the...

Mail-order metal-organic frameworks (MOFs): designing isoreticular MOF-5 analogues comprising commercially available organic molecules

Kuldeep Jariwala, Li-Chiang Lin, Berend Smit, Richard L. Martin & Maciej Haranczyk
Metal–organic frameworks (MOFs), a class of porous materials, are of particular interest in gas storage and separation applications due largely to their high internal surface areas and tunable structures. MOF-5 is perhaps the archetypal MOF; in particular, many isoreticular analogues of MOF-5 have been synthesized, comprising alternative dicarboxylic acid ligands. In this contribution we introduce a new set of hypothesized MOF-5 analogues, constructed from commercially available organic molecules. We describe our automated procedure for hypothetical...

A Standard Solid State Pseudopotentials (SSSP) library optimized for precision and efficiency (Version 1.1, data download)

Ivano E. Castelli, Nicolas Mounet, Antimo Marrazzo, Nicola Marzari & Gianluca Prandini
Despite the enormous success and popularity of density functional theory, systematic verification and validation studies are still very limited both in number and scope. Here, we propose a universal standard protocol to verify publicly available pseudopotential libraries, based on several independent criteria including verification against all-electron equations of state and plane-wave convergence tests for phonon frequencies, band structure, cohesive energy and pressure. Adopting these criteria we obtain two optimal pseudopotential sets, namely the Standard Solid...

Isobaric-Isothermal Monte Carlo Simulations of Bulk Liquid Water from MP2 and RPA Theory (MC Trajectories Data Download)

Juerg Hutter, Mauro Del Ben & Joost VandeVondele
Methods based on the second order Møller–Plesset perturbation theory (MP2) and the Random Phase Approximation (RPA) have emerged as practicable and reliable approaches to improve the accuracy of density functional approximations for first principle atomistic simulations. Such approaches are in fact capable to account ab-initio for non-local dynamical electron correlation effects, which play a fundamental role, for example, in the description of non-bonded interactions. To assess the performance of MP2 and RPA for real applications,...

Coupled-Cluster Polarizabilities in the QM7b and a Showcase Database

Yang Yang, Michele Ceriotti, DiStasio Jr., Robert A., David M. Wilkins, Andrea Grisafi & Ka Un Lao
Dipole polarizabilities, computed using linear response coupled cluster theory and density functional theory (using d-aug-cc-pVDZ basis set), for 7211 molecules from the QM7b dataset of small molecules and for 52 molecules from a showcase dataset.

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