jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Kristof T. Schütt | Michael Gastegger | Alexandre Tkatchenko | K. Müller | Reinhard J. Maurer
Source: Nature Communications (article, 2019-11-15)
Field: Materials Science — Materials Chemistry

Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions Machine learning advances chemistry and materials science by enabling large-scale exploration of chemical space based on quantum chemical calculations. While these models supply fast and accurate predictions of atomistic chemical properties, they do not explicitly capture the electronic degrees of freedom of a molecule, which limits their applicability for reactive chemistry and chemical analysis. Here we present a deep learning framework for the prediction of the quantum mechanical wavefunction in a local basis of atomic orbitals from which all other ground-state properties can be derived. This approach retains full access to the electronic structure via the wavefunction at force-field-like efficiency and captures quantum mechanics in an analytically differentiable representation. On several examples, we demonstrate that this opens promising avenues to perform inverse design of molecular structures for targeting electronic property optimisation and a clear path towards increased synergy of machine learning and quantum chemistry. Wave function ; Quantum chemistry ; Differentiable function ; Electronic structure ; Atomic orbital ; Computer science ; Quantum ; Chemical space ; Representation (politics) ; Statistical physics ; Quantum mechanics ; Chemistry ; Artificial intelligence ; Physics ; Molecule ; Mathematics ; Drug discovery ; Electron Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: Akansha Dager | Takashi Uchida | Toru Maekawa | Masaru Tachibana
Source: Scientific Reports (article, 2019-09-30)
Field: Materials Science — Materials Chemistry

Synthesis and characterization of Mono-disperse Carbon Quantum Dots from Fennel Seeds: Photoluminescence analysis using Machine Learning Herein, we present the synthesis of mono-dispersed C-QDs via single-step thermal decomposition process using the fennel seeds (Foeniculum vulgare). As synthesized C-QDs have excellent colloidal, photo-stability, environmental stability (pH) and do not require any additional surface passivation step to improve the fluorescence. The C-QDs show excellent PL activity and excitation-independent emission. Synthesis of excitation-independent C-QDs, to the best of our knowledge, using natural carbon source via pyrolysis process has never been achieved before. The effect of reaction time and temperature on pyrolysis provides insight into the synthesis of C-QDs. We used Machine-learning techniques (ML) such as PCA, MCR-ALS, and NMF-ARD-SO in order to provide a plausible explanation for the origin of the PL mechanism of as-synthesized C-QDs. ML techniques are capable of handling and analyzing the large PL data-set, and institutively recommend the best excitation wavelength for PL analysis. Mono-disperse C-QDs are highly desirable and have a range of potential applications in bio-sensing, cellular imaging, LED, solar cell, supercapacitor, printing, and sensors. Fluorescence ; Materials science ; Photoluminescence ; Passivation ; Quantum dot ; Pyrolysis ; Excitation ; Thermal stability ; Carbon fibers ; Thermal decomposition ; Nanotechnology ; Computer science ; Chemical engineering ; Optoelectronics ; Chemistry ; Optics ; Organic chemistry Carbon and Quantum Dots Applications ; Nanocluster Synthesis and Applications ; Quantum Dots Synthesis And Properties
Authors: Alauddin Ahmed | Saona Seth | Justin Purewal | Antek G. Wong‐Foy | Mike Veenstra | Adam J. Matzger | Donald J. Siegel
Source: Nature Communications (article, 2019-04-05)
Field: Chemistry — Inorganic Chemistry

Exceptional hydrogen storage achieved by screening nearly half a million metal-organic frameworks Few hydrogen adsorbents balance high usable volumetric and gravimetric capacities. Although metal-organic frameworks (MOFs) have recently demonstrated progress in closing this gap, the large number of MOFs has hindered the identification of optimal materials. Here, a systematic assessment of published databases of real and hypothetical MOFs is presented. Nearly 500,000 compounds were screened computationally, and the most promising were assessed experimentally. Three MOFs with capacities surpassing that of IRMOF-20, the record-holder for balanced hydrogen capacity, are demonstrated: SNU-70, UMCM-9, and PCN-610/NU-100. Analysis of trends reveals the existence of a volumetric ceiling at ∼40 g H<sub>2</sub> L<sup>-1</sup>. Surpassing this ceiling is proposed as a new capacity target for hydrogen adsorbents. Counter to earlier studies of total hydrogen uptake in MOFs, usable capacities in the highest-capacity materials are negatively correlated with density and volumetric surface area. Instead, capacity is maximized by increasing gravimetric surface area and porosity. This suggests that property/performance trends for total capacities may not translate to usable capacities. Hydrogen storage ; Metal-organic framework ; Computer science ; Hydrogen ; Materials science ; Environmental science ; Chemistry ; Organic chemistry Metal-Organic Frameworks: Synthesis and Applications ; Hydrogen Storage and Materials ; Covalent Organic Framework Applications
Authors: Zhijie Chen | Sylvia L. Hanna | Louis R. Redfern | Dalal Alezi | Timur İslamoğlu | Omar K. Farha
Source: Coordination Chemistry Reviews (article, 2019-02-10)
Field: Chemistry — Inorganic Chemistry

Reticular chemistry in the rational synthesis of functional zirconium cluster-based MOFs Zirconium ; Chemistry ; Reticular connective tissue ; Nanotechnology ; Cluster (spacecraft) ; Rational design ; Cluster chemistry ; Cyclopentadienyl complex ; Molecule ; Organic chemistry ; Computer science ; Materials science ; Catalysis Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications ; Magnetism in coordination complexes
Authors: Matthew J. West | James W. B. Fyfe | Julien C. Vantourout | Allan J. B. Watson
Source: Chemical Reviews (review, 2019-11-22)
Field: Chemistry — Organic Chemistry

Mechanistic Development and Recent Applications of the Chan–Lam Amination Transition metal-mediated formation of C-N bonds is an essential synthetic methodology. The discovery of the Chan-Lam amination provided a C-N bond forming process that was mild, convenient, and inexpensive, offering an alternative to complementary methods using other transition metals (TMs). Over the past 20 years, this reaction has seen considerable development in its scope of application, uptake into industry, and understanding of its mechanism. This review provides an account of the development of the Chan-Lam amination, highlighting progress and notable examples of application since 2011. Focus is given to evolution in mechanistic understanding and selected applications of the methodology within medicinal and process chemistry. Chemistry ; Amination ; Biochemical engineering ; Combinatorial chemistry ; Nanotechnology ; Organic chemistry ; Catalysis Catalytic Cross-Coupling Reactions ; Chemical Synthesis and Analysis ; Asymmetric Hydrogenation and Catalysis
Authors: Archismita Misra | Károly Kozma | Carsten Streb | May Nyman
Source: Angewandte Chemie International Edition (review, 2019-07-01)
Field: Materials Science — Materials Chemistry

Beyond Charge Balance: Counter‐Cations in Polyoxometalate Chemistry Polyoxometalates (POMs) are molecular metal-oxide anions applied in energy conversion and storage, manipulation of biomolecules, catalysis, as well as materials design and assembly. Although often overlooked, the interplay of intrinsically anionic POMs with organic and inorganic cations is crucial to control POM self-assembly, stabilization, solubility, and function. Beyond simple alkali metals and ammonium, chemically diverse cations including dendrimers, polyvalent metals, metal complexes, amphiphiles, and alkaloids allow tailoring properties for known applications, and those yet to be discovered. This review provides an overview of fundamental POM-cation interactions in solution, the resulting solid-state compounds, and behavior and properties that emerge from these POM-cation interactions. We will explore how application-inspired research has exploited cation-controlled design to discover new POM materials, which in turn has led to the quest for fundamental understanding of POM-cation interactions. Polyoxometalate ; Chemistry ; Nanotechnology ; Amphiphile ; Alkali metal ; Dendrimer ; Combinatorial chemistry ; Catalysis ; Organic chemistry ; Materials science ; Polymer Polyoxometalates: Synthesis and Applications ; Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications
Authors: Ryan J. Hickey | Andrew E. Pelling
Source: Frontiers in Bioengineering and Biotechnology (review, 2019-03-22)
Field: Materials Science — Biomaterials

Cellulose Biomaterials for Tissue Engineering In this review, we highlight the importance of nanostructure of cellulose-based biomaterials to allow cellular adhesion, the contribution of nanostructure to macroscale mechanical properties, and several key applications of these materials for fundamental scientific research and biomedical engineering. Different features on the nanoscale can have macroscale impacts on tissue function. Cellulose is a diverse material with tunable properties and is a promising platform for biomaterial development and tissue engineering. Cellulose-based biomaterials offer some important advantages over conventional synthetic materials. Here we provide an up-to-date summary of the status of the field of cellulose-based biomaterials in the context of bottom-up approaches for tissue engineering. We anticipate that cellulose-based material research will continue to expand because of the diversity and versatility of biochemical and biophysical characteristics highlighted in this review. Biomaterial ; Cellulose ; Tissue engineering ; Context (archaeology) ; Nanotechnology ; Materials science ; Bacterial cellulose ; Biomedical engineering ; Engineering ; Chemical engineering ; Biology Advanced Cellulose Research Studies ; Electrospun Nanofibers in Biomedical Applications ; biodegradable polymer synthesis and properties
Authors: Constantin Mircioiu | Victor Voicu | Valentina Anuța | Andra Tudose | Christian Celia | Donatella Paolino | Massimo Fresta | Roxana Colette Sandulovici | Ion Mircioiu
Source: Pharmaceutics (review, 2019-03-21)
Field: Materials Science — Biomaterials

Mathematical Modeling of Release Kinetics from Supramolecular Drug Delivery Systems Embedding of active substances in supramolecular systems has as the main goal to ensure the controlled release of the active ingredients. Whatever the final architecture or entrapment mechanism, modeling of release is challenging due to the moving boundary conditions and complex initial conditions. Despite huge diversity of formulations, diffusion phenomena are involved in practically all release processes. The approach in this paper starts, therefore, from mathematical methods for solving the diffusion equation in initial and boundary conditions, which are further connected with phenomenological conditions, simplified and idealized in order to lead to problems which can be analytically solved. Consequently, the release models are classified starting from the geometry of diffusion domain, initial conditions, and conditions on frontiers. Taking into account that practically all solutions of the models use the separation of variables method and integral transformation method, two specific applications of these methods are included. This paper suggests that "good modeling practice" of release kinetics consists essentially of identifying the most appropriate mathematical conditions corresponding to implied physicochemical phenomena. However, in most of the cases, models can be written but analytical solutions for these models cannot be obtained. Consequently, empiric models remain the first choice, and they receive an important place in the review. Drug delivery ; Kinetics ; Supramolecular chemistry ; Chemistry ; Drug ; Pharmacology ; Nanotechnology ; Computer science ; Medicine ; Materials science ; Organic chemistry ; Molecule ; Physics Nanoparticle-Based Drug Delivery ; Drug Solubulity and Delivery Systems ; Advanced Drug Delivery Systems
Authors: Patrick Brisebois | Mohamed Siaj
Source: Journal of Materials Chemistry C (review, 2019-12-10)
Field: Materials Science — Materials Chemistry

Harvesting graphene oxide – years 1859 to 2019: a review of its structure, synthesis, properties and exfoliation A benchmark guide for tailoring graphene oxide from a practical viewpoint. Graphene ; Materials science ; Oxide ; Exfoliation joint ; Benchmark (surveying) ; Nanotechnology ; Graphene oxide paper ; Metallurgy Graphene research and applications ; Graphene and Nanomaterials Applications ; Advancements in Battery Materials
Authors: Jonas Matern | Yeray Dorca | Luis Sánchez | Gustavo Fernández
Source: Angewandte Chemie International Edition (review, 2019-07-04)
Field: Materials Science — Biomaterials

Revising Complex Supramolecular Polymerization under Kinetic and Thermodynamic Control Pathway complexity, hierarchical organization, out of equilibrium, and metastable or kinetically trapped species are common terms widely used in recent, high-quality publications in the field of supramolecular polymers. Often, the terminologies used to describe the different self-assembly pathways, the species involved, as well as their relationship and relative stability are not trivial. Different terms and classifications are commonly found in the literature, however, in many cases, without clear definitions or guidelines on how to use them and how to determine them experimentally. The aim of this Minireview is to classify, differentiate, and correlate the existing concepts with the help of recent literature reports to provide the reader with a general insight into thermodynamic and kinetic aspects of complex supramolecular polymerization processes. A good comprehension of these terms and concepts should contribute to the development of new complex, functional materials. Supramolecular chemistry ; Metastability ; Polymerization ; Computer science ; Comprehension ; Kinetic control ; Chemistry ; Nanotechnology ; Polymer ; Materials science ; Molecule Supramolecular Self-Assembly in Materials ; Supramolecular Chemistry and Complexes ; Polydiacetylene-based materials and applications
Authors: Christian C. Nadell | Bohao Huang | Jordan M. Malof | Willie J. Padilla
Source: Optics Express (article, 2019-09-16)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Deep learning for accelerated all-dielectric metasurface design Deep learning has risen to the forefront of many fields in recent years, overcoming challenges previously considered intractable with conventional means. Materials discovery and optimization is one such field, but significant challenges remain, including the requirement of large labeled datasets and one-to-many mapping that arises in solving the inverse problem. Here we demonstrate modeling of complex all-dielectric metasurface systems with deep neural networks, using both the metasurface geometry and knowledge of the underlying physics as inputs. Our deep learning network is highly accurate, achieving an average mean square error of only 1.16 × 10<sup>-3</sup> and is over five orders of magnitude faster than conventional electromagnetic simulation software. We further develop a novel method to solve the inverse modeling problem, termed fast forward dictionary search (FFDS), which offers tremendous controls to the designer and only requires an accurate forward neural network model. These techniques significantly increase the viability of more complex all-dielectric metasurface designs and provide opportunities for the future of tailored light matter interactions. Computer science ; Deep learning ; Artificial neural network ; Inverse problem ; Inverse ; Field (mathematics) ; Dielectric ; Software ; Artificial intelligence ; Implementation ; Computer engineering ; Algorithm ; Physics ; Mathematics ; Geometry Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Millimeter-Wave Propagation and Modeling
Authors: Yujing Ren | Yan Tang | Leilei Zhang | Xiaoyan Liu | Lin Li | Shu Miao | Dang Sheng Su | Aiqin Wang | Jun Li | Tao Zhang
Source: Nature Communications (article, 2019-10-03)
Field: Materials Science — Materials Chemistry

Unraveling the coordination structure-performance relationship in Pt1/Fe2O3 single-atom catalyst Heterogeneous single-atom catalyst (SAC) opens a unique entry to establishing structure-performance relationship at the molecular level similar to that in homogeneous catalysis. The challenge lies in manipulating the coordination chemistry of single atoms without changing single-atom dispersion. Here, we develop an efficient synthetic method for SACs by using ethanediamine to chelate Pt cations and then removing the ethanediamine by a rapid thermal treatment (RTT) in inert atmosphere. The coordination chemistry of Pt single atoms on a Fe<sub>2</sub>O<sub>3</sub> support is finely tuned by merely adjusting the RTT temperature. With the decrease in Pt-O coordination number, the oxidation state of Pt decreases, and consequently the hydrogenation activity increases to a record level without loss of chemoselectivity. The tunability of the local coordination chemistry, oxidation states of the metal, and the catalytic performance of single atoms reveals the unique role of SACs as a bridge between heterogeneous and homogeneous catalysis. Atom (system on chip) ; Catalysis ; Chemistry ; Crystallography ; Computer science ; Biochemistry Catalytic Processes in Materials Science ; Electrocatalysts for Energy Conversion ; Nanomaterials for catalytic reactions
Authors: Wenhao Sun | Christopher J. Bartel | Elisabetta Arca | Sage R. Bauers | Bethany E. Matthews | Bernardo Orvañanos | Bor-Rong Chen | Michael F. Toney | Laura T. Schelhas | William Tumas | Janet Tate | Andriy Zakutayev | Stephan Lany | Aaron M. Holder | Gerbrand Ceder
Source: Nature Materials (article, 2019-06-17)
Field: Materials Science — Materials Chemistry

A map of the inorganic ternary metal nitrides Ternary operation ; Nitride ; Materials science ; Density functional theory ; Metastability ; Chemical physics ; Chemical stability ; Nanotechnology ; Chemistry ; Computational chemistry ; Computer science Machine Learning in Materials Science ; Inorganic Chemistry and Materials ; MXene and MAX Phase Materials
Authors: Mohamed Rachid Tchalala | Prashant M. Bhatt | Karumbaiah N. Chappanda | Sérgio R. Tavares | Karim Adil | Youssef Belmabkhout | Aleksander Shkurenko | Amandine Cadiau | Nicolas Heymans | Guy De Weireld | Guillaume Maurin | K. Saláma | Mohamed Eddaoudi
Source: Nature Communications (article, 2019-03-22)
Field: Chemistry — Inorganic Chemistry

Fluorinated MOF platform for selective removal and sensing of SO2 from flue gas and air Conventional SO<sub>2</sub> scrubbing agents, namely calcium oxide and zeolites, are often used to remove SO<sub>2</sub> using a strong or irreversible adsorption-based process. However, adsorbents capable of sensing and selectively capturing this toxic molecule in a reversible manner, with in-depth understanding of structure-property relationships, have been rarely explored. Here we report the selective removal and sensing of SO<sub>2</sub> using recently unveiled fluorinated metal-organic frameworks (MOFs). Mixed gas adsorption experiments were performed at low concentrations ranging from 250 p.p.m. to 7% of SO<sub>2</sub>. Direct mixed gas column breakthrough and/or column desorption experiments revealed an unprecedented SO<sub>2</sub> affinity for KAUST-7 (NbOFFIVE-1-Ni) and KAUST-8 (AlFFIVE-1-Ni) MOFs. Furthermore, MOF-coated quartz crystal microbalance transducers were used to develop sensors with the ability to detect SO<sub>2</sub> at low concentrations ranging from 25 to 500 p.p.m. Quartz crystal microbalance ; Adsorption ; Flue gas ; Desorption ; Materials science ; Metal-organic framework ; Chemical engineering ; Molecule ; Oxide ; Nanotechnology ; Chemistry ; Organic chemistry Metal-Organic Frameworks: Synthesis and Applications ; Gas Sensing Nanomaterials and Sensors ; Molecular Sensors and Ion Detection
Authors: Parvarish Sharma | Meenu Mehta | Daljeet Singh Dhanjal | Simran Kaur | Gaurav Gupta | Harjeet Singh | Lakshmi Thangavelu | S. Rajeshkumar | Murtaza M. Tambuwala | Hamid A. Bakshi | Dinesh Kumar Chellappan | Kamal Dua | Saurabh Satija
Source: Chemico-Biological Interactions (review, 2019-06-18)
Field: Materials Science — Biomaterials

Emerging trends in the novel drug delivery approaches for the treatment of lung cancer Nanocarriers ; Drug delivery ; Lung cancer ; Medicine ; Cancer ; Drug ; Treatment of lung cancer ; Targeted drug delivery ; Nanotechnology ; Pharmacology ; Oncology ; Internal medicine ; Materials science Nanoparticle-Based Drug Delivery ; Advanced biosensing and bioanalysis techniques ; Dendrimers and Hyperbranched Polymers
Authors: Derek J. Durand | Natalie Fey
Source: Chemical Reviews (review, 2019-02-25)
Field: Chemistry — Inorganic Chemistry

Computational Ligand Descriptors for Catalyst Design Ligands, especially phosphines and carbenes, can play a key role in modifying and controlling homogeneous organometallic catalysts, and they often provide a convenient approach to fine-tuning the performance of known catalysts. The measurable outcomes of such catalyst modifications (yields, rates, selectivity) can be set into context by establishing their relationship to steric and electronic descriptors of ligand properties, and such models can guide the discovery, optimization, and design of catalysts. In this review we present a survey of calculated ligand descriptors, with a particular focus on homogeneous organometallic catalysis. A range of different approaches to calculating steric and electronic parameters are set out and compared, and we have collected descriptors for a range of representative ligand sets, including 30 monodentate phosphorus(III) donor ligands, 23 bidentate P,P-donor ligands, and 30 carbenes, with a view to providing a useful resource for analysis to practitioners. In addition, several case studies of applications of such descriptors, covering both maps and models, have been reviewed, illustrating how descriptor-led studies of catalysis can inform experiments and highlighting good practice for model comparison and evaluation. Steric effects ; Chemistry ; Denticity ; Catalysis ; Ligand (biochemistry) ; Homogeneous ; Context (archaeology) ; Organometallic chemistry ; Homogeneous catalysis ; Electronic effect ; Combinatorial chemistry ; Computational chemistry ; Biochemical engineering ; Stereochemistry ; Organic chemistry ; Thermodynamics ; Metal Asymmetric Hydrogenation and Catalysis ; Chemical Synthesis and Analysis ; Machine Learning in Materials Science