jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Lance Phillip L. Mosca | Andrew B. Gapan | Rica Angela Angeles | Edgar Clyde R. Lopez
Source:  (article, 2023-11-15)
Field: Chemistry — Inorganic Chemistry

Stability of Metal–Organic Frameworks: Recent Advances and Future Trends In recent years, metal–organic frameworks (MOFs) have gained a lot of attention from researchers because of their potential applications in gas separation, storage, catalysis, as well as sensing. In spite of this, further development for the actual utilization of this material is hindered mainly by its lack of ability to withstand harsh conditions. Advances over the past few years have made it possible to create MOFs with greater variability and structural properties that are more robust in nature. This paper focuses on the development of synthesis and design of MOFs so as to attain robust frameworks that are relevant for various applications. Finally, this paper also discusses the possible future directions of study for synthesizing highly durable MOFs. Metal-organic framework ; Nanotechnology ; Biochemical engineering ; Computer science ; Risk analysis (engineering) ; Systems engineering ; Engineering ; Materials science ; Business ; Chemistry Metal-Organic Frameworks: Synthesis and Applications ; Advanced Nanomaterials in Catalysis ; Dendrimers and Hyperbranched Polymers
Authors: Liang Qiu | Xinyue Han | Chengfen Xing | Ulrich Glebe
Source: Small (review, 2023-02-03)
Field: Chemistry — Organic Chemistry

Polymerization‐Induced Self‐Assembly: An Emerging Tool for Generating Polymer‐Based Biohybrid Nanostructures The combination of biomolecules and synthetic polymers provides an easy access to utilize advantages from both the synthetic world and nature. This is not only important for the development of novel innovative materials, but also promotes the application of biomolecules in various fields including medicine, catalysis, and water treatment, etc. Due to the rapid progress in synthesis strategies for polymer nanomaterials and deepened understanding of biomolecules' structures and functions, the construction of advanced polymer-based biohybrid nanostructures (PBBNs) becomes prospective and attainable. Polymerization-induced self-assembly (PISA), as an efficient and versatile technique in obtaining polymeric nano-objects at high concentrations, has demonstrated to be an attractive alternative to existing self-assembly procedures. Those advantages induce the focus on the fabrication of PBBNs via the PISA technique. In this review, current preparation strategies are illustrated based on the PISA technique for achieving various PBBNs, including grafting-from and grafting-through methods, as well as encapsulation of biomolecules during and subsequent to the PISA process. Finally, advantages and drawbacks are discussed in the fabrication of PBBNs via the PISA technique and obstacles are identified that need to be overcome to enable commercial application. Biomolecule ; Nanotechnology ; Materials science ; Polymer ; Polymerization ; Nanomaterials ; Nanostructure ; Fabrication ; Self-assembly Advanced Polymer Synthesis and Characterization ; biodegradable polymer synthesis and properties ; Polymer Surface Interaction Studies
Authors: Maria Leila Popa | Manuela Daniela Preda | Ionela Andreea Neacșu | Alexandru Mihai Grumezescu | Octav Ginghină
Source: International Journal of Molecular Sciences (review, 2023-01-18)
Field: Materials Science — Materials Chemistry

Traditional vs. Microfluidic Synthesis of ZnO Nanoparticles Microfluidics provides a precise synthesis of micro-/nanostructures for various applications, including bioengineering and medicine. In this review article, traditional and microfluidic synthesis methods of zinc oxide (ZnO) are compared concerning particle size distribution, morphology, applications, reaction parameters, used reagents, and microfluidic device materials. Challenges of traditional synthesis methods are reviewed in a manner where microfluidic approaches may overcome difficulties related to synthesis precision, bulk materials, and reproducibility. Microfluidics ; Nanotechnology ; Materials science ; Nanoparticle ; Particle size ; Chemical engineering ; Engineering ZnO doping and properties ; Innovative Microfluidic and Catalytic Techniques Innovation ; Biosensors and Analytical Detection
Authors: Hongde Yu | Thomas Heine
Source: Journal of the American Chemical Society (article, 2023-08-23)
Field: Chemistry — Organic Chemistry

Magnetic Coupling Control in Triangulene Dimers Metal-free magnetism remains an enigmatic field, offering prospects for unconventional magnetic and electronic devices. In the pursuit of such magnetism, triangulenes, endowed with inherent spin polarization, are promising candidates to serve as monomers to construct extended structures. However, controlling and enhancing the magnetic interactions between the monomers persist as a significant challenge in molecular spintronics, as so far only weak antiferromagnetic coupling through the linkage has been realized, hindering their room temperature utilization. Herein, we investigate 24 triangulene dimers using first-principles calculations and demonstrate their tunable magnetic coupling (<i>J</i>), achieving unprecedented strong <i>J</i> values of up to -144 meV in a non-Kekulé dimer. We further establish a positive correlation between bandgap, electronic coupling, and antiferromagnetic interaction, thereby providing molecular-level insights into enhancing magnetic interactions. By twisting the molecular fragments, we demonstrate an effective and feasible approach to control both the sign and strength of <i>J</i> by tuning the balance between potential and kinetic exchanges. We discover that <i>J</i> can be substantially boosted at planar configurations up to -198 meV. We realize ferromagnetic coupling in nitrogen-doped triangulene dimers at both planar and largely twisted configurations, representing the first example of ferromagnetic triangulene dimers that cannot be predicted by the Ovchinnikov rule. This work thus provides a practical strategy for augmenting magnetic coupling and open up new avenues for metal-free ferromagnetism. Antiferromagnetism ; Magnetism ; Chemistry ; Spintronics ; Ferromagnetism ; Inductive coupling ; Coupling (piping) ; Condensed matter physics ; Planar ; Chemical physics ; Physics ; Materials science ; Quantum mechanics ; Computer science Synthesis and Properties of Aromatic Compounds ; Advanced Condensed Matter Physics ; Advanced NMR Techniques and Applications
Authors: Athanasios Koutsianos | Roman Pallach | Louis Frentzel‐Beyme | Chinmoy Das | Michael Paulus | Christian Sternemann | Sebastian Henke
Source: Nature Communications (article, 2023-07-14)
Field: Chemistry — Inorganic Chemistry

Breathing porous liquids based on responsive metal-organic framework particles Responsive metal-organic frameworks (MOFs) that display sigmoidal gas sorption isotherms triggered by discrete gas pressure-induced structural transformations are highly promising materials for energy related applications. However, their lack of transportability via continuous flow hinders their application in systems and designs that rely on liquid agents. We herein present examples of responsive liquid systems which exhibit a breathing behaviour and show step-shaped gas sorption isotherms, akin to the distinct oxygen saturation curve of haemoglobin in blood. Dispersions of flexible MOF nanocrystals in a size-excluded silicone oil form stable porous liquids exhibiting gated uptake for CO<sub>2</sub>, propane and propylene, as characterized by sigmoidal gas sorption isotherms with distinct transition steps. In situ X-ray diffraction studies show that the sigmoidal gas sorption curve is caused by a narrow pore to large pore phase transformation of the flexible MOF nanocrystals, which respond to gas pressure despite being dispersed in silicone oil. Given the established flexible nature and tunability of a range of MOFs, these results herald the advent of breathing porous liquids whose sorption properties can be tuned rationally for a variety of technological applications. Sorption ; Porosity ; Materials science ; Propane ; Metal-organic framework ; Chemical engineering ; Porous medium ; Silicone oil ; Silicone ; Nanotechnology ; Adsorption ; Chemistry ; Organic chemistry ; Composite material Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications ; Membrane Separation and Gas Transport
Authors: Alhulw H. Alshammari | Majed Alshammari | Mohammed Ibrahim | Khulaif Alshammari | T.A. Taha
Source: Polymers (article, 2023-01-29)
Field: Materials Science — Polymers and Plastics

New Hybrid PVC/PVP Polymer Blend Modified with Er2O3 Nanoparticles for Optoelectronic Applications Polymer blend hybrid nanocomposites are of great importance for future optoelectronic applications. This paper presents the preparation of new polymer blend hybrid nanocomposites based on PVC/PVP modified with Er<sub>2</sub>O<sub>3</sub> nanoparticles. A low-cost solution casting method has been used to prepare the polymer nanocomposites at 0.0, 0.1, 0.3 and 0.6 wt% of Er<sub>2</sub>O<sub>3</sub>. X-ray diffraction (XRD), Fourier transform infrared (FTIR), Raman spectroscopy, and environmental scanning electron microscopy (ESEM) measurements have all been used to examine the impact of a varying wt% of Er<sub>2</sub>O<sub>3</sub> on the structural and optical characteristics of PVP/PVC polymer blends. The PVC/PVP polymer blend and Er<sub>2</sub>O<sub>3</sub> nanoparticles showed a strong interaction, which was validated by XRD, FTIR, and Raman spectrum investigations. The SEM micrographs showed a remarkable complexation among the components of the polymer nanocomposites. The activation energies for thermal decomposition of PVC/PVP doped with different Er<sub>2</sub>O<sub>3</sub> concentrations were less than that of the pure polymer film. The linear and nonlinear refractive indexes, dispersion energy, optical susceptibility and the energy gap values were found to be Er<sub>2</sub>O<sub>3</sub> concentration-dependent. With an increase in Er<sub>2</sub>O<sub>3</sub> concentration to 0.1 and 0.3 wt%, the dispersion energy and nonlinear refractive index improved, and thereafter decreased when the concentration was further increased to 0.6For the film doped with 0.1 wt% Er<sub>2</sub>O<sub>3</sub>, the optical band gap (E<sub>opt</sub>) of the composite film enhanced by about 13%. The optical absorption measurements revealed clear improvements with the addition of erbium oxide. Higher refractive index values of PVC/PVP/Er<sub>2</sub>O<sub>3</sub> films qualify the polymer blend as a cladding for electro-optic modulators. Our results indicated that the PVC/PVP/Er<sub>2</sub>O<sub>3</sub> polymer films could be suitable for optoelectronic space applications. Materials science ; Polymer ; Fourier transform infrared spectroscopy ; Nanocomposite ; Raman spectroscopy ; Polymer nanocomposite ; Scanning electron microscope ; Polymer blend ; Band gap ; Refractive index ; Nanoparticle ; Dispersion (optics) ; Chemical engineering ; Analytical Chemistry (journal) ; Composite material ; Nanotechnology ; Optoelectronics ; Optics ; Chemistry ; Copolymer ; Organic chemistry Polymer Nanocomposite Synthesis and Irradiation ; Polymer Nanocomposites and Properties ; Polymer Science and PVC
Authors: Fu‐An Guo | Jing Wang | Cailing Chen | Xinglong Dong | Xingyu Li | Hao Wang | Peng Guo | Yu Han | Jing Li
Source: Angewandte Chemie International Edition (article, 2023-04-22)
Field: Chemistry — Inorganic Chemistry

Linker Vacancy Engineering of a Robust ftw‐type Zr‐MOF for Hexane Isomers Separation Discrimination of physically similar molecules by porous solids represents an important yet challenging task in industrially relevant chemical separations. Precisely controlled pore dimension and/or tailored pore surface functionality are crucial to achieve high-efficiency separation. Metal-organic frameworks (MOFs) are promising candidates for these challenging separations in light of their structural diversity as well as highly adjustable pore dimension/functionality. We report here a microporous, ftw-type Zr-based MOF structure, HIAM-410 (HIAM=Hoffmann Institute of Advanced Materials), built on hexanuclear Zr<sub>6</sub> cluster and pyrene-1,3,6,8-tetracarboxylate (ptc<sup>4-</sup> ). Its crystallographic structure has been determined using continuous rotation electron diffraction (cRED) technique combined with Rietveld refinement against powder X-ray diffraction data, aided by low-dose high-resolution transmission electron microscopy (HRTEM) imaging. The compound features exceptional framework stability that is comparable to the prototype MOF UiO-66. Interestingly, the linker vacancies in the pristine MOF structure could be partially restored by post-synthetic linker insertion. Its separation capability of hexane isomers is enhanced substantially upon the linker vacancy engineering. The restored structure exhibits efficient splitting of monobranched and dibranched hexane isomers at both room temperature and industrially relevant temperature. Linker ; Metal-organic framework ; Materials science ; High-resolution transmission electron microscopy ; Vacancy defect ; Hexane ; Microporous material ; Molecule ; Rietveld refinement ; Crystallography ; Porosity ; Chemical engineering ; Transmission electron microscopy ; Crystal structure ; Nanotechnology ; Chemistry ; Physical chemistry ; Organic chemistry ; Composite material Metal-Organic Frameworks: Synthesis and Applications ; Boron and Carbon Nanomaterials Research ; X-ray Diffraction in Crystallography
Authors: G. Huang | Tomasz Cierpicki | Jolanta Grembecka
Source: Bioorganic Chemistry (review, 2023-03-20)
Field: Chemistry — Organic Chemistry

2-Aminobenzothiazoles in anticancer drug design and discovery Chemistry ; Drug discovery ; Kinase ; Cyclin-dependent kinase ; Anticancer drug ; Drug ; Tyrosine kinase ; Pharmacology ; Computational biology ; Biochemistry ; Signal transduction ; Biology ; Cell cycle Synthesis and biological activity ; Enzyme function and inhibition ; Quinazolinone synthesis and applications
Authors: Vivek Johny | Ajith Kuriakose Mani | Sivasubramanian Palanisamy | Visakh Kunnathuparambil Rajan | Murugesan Palaniappan | Carlo Santulli
Source: Fibers (article, 2023-01-06)
Field: Materials Science — Biomaterials

Extraction and Physico-Chemical Characterization of Pineapple Crown Leaf Fibers (PCLF) Apart from the widely discussed pineapple leaf fibers, normally referred to as PALF, fibers from other parts of the plant also exist, particularly those in the fruit crown, which are known as pineapple crown leaf fibers (PCLF). In this work, PCLF were characterized using thermogravimetric analysis (TGA), Fourier transform IR spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and atomic force microscopy (AFM). The results indicated that the properties of PCLF do not greatly differ from those observed for PALF. In particular, a cellulose content of over 67% was observed, with approximately 76% crystallinity. The main degradation phenomena of the fibers took place between 230 and 380 °C, peaking at 324 °C, which is in line with observations in other fibers which have similar cellulose and crystalline contents. There was 13.4% residue at 680 °C. Bare mechanical retting of PCLF, although not allowing a full and thorough degumming, which would only be achieved through more aggressive chemical treatment, enabled aspect ratios of over 103 to be obtained. This indicates some potential for their application as short fibers in composites. In this respect, the considerable roughness of PCLF when compared to other leaf-extracted fibers, and in particular when compared to PALF, could suggest an ability to obtain a sufficiently sound fiber–matrix interface. Materials science ; Thermogravimetric analysis ; Crystallinity ; Fourier transform infrared spectroscopy ; Composite material ; Cellulose ; Fiber ; Scanning electron microscope ; Cellulose fiber ; Chemical engineering ; Engineering Advanced Cellulose Research Studies ; Natural Fiber Reinforced Composites ; Nanocomposite Films for Food Packaging
Authors: Lorenzo Castelli | Qing Zhu | Trevor J. Shimokusu | Geoff Wehmeyer
Source: Nature Communications (article, 2023-01-24)
Field: Materials Science — Materials Chemistry

A three-terminal magnetic thermal transistor Three-terminal thermal analogies to electrical transistors have been proposed for use in thermal amplification, thermal switching, or thermal logic, but have not yet been demonstrated experimentally. Here, we design and fabricate a three-terminal magnetic thermal transistor in which the gate temperature controls the source-drain heat flow by toggling the source-drain thermal conductance from ON to OFF. The centimeter-scale thermal transistor uses gate-temperature dependent magnetic forces to actuate motion of a thermally conducting shuttle, providing thermal contact between source and drain in the ON state while breaking contact in the OFF state. We measure source-drain thermal switch ratios of 109 ± 44 in high vacuum with gate switching temperatures near 25 °C. Thermal measurements show that small heat flows into the gate can be used to drive larger heat flows from source to drain, and that the switching is reversible over >150 cycles. Proof-of-concept thermal circuit demonstrations show that magnetic thermal transistors can enable passive or active heat flow routing or can be combined to create Boolean thermal logic gates. This work will allow thermal researchers to explore the behavior of nonlinear thermal circuits using three-terminal transistors and will motivate further research developing thermal transistors for advanced thermal control. Terminal (telecommunication) ; Transistor ; Thermal ; Computer science ; Physics ; Electrical engineering ; Telecommunications ; Engineering ; Voltage Thermal properties of materials ; Thermal Radiation and Cooling Technologies ; Advancements in Semiconductor Devices and Circuit Design
Authors: Phillip M. Maffettone | Pascal Friederich | Sterling G. Baird | Ben Blaiszik | Keith A. Brown | Stuart I. Campbell | Orion A. Cohen | Rebecca L. Davis | Ian Foster | Navid Haghmoradi | Mark Hereld | Howie Joress | Nicole Jung | Ha-Kyung Kwon | Gabriella Pizzuto | Jacob Rintamaki | Casper Steinmann | Luca Torresi | Shijing Sun
Source: Digital Discovery (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

What is missing in autonomous discovery: open challenges for the community Self-driving labs (SDLs) leverage combinations of artificial intelligence, automation, and advanced computing to accelerate scientific discovery. Data science ; Computer science Machine Learning in Materials Science ; Scientific Computing and Data Management ; Genetics, Bioinformatics, and Biomedical Research
Authors: Desheng Wu | Hongye Wang | Yifei Gong | Dong Fan | Peng Ding | Qian Li | Quan Qian
Source: Journal of Materials Informatics (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Graph neural networks for molecular and materials representation Material molecular representation (MMR) plays an important role in material property or chemical reaction prediction. However, traditional expert-designed MMR methods face challenges in dealing with high dimensionality and heterogeneity of material data, leading to limited generalization capabilities and insufficient information representation. In recent years, graph neural networks (GNNs), a deep learning algorithm specifically designed for graph structures, have made inroads into the field of MMR. It will be instructive and inspiring to conduct a survey on various GNNs used for MMR. To achieve this objective, we compare GNNs with conventional MMR methods and illustrate the advantages of GNNs, such as their expressiveness and adaptability. In addition, we systematically classify and summarize the methods and applications of GNNs. Finally, we provide our insights into future research directions, taking into account the characteristics of molecular data and the inherent drawbacks of GNNs. This comprehensive survey is intended to present a holistic view of GNNs for MMR, focusing on the core concepts, the main techniques, and the future trends in this area. Computer science ; Machine learning ; Graph ; Artificial intelligence ; Adaptability ; Generalization ; Data science ; Representation (politics) ; Theoretical computer science Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Advanced Graph Neural Networks
Authors: Wojciech G. Stark | Julia Westermayr | Oscar A. Douglas‐Gallardo | James Gardner | Scott Habershon | Reinhard J. Maurer
Source: The Journal of Physical Chemistry C (article, 2023-12-04)
Field: Materials Science — Materials Chemistry

Machine Learning Interatomic Potentials for Reactive Hydrogen Dynamics at Metal Surfaces Based on Iterative Refinement of Reaction Probabilities The reactive chemistry of molecular hydrogen at surfaces, notably dissociative sticking and hydrogen evolution, plays a crucial role in energy storage and fuel cells. Theoretical studies can help to decipher underlying mechanisms and reaction design, but studying dynamics at surfaces is computationally challenging due to the complex electronic structure at interfaces and the high sensitivity of dynamics to reaction barriers. In addition, ab initio molecular dynamics, based on density functional theory, is too computationally demanding to accurately predict reactive sticking or desorption probabilities, as it requires averaging over tens of thousands of initial conditions. High-dimensional machine learning-based interatomic potentials are starting to be more commonly used in gas-surface dynamics, yet robust approaches to generate reliable training data and assess how model uncertainty affects the prediction of dynamic observables are not well established. Here, we employ ensemble learning to adaptively generate training data while assessing model performance with full uncertainty quantification (UQ) for reaction probabilities of hydrogen scattering on different copper facets. We use this approach to investigate the performance of two message-passing neural networks, SchNet and PaiNN. Ensemble-based UQ and iterative refinement allow us to expose the shortcomings of the invariant pairwise-distance-based feature representation in the SchNet model for gas-surface dynamics. Molecular dynamics ; Computer science ; Reaction dynamics ; Density functional theory ; Statistical physics ; Chemistry ; Biological system ; Computational chemistry ; Physics ; Molecule Machine Learning in Materials Science ; Fuel Cells and Related Materials ; Catalysis and Oxidation Reactions
Authors: Da Yan | Adam Smith | Cheng-Chien Chen
Source: Nature Computational Science (article, 2023-07-03)
Field: Materials Science — Materials Chemistry

Structure prediction and materials design with generative neural networks Generative grammar ; Artificial neural network ; Generative Design ; Feature (linguistics) ; Computer science ; Inverse ; Solid-state ; Artificial intelligence ; Crystal structure prediction ; Generative model ; Machine learning ; Materials science ; Crystal structure ; Engineering ; Mathematics ; Engineering physics ; Chemistry Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Computational Drug Discovery Methods