jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Francesca Milocco | F. de Vries | Harmke S. Siebe | Silène Engbers | Serhiy Demeshko | Franc Meyer | Edwin Otten
Source: Inorganic Chemistry (article, 2021-01-19)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Widening the Window of Spin-Crossover Temperatures in Bis(formazanate)iron(II) Complexes via Steric and Noncovalent Interactions Bis(formazanate)iron(II) complexes undergo a thermally induced <i>S</i> = 0 to <i>S</i> = 2 spin transition in solution. Here we present a study of how steric effects and π-stacking interactions between the triarylformazanate ligands affect the spin-crossover behavior, in addition to electronic substituent effects. Moreover, the effect of increasing the denticity of the formazanate ligands is explored by including additional OMe donors in the ligand (<b>7</b>). In total, six new compounds (<b>2</b>-<b>7</b>) have been synthesized and characterized, both in solution and in the solid state, via spectroscopic, magnetic, and structural analyses. The series spans a broad range of spin-crossover temperatures (<i>T</i><sub>1/2</sub>) for the LS ⇌ HS equilibrium in solution, with the exception of compound <b>6</b> which remains high-spin (<i>S</i> = 2) down to 210 K. In the solid state, <b>6</b> was shown to exist in two distinct forms: a tetrahedral high-spin complex (<b>6a</b>, <i>S</i> = 2) and a rare square-planar structure with an intermediate-spin state (<b>6b</b>, <i>S</i> = 1). SQUID measurements, <sup>57</sup>Fe Mössbauer spectroscopy, and differential scanning calorimetry indicate that in the solid state the square-planar form <b>6b</b> undergoes an incomplete spin-change-coupled isomerization to tetrahedral <b>6a</b>. The complex that contains additional OMe donors (<b>7</b>) results in a six-coordinate (NNO)<sub>2</sub>Fe coordination geometry, which shifts the spin-crossover to significantly higher temperatures (<i>T</i><sub>1/2</sub> = 444 K). The available experimental and computational data for <b>7</b> suggest that the Fe···OMe interaction is retained upon spin-crossover. Despite the difference in coordination environment, the weak OMe donors do not significantly alter the electronic structure or ligand-field splitting, and the occurrence of spin-crossover (similar to the compounds lacking the OMe groups) originates from a large degree of metal-ligand π-covalency. Chemistry ; Spin crossover ; Steric effects ; Crystallography ; Spin states ; Ligand (biochemistry) ; Mössbauer spectroscopy ; Spin transition ; Stacking ; Denticity ; Spin (aerodynamics) ; Substituent ; Stereochemistry ; Inorganic chemistry ; Crystal structure ; Organic chemistry Magnetism in coordination complexes ; Metal-Catalyzed Oxygenation Mechanisms ; Lanthanide and Transition Metal Complexes
Authors: J. Theo Kloprogge | Concepcion P. Ponce
Source: Minerals (review, 2021-01-23)
Field: Materials Science — Biomaterials

Spectroscopic Studies of Synthetic and Natural Saponites: A Review Saponite is a trioctahedral 2:1 smectite with the ideal composition MxMg3AlxSi4−xO10(OH,F)2.nH2O (M = interlayer cation). Both the success of the saponite synthesis and the determination of its applications depends on robust knowledge of the structure and composition of saponite. Among the routine characterization techniques, spectroscopic methods are the most common. This review, thus, provides an overview of various spectroscopic methods to characterize natural and synthetic saponites with focus on the extensive work by one of the authors (JTK). The Infrared (IR) and Raman spectra of natural and synthetic saponites are discussed in detail including the assignment of the observed bands. The crystallization of saponite is discussed based on the changes in the IR and Raman spectra and a possible crystallization model is provided. Infrared emission spectroscopy has been used to study the thermal changes of saponite in situ including the dehydration and (partial) dehydroxylation up to 750 °C. 27Al and 29Si magic-angle-spinning nuclear magnetic resonance spectroscopy is discussed (as well as 11B and 71Ga for B- and Ga-Si substitution) with respect to, in particular, Al(IV)/Al(VI) and Si/Al(IV) ratios. X-ray photoelectron spectroscopy provides chemical information as well as some information related to the local environments of the different elements in the saponite structure as reflected by their binding energies. Saponite ; Raman spectroscopy ; Infrared spectroscopy ; Crystallization ; Chemistry ; Spectroscopy ; Infrared ; X-ray photoelectron spectroscopy ; Materials science ; Clay minerals ; Mineralogy ; Nuclear magnetic resonance ; Optics ; Organic chemistry ; Physics Clay minerals and soil interactions ; Mesoporous Materials and Catalysis ; Zeolite Catalysis and Synthesis
Authors: Laure Bobyk | Adeline Tarantini | David Béal | Giulia Veronesi | Isabelle Kieffer | S. Motellier | Eugenia Valsami‐Jones | Iseult Lynch | Pierre-Henri Jouneau | Karin Pernet‐Gallay | Catherine Aude‐Garcia | Sylvie Sauvaigo | Thierry Douki | Thierry Rabilloud | Marie Carrière
Source: Environmental Science Nano (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Toxicity and chemical transformation of silver nanoparticles in A549 lung cells: dose-rate-dependent genotoxic impact Acute exposure of A549 cells to Ag-NPs induces stronger effects on DNA integrity, ROS level, cell metabolism and cell cycle than repeated exposure. Ag-NPs dissolves in both exposure conditions and Ag ions recombine with thiolated proteins. A549 cell ; Toxicity ; Silver nanoparticle ; Human lung ; DNA damage ; Transformation (genetics) ; Chemistry ; Cell ; Biophysics ; Cell cycle ; DNA ; Cell biology ; Nanoparticle ; Cell culture ; Materials science ; Nanotechnology ; Biochemistry ; Biology ; Genetics ; Gene Nanoparticles: synthesis and applications ; Air Quality and Health Impacts ; Heavy Metal Exposure and Toxicity
Authors: Elliot Y. Makhani | Ailin Zhang | Jered B. Haun
Source: Nano Convergence (review, 2021-11-30)
Field: Materials Science — Biomaterials

Quantifying and controlling bond multivalency for advanced nanoparticle targeting to cells Nanoparticles have drawn intense interest as delivery agents for diagnosing and treating various cancers. Much of the early success was driven by passive targeting mechanisms such as the enhanced permeability and retention (EPR) effect, but this has failed to lead to the expected clinical successes. Active targeting involves binding interactions between the nanoparticle and cancer cells, which promotes tumor cell-specific accumulation and internalization. Furthermore, nanoparticles are large enough to facilitate multiple bond formation, which can improve adhesive properties substantially in comparison to the single bond case. While multivalent binding is universally believed to be an attribute of nanoparticles, it is a complex process that is still poorly understood and difficult to control. In this review, we will first discuss experimental studies that have elucidated roles for parameters such as nanoparticle size and shape, targeting ligand and target receptor densities, and monovalent binding kinetics on multivalent nanoparticle adhesion efficiency and cellular internalization. Although such experimental studies are very insightful, information is limited and confounded by numerous differences across experimental systems. Thus, we focus the second part of the review on theoretical aspects of binding, including kinetics, biomechanics, and transport physics. Finally, we discuss various computational and simulation studies of nanoparticle adhesion, including advanced treatments that compare directly to experimental results. Future work will ideally continue to combine experimental data and advanced computational studies to extend our knowledge of multivalent adhesion, as well as design the most powerful nanoparticle-based agents to treat cancer. Internalization ; Nanoparticle ; Nanotechnology ; Biophysics ; Chemistry ; Cell adhesion ; Ligand (biochemistry) ; Materials science ; Computer science ; Cell ; Receptor ; Biology ; Biochemistry Nanoparticle-Based Drug Delivery ; Nanoparticles: synthesis and applications ; Gold and Silver Nanoparticles Synthesis and Applications
Authors: Tao Wei | Malte Kohring | Heiko B. Weber | Frank Hauke | Andreas Hirsch
Source: Nature Communications (article, 2021-01-22)
Field: Materials Science — Materials Chemistry

Molecular embroidering of graphene Structured covalent two-dimensional patterning of graphene with different chemical functionalities constitutes a major challenge in nanotechnology. At the same time, it opens enormous opportunities towards tailoring of physical and chemical properties with limitless combinations of spatially defined surface functionalities. However, such highly integrated carbon-based architectures (graphene embroidery) are so far elusive. Here, we report a practical realization of molecular graphene embroidery by generating regular multiply functionalized patterns consisting of concentric regions of covalent addend binding. These spatially resolved hetero-architectures are generated by repetitive electron-beam lithography/reduction/covalent-binding sequences starting with polymethyl methacrylate covered graphene deposited on a Si/SiO<sub>2</sub> substrate. The corresponding functionalization zones carry bromobenzene-, deutero-, and chloro-addends. We employ statistical Raman spectroscopy together with scanning electron microscopy/energy dispersive X-ray spectroscopy for an unambiguous characterization. The exquisitely ordered nanoarchitectures of these covalently multi-patterned graphene sheets are clearly visualized. Graphene ; Covalent bond ; Materials science ; Raman spectroscopy ; Nanotechnology ; Surface modification ; Chemistry ; Physics ; Optics ; Organic chemistry Graphene research and applications ; Molecular Junctions and Nanostructures ; Nanopore and Nanochannel Transport Studies
Authors: Yuanhao Mao | Dong Zhao | Shen Yan | Hongjia Zhang | Juan Li | Kai Han | Xiaojun Xu | Chuan Guo | Lexian Yang | Chaofan Zhang | Kun Huang | Yulin Chen
Source: Light Science & Applications (article, 2021-01-21)
Field: Materials Science — Materials Chemistry

A vacuum ultraviolet laser with a submicrometer spot for spatially resolved photoemission spectroscopy Vacuum ultraviolet (VUV) lasers have demonstrated great potential as the light source for various spectroscopies, which, if they can be focused into a small beam spot, will not only allow investigation of mesoscopic materials and structures but also find application in the manufacture of nano-objects with excellent precision. In this work, we report the construction of a 177 nm VUV laser that can achieve a record-small (~0.76 μm) focal spot at a long focal length (~45 mm) by using a flat lens without spherical aberration. The size of the beam spot of this VUV laser was tested using a metal grating and exfoliated graphene flakes, and we demonstrated its application in a fluorescence spectroscopy study on pure and Tm<sup>3+</sup>-doped NaYF<sub>4</sub> microcrystals, revealing a new emission band that cannot be observed in the traditional up-conversion process. In addition, this laser system would be an ideal light source for spatially and angle-resolved photoemission spectroscopy. Materials science ; Optics ; Laser ; Spectroscopy ; Optoelectronics ; Lens (geology) ; Physics Luminescence Properties of Advanced Materials ; Solid State Laser Technologies ; Ga2O3 and related materials
Authors: Fabrice N. H. Karabulut | Günther Höfler | Naveen Ashok Chand | Gareth W. Beckermann
Source: Polymers (article, 2021-09-24)
Field: Materials Science — Biomaterials

Electrospun Nanofibre Filtration Media to Protect against Biological or Nonbiological Airborne Particles Electrospun nanofibres can outperform their melt-blown counterparts in many applications, especially air filtration. The different filtration mechanisms of nanofibres are particularly important when it comes to the air filtration of viruses (such as COVID-19) and bacteria. In this work, we present an electrospun nanofibre filter media, FilterLayr<sup>TM</sup> by NanoLayr Ltd., containing poly(methyl methacrylate)/ethylene vinyl alcohol nanofibres. The outstanding uniformity of the nanofibres was indicated by the good correlation between pressure drop (ΔP) and areal weight with R2 values in the range of 0.82 to 0.98 across various test air velocities. By adjusting the nanofibre areal weight (basis weight), the nanofibre filter media was shown to meet the particle filtration efficiency and breathability requirements of the following internationally accepted facemask and respirator standards: N95 respirator facemask performance in accordance with NIOSH 42CFR84 (filtration efficiency of up to 98.10% at a pressure drop of 226 Pa and 290 Pa at 85 L·min<sup>-1</sup> and 120 L·min<sup>-1</sup>, respectively), Level 2 surgical facemask performance in accordance with ASTM F2299 (filtration efficiency of up to 99.97% at 100 nm particle size and a pressure drop of 44 Pa at 8 L·min<sup>-1</sup>), and Level 2 filtration efficiency and Level 1 breathability for barrier face coverings in accordance with ASTM F3502 (filtration efficiency of up to 99.68% and a pressure drop of 133 Pa at 60 L·min<sup>-1</sup>), with Level 2 breathability being achievable at lower nanofibre areal weights. Filtration (mathematics) ; Nanotechnology ; Materials science ; Biochemical engineering ; Engineering ; Mathematics Electrospun Nanofibers in Biomedical Applications ; Microplastics and Plastic Pollution ; Recycling and Waste Management Techniques
Authors: Pankaj Rajak | Beibei Wang | Ken‐ichi Nomura | Ye Luo | Aiichiro Nakano | Rajiv K. Kalia | Priya Vashishta
Source: npj Computational Materials (article, 2021-07-09)
Field: Materials Science — Materials Chemistry

Autonomous reinforcement learning agent for stretchable kirigami design of 2D materials Abstract Mechanical behavior of 2D materials such as MoS 2 can be tuned by the ancient art of kirigami. Experiments and atomistic simulations show that 2D materials can be stretched more than 50% by strategic insertion of cuts. However, designing kirigami structures with desired mechanical properties is highly sensitive to the pattern and location of kirigami cuts. We use reinforcement learning (RL) to generate a wide range of highly stretchable MoS 2 kirigami structures. The RL agent is trained by a small fraction (1.45%) of molecular dynamics simulation data, randomly sampled from a search space of over 4 million candidates for MoS 2 kirigami structures with 6 cuts. After training, the RL agent not only proposes 6-cut kirigami structures that have stretchability above 45%, but also gains mechanistic insight to propose highly stretchable (above 40%) kirigami structures consisting of 8 and 10 cuts from a search space of billion candidates as zero-shot predictions. Reinforcement learning ; Reinforcement ; Computer science ; Materials science ; Nanotechnology ; Range (aeronautics) ; Space (punctuation) ; Artificial intelligence ; Composite material Machine Learning in Materials Science ; Advanced Sensor and Energy Harvesting Materials ; Ferroelectric and Negative Capacitance Devices
Authors: Fuming Lai | Zhehao Sun | Sandra Elizabeth Saji | Yichuan He | Xue‐Feng Yu | Haitao Zhao | Haibo Guo | Zongyou Yin
Source: Small (article, 2021-03-01)
Field: Materials Science — Materials Chemistry

Machine Learning‐Aided Crystal Facet Rational Design with Ionic Liquid Controllable Synthesis Crystallographic facets in a crystal carry interior properties and proffer rich functionalities in a wide range of application areas. However, rational prediction, on-demand customization, and accurate synthesis of facets and facet junctions of a crystal are enormously desirable but still challenging. Herein, a framework of machine learning (ML)-aided crystal facet design with ionic liquid controllable synthesis is developed and then demonstrated with the star-material anatase TiO<sub>2</sub> . Aided by employing ML to acquire surface energies from facet junction datasource, the relationships between surface energy and growth conditions based on the Langmuir adsorption isotherm are unveiled, enabling to develop controllable facet synthetic strategies. These strategies are successfully verified after applied for synthesizing TiO<sub>2</sub> crystals with custom crystal facets and facet junctions under tuning ionic liquid [bmim][BF<sub>4</sub> ] experimental conditions. Therefore, this innovative framework integrates data-intensive rational design and experimental controllable synthesis to develop and customize crystallographic facets and facet junctions. This proves the feasibility of an intelligent chemistry future to accelerate the discovery of facet-governed functional material candidates. Facet (psychology) ; Materials science ; Rational design ; Anatase ; Crystal (programming language) ; Nanotechnology ; Ionic liquid ; Ionic bonding ; Adsorption ; Computer science ; Photocatalysis ; Chemistry ; Physical chemistry ; Ion Machine Learning in Materials Science ; Ionic liquids properties and applications ; Electronic and Structural Properties of Oxides
Authors: Qiang Wang | Jarrett Dumond | Jarren Teo | Hong Yee Low
Source: ACS Applied Materials & Interfaces (article, 2021-06-15)
Field: Materials Science — Surfaces, Coatings and Films

Superhydrophobic Polymer Topography Design Assisted by Machine Learning Algorithms Superhydrophobic surfaces have been largely achieved through various surface topographies. Both empirical and numerical simulations have been reported to help understand and design superhydrophobic surfaces. Many such successful surfaces have also been achieved using bioinspired and biomimetic designs. Despite this, identifying the right surface texture to meet the requirements of specific applications is not a straightforward task. Here, we report a hybrid approach that includes experimental methods, numerical simulations, and machine learning (ML) algorithms to create design maps for superhydrophobic polymer topographies. Two design objectives to investigate superhydrophobic properties were the maximum water contact angle (WCA) and Laplace pressure. The design parameters were the geometries of an isotropic pillar structure in micrometer and sub-micrometer length scales. The finite element method (FEM) was validated by the experimental data and employed to generate a labeled dataset for ML training. Artificial neural network (ANN) models were then trained on the labeled database for the topographic parameters (width <i>W</i>, height <i>H</i>, and pitch <i>P</i>) with the corresponding WCA and Laplace pressure. The ANN models yielded a series of nonlinear relationships between the topographic design parameters and the WCA and Laplace pressure and substantial differences between the micrometer and sub-micrometer length scales. Design maps that span the topography design parameters provide optimal design or tradeoff parameters. This research demonstrates the potential of ANN as a rapid design tool for surface topography exploration. Laplace pressure ; Micrometer ; Materials science ; Isotropy ; Finite element method ; Artificial neural network ; Design of experiments ; Algorithm ; Laplace's equation ; Artificial intelligence ; Computer science ; Mechanical engineering ; Structural engineering ; Engineering ; Optics ; Mathematics ; Boundary value problem Surface Modification and Superhydrophobicity ; Adhesion, Friction, and Surface Interactions ; Additive Manufacturing and 3D Printing Technologies
Authors: Manh‐Thuong Nguyen | Roger Rousseau | Patricia Paviet | Vassiliki‐Alexandra Glezakou
Source: ACS Applied Materials & Interfaces (article, 2021-09-08)
Field: Materials Science — Materials Chemistry

Actinide Molten Salts: A Machine-Learning Potential Molecular Dynamics Study Actinide molten salts represent a class of important materials in nuclear energy. Understanding them at a molecular level is critical for the proper and optimal design of relevant technological applications. Yet, owing to the complexity of electronic structure due to the 5f orbitals, computational studies of heavy elements in condensed phases using ab initio potentials to study the structure and dynamics of these elements embedded in molten salts are difficult. This lack of efficient computational protocols makes it difficult to obtain information on properties that require extensive statistical sampling like transport properties. To tackle this problem, we adopted a machine-learning approach to study ThCl<sub>4</sub>-NaCl and UCl<sub>3</sub>-NaCl binary systems. The machine-learning potential with the density functional theory accuracy allows us to obtain long molecular dynamics trajectories (ns) for large systems (10<sup>3</sup> atoms) at a considerably low computing cost, thereby efficiently gaining information about their bonding structures, thermodynamics, and dynamics at a range of temperatures. We observed a considerable change in the coordination environments of actinide elements and their characteristic coordination sphere lifetime. Our study also suggests that actinides in molten salts may not follow well-known entropy-scaling laws. Molecular dynamics ; Actinide ; Density functional theory ; Materials science ; Chemical physics ; Statistical physics ; Computational chemistry ; Chemistry ; Physics ; Inorganic chemistry Nuclear Materials and Properties ; Machine Learning in Materials Science ; Molten salt chemistry and electrochemical processes