jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Hirotaka Uryu | Tsunetomo Yamada | Koichi Kitahara | Alok Singh | Yutaka Iwasaki | Kaoru Kimura | Kanta Hiroki | Naoya Miyao | Asuka Ishikawa | Ryuji Tamura | Satoshi Ohhashi | Chang Liu | Ryo Yoshida
Source: Advanced Science (article, 2023-11-14)
Field: Materials Science — Materials Chemistry

Deep Learning Enables Rapid Identification of a New Quasicrystal from Multiphase Powder Diffraction Patterns Since the discovery of the quasicrystal, approximately 100 stable quasicrystals are identified. To date, the existence of quasicrystals is verified using transmission electron microscopy; however, this technique requires significantly more elaboration than rapid and automatic powder X-ray diffraction. Therefore, to facilitate the search for novel quasicrystals, developing a rapid technique for phase-identification from powder diffraction patterns is desirable. This paper reports the identification of a new Al-Si-Ru quasicrystal using deep learning technologies from multiphase powder patterns, from which it is difficult to discriminate the presence of quasicrystalline phases even for well-trained human experts. Deep neural networks trained with artificially generated multiphase powder patterns determine the presence of quasicrystals with an accuracy >92% from actual powder patterns. Specifically, 440 powder patterns are screened using the trained classifier, from which the Al-Si-Ru quasicrystal is identified. This study demonstrates an excellent potential of deep learning to identify an unknown phase of a targeted structure from powder patterns even when existing in a multiphase sample. Quasicrystal ; Materials science ; Powder diffraction ; Diffraction ; Transmission electron microscopy ; Classifier (UML) ; Artificial neural network ; Phase (matter) ; Selected area diffraction ; Identification (biology) ; Crystallography ; Artificial intelligence ; Nanotechnology ; Computer science ; Chemistry ; Optics ; Physics ; Biology Quasicrystal Structures and Properties ; X-ray Diffraction in Crystallography ; Mineralogy and Gemology Studies
Authors: S. Santosh | W. B. Jefrin Harris | T. S. Srivatsan
Source: Materials (review, 2023-08-17)
Field: Materials Science — Materials Chemistry

Environment-Induced Degradation of Shape Memory Alloys: Role of Alloying and Nature of Environment Shape memory effects coupled with superelasticity are the distinctive characteristics of shape memory alloys (SMAs), a type of metal. When these alloys are subject to thermomechanical processing, they have the inherent ability to react to stimuli, such as heat. As a result, these alloys have established their usefulness in a variety of fields and have in recent years been chosen for use in stents, sensors, actuators, and several other forms of life-saving medical equipment. When it comes to the shape memory materials, nickel-titanium (Ni-Ti) alloys are in the forefront and have been chosen for use in a spectrum of demanding applications. As shape memory alloys (SMAs) are chosen for use in critical environments, such as blood streams (arteries and veins), orthodontic applications, orthopedic implants, and high temperature surroundings, such as actuators in aircraft engines, the phenomenon of environment-induced degradation is of both interest and concern. Hence, the environment-induced degradation behavior of the shape memory alloys (SMAs) needs to be studied to find viable ways to improve their resistance to an aggressive environment. The degradation that occurs upon exposure to an aggressive environment is often referred to as corrosion. Environment-induced degradation, or corrosion, being an unavoidable factor, certain techniques can be used for the purpose of enhancing the degradation resistance of shape memory alloys (SMAs). In this paper, we present and discuss the specific role of microstructure and contribution of environment to the degradation behavior of shape memory alloys (SMAs) while concurrently providing methods to resist both the development and growth of the degradation caused by the environment. Shape-memory alloy ; Pseudoelasticity ; Materials science ; Actuator ; Corrosion ; Degradation (telecommunications) ; Nickel titanium ; Microstructure ; Metallurgy ; Computer science ; Martensite ; Artificial intelligence Shape Memory Alloy Transformations
Authors: Julia Romanova | Rumen Lyapchev | Mihail Kolarski | Martin Tsvetkov | Denitsa Elenkova | Bernd Morgenstern | Joana Zaharieva
Source: Molecules (article, 2023-05-16)
Field: Materials Science — Materials Chemistry

Molecular Design of Luminescent Complexes of Eu(III): What Can We Learn from the Ligands The luminescent metal-organic complexes of rare earth metals are advanced materials with wide application potential in chemistry, biology, and medicine. The luminescence of these materials is due to a rare photophysical phenomenon called antenna effect, in which the excited ligand transmits its energy to the emitting levels of the metal. However, despite the attractive photophysical properties and the intriguing from a fundamental point of view antenna effect, the theoretical molecular design of new luminescent metal-organic complexes of rare earth metals is relatively limited. Our computational study aims to contribute in this direction, and we model the excited state properties of four new phenanthroline-based complexes of Eu(III) using the TD-DFT/TDA approach. The general formula of the complexes is EuL<sub>2</sub>A<sub>3</sub>, where L is a phenanthroline with -2-CH<sub>3</sub>O-C<sub>6</sub>H<sub>4</sub>, -2-HO-C<sub>6</sub>H<sub>4</sub>, -C<sub>6</sub>H<sub>5</sub> or -O-C<sub>6</sub>H<sub>5</sub> substituent at position 2 and A is Cl<sup>-</sup> or NO<sub>3</sub><sup>-</sup>. The antenna effect in all newly proposed complexes is estimated as viable and is expected to possess luminescent properties. The relationship between the electronic properties of the isolated ligands and the luminescent properties of the complexes is explored in detail. Qualitative and quantitative models are derived to interpret the ligand-to-complex relation, and the results are benchmarked with respect to available experimental data. Based on the derived model and common molecular design criteria for efficient antenna ligands, we choose phenanthroline with -O-C<sub>6</sub>H<sub>5</sub> substituent to perform complexation with Eu(III) in the presence of NO<sub>3</sub>¯. Experimental results for the newly synthesized Eu(III) complex are reported with a luminescent quantum yield of about 24% in acetonitrile. The study demonstrates the potential of low-cost computational models for discovering metal-organic luminescent materials. Substituent ; Luminescence ; Excited state ; Ligand (biochemistry) ; Antenna effect ; Phenanthroline ; Chemistry ; Metal ; Materials science ; Photochemistry ; Stereochemistry ; Crystallography ; Physics ; Atomic physics ; Organic chemistry ; Optoelectronics Lanthanide and Transition Metal Complexes ; Magnetism in coordination complexes ; Luminescence Properties of Advanced Materials
Authors: Lars Lüder | Peter Niraj Nirmalraj | A. Neels | René M. Rossi | Michel Calame
Source: ACS Applied Nano Materials (article, 2023-02-13)
Field: Materials Science — Materials Chemistry

Sensing of KCl, NaCl, and Pyocyanin with a MOF-Decorated Electrospun Nitrocellulose Matrix Wearable sensors can provide important insight into a patient’s health status by monitoring the concentration of specific biomarkers in body fluids. Compared to biofluids such as blood or cerebrospinal fluid, which require an invasive acquisition process, other body fluids such as sweat or exhaled air can be easily collected using patches or masks, sufficient for the detection of metabolic and pathological changes. However, the successful integration of an efficient biosensor into textiles or polymer substrates is a challenge if flexibility and functionality are not to be compromised. Here, we demonstrate the integration of nanoporous metal–organic framework (MOF) particles with nitrocellulose (NC) fibrous layers using an electrospinning approach and validate the efficiency of our MOF@NC structure as biosensors. The chemical response of this hybrid nanomaterial upon exposure to different ionic sweat biomarkers such as NaCl and KCl as well as pyocyanin, a biomarker for the nosocomial pathogen Pseudomonas aeruginosa, was investigated using Raman spectroscopy. A change of the Raman intensity at distinct peaks of our MOF-containing architecture occurs after treatment of the material with the analyte solutions. Furthermore, we observed the sensitivities for pyocyanin at the normalized Raman intensity change to be up to −1120 au μm–1, about 4 orders of magnitude larger than for NaCl and KCl. The independence of our architecture from the type of MOF and the possibility of using different MOFs with individual chemistry make this approach a promising platform for versatile and adaptable sensing of biomarkers with high sensitivity and selectivity. Nitrocellulose ; Biosensor ; Nanotechnology ; Nanoporous ; Materials science ; Nanomaterials ; Raman spectroscopy ; Analyte ; Chemistry ; Chromatography ; Membrane Advanced Nanomaterials in Catalysis ; Gas Sensing Nanomaterials and Sensors ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Yu-Kai Liao | Yi‐Sheng Lai | Fei Pan | Yen‐Hsun Su
Source: Journal of Materials Chemistry A (article, 2023-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Hybrid-biotaxonomy-like machine learning enables an anticipated surface plasmon resonance of Au/Ag nanoparticles assembled on ZnO nanorods A genetic algorithm neural network model based on machine learning has been established for precise prediction of plasmonic resonance by considering the fabrication parameters of heterostructural noble metal nanoparticles. Surface plasmon resonance ; Nanorod ; Plasmon ; Nanoparticle ; Materials science ; Nanotechnology ; Noble metal ; Artificial neural network ; Fabrication ; Computer science ; Metal ; Optoelectronics ; Artificial intelligence Gold and Silver Nanoparticles Synthesis and Applications ; Nanoparticles: synthesis and applications
Authors: Duoyang Fan | Xiaohui Liu | Yueming Ren | Shuaige Bai | Yanbing Li | Ziheng Luo | Jie Dong | Fei Chen | Wenbin Zeng
Source: Frontiers in Bioengineering and Biotechnology (review, 2023-04-21)
Field: Chemistry — Organic Chemistry

Functional insights to the development of bioactive material for combating bacterial infections The emergence of antibiotic-resistant "superbugs" poses a serious threat to human health. Nanomaterials and cationic polymers have shown unprecedented advantages as effective antimicrobial therapies due to their flexibility and ability to interact with biological macromolecules. They can incorporate a variety of antimicrobial substances, achieving multifunctional effects without easily developing drug resistance. Herein, this article discusses recent advances in cationic polymers and nano-antibacterial materials, including material options, fabrication techniques, structural characteristics, and activity performance, with a focus on their fundamental active elements. Flexibility (engineering) ; Antimicrobial ; Nanotechnology ; Cationic polymerization ; Antibiotic resistance ; Biochemical engineering ; Antibiotics ; Materials science ; Chemistry ; Engineering ; Biochemistry ; Organic chemistry Antimicrobial agents and applications ; Antimicrobial Peptides and Activities ; Nanoplatforms for cancer theranostics
Authors: Alyssa J. Anderson | Greg J. Dodge | Karen N. Allen | Barbara Imperiali
Source: Protein Science (article, 2023-04-25)
Field: Chemistry — Organic Chemistry

Co‐conserved sequence motifs are predictive of substrate specificity in a family of monotopic phosphoglycosyl transferases Monotopic phosphoglycosyl transferases (monoPGTs) are an expansive superfamily of enzymes that catalyze the first membrane-committed step in the biosynthesis of bacterial glycoconjugates. MonoPGTs show a strong preference for their cognate nucleotide diphospho-sugar (NDP-sugar) substrates. However, despite extensive characterization of the monoPGT superfamily through previous development of a sequence similarity network comprising >38,000 nonredundant sequences, the connection between monoPGT sequence and NDP-sugar substrate specificity has remained elusive. In this work, we structurally characterize the C-terminus of a prototypic monoPGT for the first time and show that 19 C-terminal residues play a significant structural role in a subset of monoPGTs. This new structural information facilitated the identification of co-conserved sequence "fingerprints" that predict NDP-sugar substrate specificity for this subset of monoPGTs. A Hidden Markov model was generated that correctly assigned the substrate of previously unannotated monoPGTs. Together, these structural, sequence, and biochemical analyses have delivered new insight into the determinants guiding substrate specificity of monoPGTs and have provided a strategy for assigning the NDP-sugar substrate of a subset of enzymes in the superfamily that use UDP-di-N-acetyl bacillosamine. Moving forward, this approach may be applied to identify additional sequence motifs that serve as fingerprints for monoPGTs of differing UDP-sugar substrate specificity. Biology ; Biochemistry ; Sequence motif ; Structural similarity ; Nucleotide sugar ; Conserved sequence ; Peptide sequence ; Sequence (biology) ; Sequence alignment ; Computational biology ; Enzyme ; Genetics ; Gene ; Biosynthesis Carbohydrate Chemistry and Synthesis ; Glycosylation and Glycoproteins Research ; Biochemical and Molecular Research
Authors: Matthew J. Burn | Paul L. A. Popelier
Source: Journal of Chemical Theory and Computation (article, 2023-02-09)
Field: Materials Science — Materials Chemistry

Gaussian Process Regression Models for Predicting Atomic Energies and Multipole Moments Developing a force field is a difficult task because its design is typically pulled in opposite directions by speed and accuracy. FFLUX breaks this trend by utilizing Gaussian process regression (GPR) to predict, at <i>ab initio</i> accuracy, atomic energies and multipole moments as obtained from the quantum theory of atoms in molecules (QTAIM). This work demonstrates that the in-house FFLUX training pipeline can generate successful GPR models for six representative molecules: peptide-capped glycine and alanine, glucose, paracetamol, aspirin, and ibuprofen. The molecules were sufficiently distorted to represent configurations from an AMBER-GAFF2 molecular dynamics run. All internal degrees of freedom were covered corresponding to 93 dimensions in the case of the largest molecule ibuprofen (33 atoms). Benefiting from active learning, the GPR models contain only about 2000 training points and return largely sub-kcal mol<sup>-1</sup> prediction errors for the validation sets. A proof of concept has been reached for transferring the model produced through active learning on one atomic property to that of the remaining atomic properties. The prediction of electrostatic interaction can be assessed at the intermolecular level, and the vast majority of interactions have a root-mean-square error of less than 0.1 kJ mol<sup>-1</sup> with a maximum value of ∼1 kJ mol<sup>-1</sup> for a glycine and paracetamol dimer. Multipole expansion ; Intermolecular force ; Ab initio ; Chemistry ; Force field (fiction) ; Kriging ; Molecule ; Computational chemistry ; Computer science ; Atomic physics ; Statistical physics ; Physics ; Quantum mechanics ; Artificial intelligence ; Machine learning Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Mass Spectrometry Techniques and Applications
Authors: Natalia Osiecka | Zbigniew Galewski | Ewa Juszyńska‐Gałązka
Source: Crystals (article, 2023-07-30)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Distinguishing the Focal-Conic Fan Texture of Smectic A from the Focal-Conic Fan Texture of Smectic B This publication presents methods of distinguishing the focal texture of the conical smectic phase A (SmA) and the crystalline smectic B phase (CrB). Most often, characteristic transition bars are observed in polarized light at the temperature point of the SmA–CrB phase transition. TOApy software transforms each image from a series of images recorded during POM observation to a function of light intensity versus temperature. Thermo-optical analysis is a powerful quantitative tool to notice this phase transition, but it has some limitations. The other applied method, the local binary pattern (LBP) algorithm, with high probability, detects differences between the textures of the conical focal fan of the SmA and CrB phases. The LBP algorithm is an efficient tool for texture classification. Conic section ; Texture (cosmology) ; Optics ; Conical surface ; Phase (matter) ; Cardinal point ; Transition point ; Materials science ; Binary number ; Physics ; Artificial intelligence ; Mathematics ; Geometry ; Image (mathematics) ; Computer science ; Mechanics Liquid Crystal Research Advancements ; Neurobiology and Insect Physiology Research ; Plant Diversity and Evolution
Authors: Mehmet Bağlan | Ümit Yıldıko | Kenan Gören
Source: Eskişehir Teknik Üniversitesi Bilim ve Teknoloji Dergisi B - Teorik Bilimler (article, 2023-02-27)
Field: Chemistry — Organic Chemistry

DFT CALCULATIONS AND MOLECULAR DOCKING STUDY IN 6-(2”-PYRROLIDINONE-5”-YL)-(-) EPICATECHIN MOLECULE FROM FLAVONOIDS The 6-311G(d,p) and SDD basis sets have been used to calculate the vibration frequencies, and the DFT/B3LYP approach was used to optimize the structure. The energy gap of the molecule has been calculated using the lowest unoccupied molecular orbital (LUMO) with the highest occupied molecular orbital (HOMO). The stability and charge delocalization of the Title molecule have been investigated using natural bond orbital (NBO) analysis. The dipole moment, polarizability, and first-order hyperpolarizability, as well as the molecular electrostatic potentially (MEP) and thermodynamic features, have been used to compute the nonlinear optical (NLO) behavior of the title molecule. The Schrödinger program was used to conduct molecular docking works to determine information about the interactions between the AChE and BChE enzymes and the chemical. In addition, a molecular docking study was analyzed for compounds PEP with AChE and BChE synthase binding protenins (PDB:4M0E) and (PDB:6SAM) using the Discovery Studio 2021 Client program. Compound AChE showed -7.105 kcal/mol while compounds BChE showed a inding score of -7.784 kcal/mol. Natural bond orbital ; Hyperpolarizability ; HOMO/LUMO ; Chemistry ; Computational chemistry ; Polarizability ; Molecular orbital ; Protein Data Bank (RCSB PDB) ; Molecule ; Docking (animal) ; Dipole ; Stereochemistry ; Crystallography ; Density functional theory ; Organic chemistry Synthesis and biological activity ; Nonlinear Optical Materials Research ; Bioactive Compounds and Antitumor Agents
Authors: Raluca Nicoleta Darie-Niță | Anamaria Irimia | Florica Doroftei | Laura Mihaela Ștefan | Andrzej Iwańczuk | Agnieszka Trusz
Source: International Journal of Molecular Sciences (article, 2023-02-11)
Field: Materials Science — Biomaterials

Bioactive and Physico-Chemical Assessment of Innovative Poly(lactic acid)-Based Biocomposites Containing Sage, Coconut Oil, and Modified Nanoclay The bioactivity of the versatile biodegradable biopolymer poly(lactic acid) (PLA) can be obtained by combining it with natural or synthetic compounds. This paper deals with the preparation of bioactive formulations involving the melt processing of PLA loaded with a medicinal plant (sage) and an edible oil (coconut oil), together with an organomodifed montmorillonite nanoclay, and an assessment of the resulting structural, surface, morphological, mechanical, and biological properties of the biocomposites. By modulating the components, the prepared biocomposites show flexibility, both antioxidant and antimicrobial activity, as well as a high degree of cytocompatibility, being capable to induce the cell adherence and proliferation on their surface. Overall, the obtained results suggest that the developed PLA-based biocomposites could potentially be used as bioactive materials in medical applications. Biocomposite ; Biopolymer ; SAGE ; Lactic acid ; Materials science ; Antioxidant ; Antimicrobial ; Food science ; Chemical engineering ; Chemistry ; Composite material ; Organic chemistry ; Polymer ; Composite number ; Bacteria ; Biology biodegradable polymer synthesis and properties ; Nanocomposite Films for Food Packaging ; Electrospun Nanofibers in Biomedical Applications
Authors: Line Mouaffac | Karen Palacio‐Rodríguez | Fabio Pietrucci
Source: Journal of Chemical Theory and Computation (article, 2023-08-07)
Field: Materials Science — Materials Chemistry

Optimal Reaction Coordinates and Kinetic Rates from the Projected Dynamics of Transition Paths Finding optimal reaction coordinates and predicting accurate kinetic rates for activated processes are two of the foremost challenges of molecular simulations. We introduce an algorithm that tackles the two problems at once: starting from a limited number of reactive molecular dynamics trajectories (transition paths), we automatically generate with a Monte Carlo approach a sequence of different reaction coordinates that progressively reduce the kinetic rate of their projected effective dynamics. Based on a variational principle, the minimal rate accurately approximates the exact one, and it corresponds to the optimal reaction coordinate. After benchmarking the method on an analytic double-well system, we apply it to complex atomistic systems: the interaction of carbon nanoparticles of different sizes in water. Reaction coordinate ; Molecular dynamics ; Kinetic energy ; Kinetic Monte Carlo ; Statistical physics ; Monte Carlo method ; Reaction rate ; Computer science ; Sequence (biology) ; Chemistry ; Physics ; Computational chemistry ; Mathematics ; Classical mechanics Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Spectroscopy and Quantum Chemical Studies