jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Lanxia Hao | Yali Yang | Yu Huan | Hongbo Cheng | Yuyao Zhao | Yingying Wang | Jing Yan | Wei Ren | Jun Ouyang
Source: npj Computational Materials (article, 2021-05-06)
Field: Materials Science — Materials Chemistry

Achieving a high dielectric tunability in strain-engineered tetragonal K0.5Na0.5NbO3 films Abstract Using a modified Landau-Devonshire type thermodynamic potential, we show that dielectric tunability η of a tetragonal ferroelectric film can be analytically solved. At a given electric field E , η is a function of the remnant polarization ( $$P_0^f$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msubsup> <mml:mrow> <mml:mi>P</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>0</mml:mn> </mml:mrow> <mml:mrow> <mml:mi>f</mml:mi> </mml:mrow> </mml:msubsup> </mml:math> ) and the small-field relative dielectric permittivity ( $$\chi _0^f$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msubsup> <mml:mrow> <mml:mi>χ</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>0</mml:mn> </mml:mrow> <mml:mrow> <mml:mi>f</mml:mi> </mml:mrow> </mml:msubsup> </mml:math> ), which are commonly measured material properties. After a survey of materials, a large η ~80% is predicted to be achievable in a (001)-oriented tetragonal (K 0.5 ,Na 0.5 )NbO 3 film. This strain-stabilized tetragonal phase is verified by density functional theory (DFT) calculations. (K 0.5 ,Na 0.5 )NbO 3 films based on this design were successfully prepared via a sputtering deposition process on SrRuO 3 -buffered (100)SrTiO 3 substrates. The resulted epitaxial films showed a sizable $$P_0^f$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msubsup> <mml:mrow> <mml:mi>P</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>0</mml:mn> </mml:mrow> <mml:mrow> <mml:mi>f</mml:mi> </mml:mrow> </mml:msubsup> </mml:math> (~0.21C m −2 ) and a large $$\chi _0^f$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msubsup> <mml:mrow> <mml:mi>χ</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>0</mml:mn> </mml:mrow> <mml:mrow> <mml:mi>f</mml:mi> </mml:mrow> </mml:msubsup> </mml:math> (~830–860), as well as a large η close to the theoretical value. The measured dielectric tunabilities as functions of E are well described by the theoretical η ( E ) curves, validating our integrated approach rooted in a theoretical understanding. Tetragonal crystal system ; Materials science ; Ferroelectricity ; Dielectric ; Algorithm ; Analytical Chemistry (journal) ; Crystallography ; Chemistry ; Computer science ; Crystal structure Ferroelectric and Piezoelectric Materials ; Multiferroics and related materials ; Dielectric properties of ceramics
Authors: René Wittmann | Louis B. G. Cortes | Hartmut Löwen | Dirk G. A. L. Aarts
Source: Nature Communications (article, 2021-01-27)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Particle-resolved topological defects of smectic colloidal liquid crystals in extreme confinement Confined samples of liquid crystals are characterized by a variety of topological defects and can be exposed to external constraints such as extreme confinements with nontrivial topology. Here we explore the intrinsic structure of smectic colloidal layers dictated by the interplay between entropy and an imposed external topology. Considering an annular confinement as a basic example, a plethora of competing states is found with nontrivial defect structures ranging from laminar states to multiple smectic domains and arrays of edge dislocations, which we refer to as Shubnikov states in formal analogy to the characteristic of type-II superconductors. Our particle-resolved results, gained by a combination of real-space microscopy of thermal colloidal rods and fundamental-measure-based density functional theory of hard anisotropic bodies, agree on a quantitative level. Liquid crystal ; Topological defect ; Anisotropy ; Colloidal particle ; Condensed matter physics ; Topology (electrical circuits) ; Superconductivity ; Particle (ecology) ; Laminar flow ; Materials science ; Rod ; Colloid ; Physics ; Chemical physics ; Optics ; Chemistry Liquid Crystal Research Advancements ; Material Dynamics and Properties ; Plant and animal studies
Authors: Dimitrios Bachtis | Gert Aarts | Biagio Lucini
Source: Physical review. D/Physical review. D. (article, 2021-04-23)
Field: Materials Science — Materials Chemistry

Quantum field-theoretic machine learning We derive machine learning algorithms from discretized Euclidean field theories, making inference and learning possible within dynamics described by quantum field theory. Specifically, we demonstrate that the ${\ensuremath{\phi}}^{4}$ scalar field theory satisfies the Hammersley-Clifford theorem, therefore recasting it as a machine learning algorithm within the mathematically rigorous framework of Markov random fields. We illustrate the concepts by minimizing an asymmetric distance between the probability distribution of the ${\ensuremath{\phi}}^{4}$ theory and that of target distributions, by quantifying the overlap of statistical ensembles between probability distributions and through reweighting to complex-valued actions with longer-range interactions. Neural network architectures are additionally derived from the ${\ensuremath{\phi}}^{4}$ theory which can be viewed as generalizations of conventional neural networks and applications are presented. We conclude by discussing how the proposal opens up a new research avenue, that of developing a mathematical and computational framework of machine learning within quantum field theory. Quantum machine learning ; Field (mathematics) ; Computer science ; Quantum ; Artificial intelligence ; Machine learning ; Physics ; Quantum mechanics ; Quantum computer ; Mathematics ; Pure mathematics Machine Learning in Materials Science ; Quantum Computing Algorithms and Architecture ; Gaussian Processes and Bayesian Inference
Authors: Łukasz Kozłowski
Source: Nucleic Acids Research (article, 2021-10-06)
Field: Chemistry — Spectroscopy

Proteome-<i>pI</i>2.0: proteome isoelectric point database update Proteome-pI 2.0 is an update of an online database containing predicted isoelectric points and pKa dissociation constants of proteins and peptides. The isoelectric point-the pH at which a particular molecule carries no net electrical charge-is an important parameter for many analytical biochemistry and proteomics techniques. Additionally, it can be obtained directly from the pKa values of individual charged residues of the protein. The Proteome-pI 2.0 database includes data for over 61 million protein sequences from 20 115 proteomes (three to four times more than the previous release). The isoelectric point for proteins is predicted by 21 methods, whereas pKa values are inferred by one method. To facilitate bottom-up proteomics analysis, individual proteomes were digested in silico with the five most commonly used proteases (trypsin, chymotrypsin, trypsin + LysC, LysN, ArgC), and the peptides' isoelectric point and molecular weights were calculated. The database enables the retrieval of virtual 2D-PAGE plots and customized fractions of a proteome based on the isoelectric point and molecular weight. In addition, isoelectric points for proteins in NCBI non-redundant (nr), UniProt, SwissProt, and Protein Data Bank are available in both CSV and FASTA formats. The database can be accessed at http://isoelectricpointdb2.org. Proteome ; Biology ; Isoelectric point ; Pi ; Isoelectric focusing ; Proteomics ; Database ; Computational biology ; Human proteome project ; Bioinformatics ; Genetics ; Biochemistry ; Gene ; Enzyme Advanced Proteomics Techniques and Applications ; Enzyme Structure and Function ; Genomics and Phylogenetic Studies
Authors: Ayesha Wickramasinghe | Yiling Xiao | Naohiro Kobayashi | Songlin Wang | Kathryn P. Scherpelz | Toshio Yamazaki | Stephen C. Meredith | Yoshitaka Ishii
Source: Journal of the American Chemical Society (article, 2021-07-26)
Field: Chemistry — Spectroscopy

Sensitivity-Enhanced Solid-State NMR Detection of Structural Differences and Unique Polymorphs in Pico- to Nanomolar Amounts of Brain-Derived and Synthetic 42-Residue Amyloid-β Fibrils Amyloid-β (Aβ) fibrils in neuritic plaques are a hallmark of Alzheimer's disease (AD). Since the 42-residue Aβ (Aβ42) fibril is the most pathogenic among different Aβ species, its structural characterization is crucial to our understanding of AD. While several polymorphs have been reported for Aβ40, previous studies of Aβ42 fibrils prepared at neutral pH detected essentially only one structure, with an S-shaped β-sheet arrangement (<i>e.g.</i>, Xiao et al. <i>Nat. Struct. Mol. Biol.</i> 2015, 22, 499). Herein, we demonstrate the feasibility of characterizing the structure of trace amounts of brain-derived and synthetic amyloid fibrils by sensitivity-enhanced <sup>1</sup>H-detected solid-state NMR (SSNMR) under ultrafast magic angle spinning. By taking advantage of the high sensitivity of this technique, we first demonstrate its applicability for the high-throughput screening of trace amounts of selectively <sup>13</sup>C- and <sup>15</sup>N-labeled Aβ42 fibril prepared with ∼0.01% patient-derived amyloid (<i>ca</i>. 4 pmol) as a seed. The comparison of 2D <sup>13</sup>C/<sup>1</sup>H SSNMR data revealed marked structural differences between AD-derived Aβ42 (∼40 nmol or ∼200 μg) and synthetic fibrils in less than 10 min, confirming the feasibility of assessing the fibril structure from ∼1 pmol of brain amyloid seed in ∼2.5 h. We also present the first structural characterization of synthetic <i>fully protonated</i> Aβ42 fibril by <sup>1</sup>H-detected 3D and 4D SSNMR. With procedures assisted by automated assignments, main-chain resonance assignments were completed for trace amounts (∼42 nmol) of a <i>fully protonated</i> amyloid fibril in the <sup>1</sup>H-detection approach. The results suggest that this Aβ42 fibril exhibits a novel fold or polymorph structure. Chemistry ; Fibril ; Amyloid fibril ; Solid-state nuclear magnetic resonance ; Protonation ; Amyloid (mycology) ; Residue (chemistry) ; Peptide ; Congo red ; Crystallography ; Amyloid β ; Biophysics ; Biochemistry ; Nuclear magnetic resonance ; Organic chemistry Advanced NMR Techniques and Applications ; Supramolecular Self-Assembly in Materials ; Alzheimer's disease research and treatments
Authors: Joakim Brorsson | Arsalan Hashemi | Zheyong Fan | Erik Fransson | Fredrik Eriksson | Tapio Ala-Nissilä | Arkady V. Krasheninnikov | Hannu‐Pekka Komsa | Paul Erhart
Source: Advanced Theory and Simulations (article, 2021-11-27)
Field: Materials Science — Materials Chemistry

Efficient Calculation of the Lattice Thermal Conductivity by Atomistic Simulations with Ab Initio Accuracy Abstract High‐order force constant expansions can provide accurate representations of the potential energy surface relevant to vibrational motion. They can be efficiently parametrized using quantum mechanical calculations and subsequently sampled at a fraction of the cost of the underlying reference calculations. Here, force constant expansions are combined via the hiphive package with GPU‐accelerated molecular dynamics simulations via the GPUMD package to obtain an accurate, transferable, and efficient approach for sampling the dynamical properties of materials. The performance of this methodology is demonstrated by applying it both to materials with very low thermal conductivity (Ba 8 Ga 16 Ge 30 , SnSe) and a material with a relatively high lattice thermal conductivity (monolayer‐MoS 2 ). These cases cover both situations with weak (monolayer‐MoS 2 , SnSe) and strong (Ba 8 Ga 16 Ge 30 ) pho renormalization. The simulations also enable to access complementary information such as the spectral thermal conductivity, which allows to discriminate the contribution by different phonon modes while accounting for scattering to all orders. The software packages described here are made available to the scientific community as free and open‐source software in order to encourage the more widespread use of these techniques as well as their evolution through continuous and collaborative development. Phonon ; Thermal conductivity ; Materials science ; Molecular dynamics ; Ab initio ; Monolayer ; Statistical physics ; Lattice (music) ; Quantum ; Physics ; Condensed matter physics ; Computational chemistry ; Chemistry ; Nanotechnology ; Quantum mechanics ; Composite material Advanced Thermoelectric Materials and Devices ; Thermal properties of materials ; Machine Learning in Materials Science
Authors: Sandra Munera | Alejandro Rodríguez | Nuria Aleixos | Sergio Cubero | Juan Gómez‐Sanchís | J. Blasco
Source: Foods (article, 2021-09-13)
Field: Chemistry — Analytical Chemistry

Detection of Invisible Damages in ‘Rojo Brillante’ Persimmon Fruit at Different Stages Using Hyperspectral Imaging and Chemometrics The main cause of flesh browning in 'Rojo Brillante' persimmon fruit is mechanical damage caused during harvesting and packing. Innovation and research on nondestructive techniques to detect this phenomenon in the packing lines are necessary because this type of alteration is often only seen when the final consumer peels the fruit. In this work, we have studied the application of hyperspectral imaging in the range of 450-1040 nm to detect mechanical damage without any external symptoms. The fruit was damaged in a controlled manner. Later, images were acquired before and at 0, 1, 2 and 3 days after damage induction. First, the spectral data captured from the images were analysed through an algorithm based on principal component analysis (PCA). The aim was to automatically separate intact and damaged fruit, and to detect the damage in the PC images when present. With this algorithm, 90.0% of intact fruit and 90.8% of damaged fruit were correctly detected. A model based on partial least squares-discriminant analysis (PLS-DA), was later calibrated using the mean spectrum of the pixels detected as damaged, to determine the moment when the fruit was damaged. The model differentiated fruit corresponding correctly to 0, 1, 2 and 3 days after damage induction, achieving a total accuracy of 99.4%. Hyperspectral imaging ; Chemometrics ; Principal component analysis ; Horticulture ; Flesh ; Mathematics ; Linear discriminant analysis ; Browning ; Artificial intelligence ; Pattern recognition (psychology) ; Botany ; Chemistry ; Computer science ; Biology ; Chromatography Spectroscopy and Chemometric Analyses ; Phytochemicals and Antioxidant Activities ; Meat and Animal Product Quality
Authors: Vadim Vorobyov | Sebastian Zaiser | Nikolas Abt | Jonas Meinel | Durga Bhaktavatsala Rao Dasari | Philipp Neumann | Jörg Wrachtrup
Source: npj Quantum Information (article, 2021-08-09)
Field: Materials Science — Materials Chemistry

Quantum Fourier transform for nanoscale quantum sensing Abstract The quantum Fourier transformation (QFT) is a key building block for a whole wealth of quantum algorithms. Despite its proven efficiency, only a few proof-of-principle demonstrations have been reported. Here we utilize QFT to enhance the performance of a quantum sensor. We implement the QFT algorithm in a hybrid quantum register consisting of a nitrogen-vacancy (NV) center electron spin and three nuclear spins. The QFT runs on the nuclear spins and serves to process the sensor—i.e., the NV electron spin signal. Specifically, we show the application of QFT for correlation spectroscopy, where the long correlation time benefits the use of the QFT in gaining maximum precision and dynamic range at the same time. We further point out the ability for demultiplexing the nuclear magnetic resonance (NMR) signals using QFT and demonstrate precision scaling with the number of used qubits. Our results mark the application of a complex quantum algorithm in sensing which is of particular interest for high dynamic range quantum sensing and nanoscale NMR spectroscopy experiments. Quantum sensor ; Quantum computer ; Spins ; Qubit ; Quantum Fourier transform ; Physics ; Quantum technology ; Quantum algorithm ; Nitrogen-vacancy center ; Quantum metrology ; Quantum information ; Quantum network ; Fourier transform ; Quantum error correction ; Quantum ; Quantum mechanics ; Open quantum system ; Condensed matter physics Diamond and Carbon-based Materials Research ; Atomic and Subatomic Physics Research ; Quantum Information and Cryptography
Authors: Mayyada M. H. El‐Sayed | Rasha E. Elsayed | Aya Attia | Hebatullah H. Farghal | Rasha A. Azzam | Tarek M. Madkour
Source: Carbohydrate Polymer Technologies and Applications (article, 2021-07-16)
Field: Chemistry — Organic Chemistry

Novel nanoporous membranes of bio-based cellulose acetate, poly(lactic acid) and biodegradable polyurethane in-situ impregnated with catalytic cobalt nanoparticles for the removal of Methylene Blue and Congo Red dyes from wastewater The discharge of contaminants of emerging concern (CECs) into water streams is becoming a major global issue. Herein, novel nanoporous membranes of bio-based cellulose acetate, poly(lactic acid) and biodegradable polyurethane in-situ impregnated with catalytic cobalt nanoparticles were synthesized and tested for the removal of Methylene Blue (MB) and Congo Red (CR) dyes from water. The bio-based polymers supported the formation of a network hydrogen bonding among different functional groups as confirmed using FTIR, which improved the membrane stability. Porogen was used to create nanopores within the film bulk, which were used to impregnate the membranes with cobalt nanoparticles that ensured the adsorption, degradation and removal of the hazardous contaminants from polluted water. Up to almost 60% of each of MB and CR were removed under UV irradiation, while adsorption was well described by the Linear and Langmuir isotherms, respectively. The thermodynamic study showed that the adsorption process is dissociative and, thus, involves photocatalytic dye degradation. Both dyes exhibited the same overall rate of adsorption, but CR showed a faster diffusion rate as predicted by the intra-particle diffusion model. Loading the nanoparticles into a biopolymeric matrix could potentially reduce the risks of their environmental release as free particles in water effluents. Congo red ; Adsorption ; Membrane ; Nanoparticle ; Chemical engineering ; Nanoporous ; Materials science ; Methylene blue ; Cellulose acetate ; Catalysis ; Chemistry ; Nuclear chemistry ; Photocatalysis ; Organic chemistry ; Nanotechnology Nanomaterials for catalytic reactions ; Adsorption and biosorption for pollutant removal ; Environmental remediation with nanomaterials
Authors: Subhankar Kundu | A. Kasem Chowdhury | Somen Nandi | Kankan Bhattacharyya | Abhijit Patra
Source: Chemical Science (article, 2021-01-01)
Field: Materials Science — Biomaterials

Deciphering the evolution of supramolecular nanofibers in solution and solid-state: a combined microscopic and spectroscopic approach Supramolecular self-assembly of small organic molecules has emerged as a powerful tool to construct well-defined micro- and nanoarchitecture through fine-tuning a range of intermolecular interactions. The size, shape, and optical properties of these nanostructures largely depend on the specific assembly of the molecular building units, temperature and polarity of the medium, and external stimuli. The engineering of supramolecular self-assembled nanostructures with morphology-dependent tunable emission is in high demand due to the promising scope in nanodevices and molecular machines. However, probing the evolution of molecular aggregates from the solution and directing the self-assembly process in a pre-defined fashion are challenging. In the present study, we have deciphered the sequential evolution of supramolecular nanofibers from solution to spherical and oblong-shaped nanoparticles through the variation of solvent polarity, tuning the hydrophobic-hydrophilic interactions. An intriguing case of molecular self-assembly has been elucidated employing a newly designed π-conjugated thiophene derivative (TPAn) through a combination of steady-state absorption, emission measurements, fluorescence correlation spectroscopy (FCS), and electron microscopy. The FCS analysis and microscopy results revealed that the small-sized nanofibers in the dispersion further agglomerated upon solvent evaporation, resulting in a network of nanofibers. Stimuli-responsive reversible interconversion between a network of nanofibers and spherical nanoaggregates was probed both in dispersion and solvent-evaporated state. The evolution of organic nanofibers and a subtle control over the self-assembly process demonstrated in the current investigation provide a general paradigm to correlate the size, shape, and emission properties of fluorescent molecular aggregates in complex heterogeneous media, including a human cell. Nanofiber ; Supramolecular chemistry ; Materials science ; Nanostructure ; Nanotechnology ; Self-assembly ; Intermolecular force ; Nanoparticle ; Molecule ; Chemistry ; Organic chemistry Supramolecular Self-Assembly in Materials ; Luminescence and Fluorescent Materials ; Polydiacetylene-based materials and applications
Authors: Mohammad Murwih Alidmat | Melati Khairuddean | N Norman | Anis Nasihah Mohamed Asri | Mohd Suhaimi | Garima Sharma
Source: Arabian Journal of Chemistry (article, 2021-07-06)
Field: Chemistry — Organic Chemistry

Synthesis, characterization, docking study and biological evaluation of new chalcone, pyrazoline, and pyrimidine derivatives as potent antimalarial compounds Malaria is a protozoan disease caused by a unicellular parasite named Plasmodium (Phylum- Apicomplexa). World Health Organization has estimated roughly fifty percent of the world’s community lives under the continuing threat of malaria. The focus of drug discovery has increased towards valuable structures known as chalcones, pyrazoline, and pyrimidine due to their extensive bioactivity in malaria treatment. In this study, four chalcone derivatives (1–4) have been synthesized via the Claisen-Schmidt condensation. New compounds of 12 pyrazolines (1–4)Ai-iii and eight pyrimidines, (1–4)Bi-ii derivatives have also been synthesized via a ring-closing reaction of the chalcones. All the synthesized compounds were characterized and tested against malaria. The results showed that compound 1Aiii exhibited significant antiproliferative effects against 3D7 and RKL9 with 3D7 = 2.1 μg/mL, IC80 3D7 = 8 μg/mL, and IC50 RKL9 when exposed to compared to the reference anticancer drug, CQ Chloroquine diphosphate, and Artemisinin. The molecular docking analysis showed that compounds 1, 1Aiii and 1Bi had entered the PfATP4 receptor pocket and had been stuck with the amino acids in a high affinity of binding. Chalcone ; Chemistry ; Pyrimidine ; Artemisinin ; Plasmodium falciparum ; Pyrazoline ; Stereochemistry ; Antimalarial Agent ; Docking (animal) ; Combinatorial chemistry ; Malaria ; Organic chemistry Synthesis and biological activity ; Synthesis and Biological Evaluation ; Computational Drug Discovery Methods