jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: William J. Gee
Source: Australian Journal of Chemistry (article, 2019-01-03)
Field: Materials Science — Materials Chemistry

Recent Trends Concerning Upconversion Nanoparticles and Near-IR Emissive Lanthanide Materials in the Context of Forensic Applications Upconversion nanoparticles (UCNPs) are materials that, upon absorbing multiple photons of low energy (e.g. infrared radiation), subsequently emit a single photon of higher energy, typically within the visible spectrum. The physics of these materials have been the subject of detailed investigations driven by the potential application of these materials as medical imaging devices. One largely overlooked application of UCNPs is forensic science, wherein the ability to produce visible light from infrared light sources would result in a new generation of fingerprint powders that circumvent background interference which can be encountered with visible and ultraviolet light sources. Using lower energy, infrared radiation would simultaneously improve the safety of forensic practitioners who often employ light sources in less than ideal locations. This review article covers the development of UCNPs, the use of infrared radiation to visualise fingerprints by the forensic sciences, and the potential benefits of applying UCNP materials over current approaches. Photon upconversion ; Infrared ; Nanotechnology ; Context (archaeology) ; Electromagnetic spectrum ; Materials science ; Photon ; Visible spectrum ; Optoelectronics ; Engineering physics ; Optics ; Physics ; Doping Luminescence Properties of Advanced Materials ; Radiation Detection and Scintillator Technologies ; Luminescence and Fluorescent Materials
Authors: Charlotte Flatebo | Sean S. E. Collins | Benjamin S. Hoener | Yiyu Cai | Stephan Link | Christy F. Landes
Source: The Journal of Physical Chemistry C (article, 2019-05-06)
Field: Chemistry — Electrochemistry

Electrodissolution Inhibition of Gold Nanorods with Oxoanions Metal nanoparticles experience varied chemical environments that can cause corrosion and dissolution in electronics, electrocatalysis, and sensing applications. Understanding oxidative dissolution is critical for plasmonic nanoparticles because their optical properties strongly depend on size and shape. We demonstrate that the addition of low relative concentrations of oxoanions to aqueous halide electrolyte solutions improves the morphological stability of plasmonic gold nanorods at anodic electrochemical potentials that otherwise induce complete oxidative electrodissolution. Single particle hyperspectral dark-field imaging and correlated scanning electron microscopy show that oxoanions alter the electrodissolution onset potential, electrodissolution pathway, and nanoparticle reaction heterogeneity, as compared to chloride-only electrolyte solutions. We identify five mechanistic contributors to the corrosion inhibition capabilities of oxoanions in the presence of chloride ions, with the aim of expanding the range of electrochemical sensing and catalysis applications for plasmonic metal nanoparticles. Of the contributors investigated, the pH, adsorption potential, and ionicity of the oxoanion are found to be the most influential factors, supporting the superior corrosion inhibition observed with bicarbonate and phosphate. Chemistry ; Dissolution ; Nanoparticle ; Nanorod ; Plasmon ; Electrolyte ; Electrochemistry ; Halide ; Chloride ; Corrosion ; Inorganic chemistry ; Chemical engineering ; Aqueous solution ; Nanotechnology ; Materials science ; Electrode ; Organic chemistry ; Physical chemistry Electrochemical Analysis and Applications ; Electrocatalysts for Energy Conversion ; Advanced Nanomaterials in Catalysis
Authors: Marianna Mamusa | Paolo Tempesti | Arianna Bartolini | Emiliano Carretti | Ahmad Ghobadi | Johan Smets | Yousef G. Aouad | Piero Baglioni
Source: Nanoscale (article, 2019-01-01)
Field: Chemistry — Organic Chemistry

Associative properties of poly(ethylene glycol)–poly(vinyl acetate) comb-like graft copolymers in water The self-assembly of amphiphilic graft copolymers is generally reported for polymer melts or polymers deposited onto surfaces, while a small number of cases deal with binary mixtures with water. We report on the associative properties of poly(ethylene glycol)-graft-poly(vinyl acetate) (PEG-g-PVAc) comb-like copolymers in water, demonstrating the existence of a percolative behaviour when increasing the PEG-g-PVAc content. Rheology, light- and small-angle X-ray scattering experiments, together with dissipative particle dynamics simulations, reveal a progressive transition from spherical polymer single-chain nanoparticles (SCNPs) towards hierarchically complex structures as the weight fraction of the polymer in water increases. The ability of PEG-g-PVAc to attain different nano- and microstructures is of great importance in numerous applications such as in the fields of cosmetics, detergency and drug delivery. Copolymer ; Ethylene glycol ; Materials science ; Polymer chemistry ; Vinyl acetate ; Ethylene-vinyl acetate ; Chemical engineering ; Composite material ; Polymer Advanced Polymer Synthesis and Characterization ; Surfactants and Colloidal Systems ; Microfluidic and Capillary Electrophoresis Applications
Authors: K. Michalska | Jennifer Gale | G. Joachimiak | Changsoo Chang | C. Hatzos-Skintges | B. Nocek | Stephen Johnston | L. Bigelow | Besnik Bajrami | R. Jedrzejczak | Samantha Wellington | Deborah T. Hung | Partha P. Nag | Stewart L. Fisher | M. Endres | A. Joachimiak
Source: IUCrJ (article, 2019-05-29)
Field: Materials Science — Materials Chemistry

Conservation of the structure and function of bacterial tryptophan synthases Tryptophan biosynthesis is one of the most characterized processes in bacteria, in which the enzymes from <i>Salmonella typhimurium</i> and <i>Escherichia coli</i> serve as model systems. Tryptophan synthase (TrpAB) catalyzes the final two steps of tryptophan biosynthesis in plants, fungi and bacteria. This pyridoxal 5'-phosphate (PLP)-dependent enzyme consists of two protein chains, α (TrpA) and β (TrpB), functioning as a linear αββα heterotetrameric complex containing two TrpAB units. The reaction has a complicated, multistep mechanism resulting in the β-replacement of the hydroxyl group of l-serine with an indole moiety. Recent studies have shown that functional TrpAB is required for the survival of pathogenic bacteria in macrophages and for evading host defense. Therefore, TrpAB is a promising target for drug discovery, as its orthologs include enzymes from the important human pathogens <i>Streptococcus pneumoniae</i>, <i>Legionella pneumophila</i> and <i>Francisella tularensis</i>, the causative agents of pneumonia, legionnaires' disease and tularemia, respectively. However, specific biochemical and structural properties of the TrpABs from these organisms have not been investigated. To fill the important phylogenetic gaps in the understanding of TrpABs and to uncover unique features of TrpAB orthologs to spearhead future drug-discovery efforts, the TrpABs from <i>L. pneumophila</i>, <i>F. tularensis</i> and <i>S. pneumoniae</i> have been characterized. In addition to kinetic properties and inhibitor-sensitivity data, structural information gathered using X-ray crystallo-graphy is presented. The enzymes show remarkable structural conservation, but at the same time display local differences in both their catalytic and allosteric sites that may be responsible for the observed differences in catalysis and inhibitor binding. This functional dissimilarity may be exploited in the design of species-specific enzyme inhibitors. Tryptophan ; Function (biology) ; Chemistry ; Computational biology ; Biochemistry ; Biology ; Computer science ; Cell biology ; Amino acid Enzyme Structure and Function ; Tryptophan and brain disorders ; Microbial Metabolic Engineering and Bioproduction
Authors: Sima Singh | Afzal Hussain | Faiyaz Shakeel | Mohamed Jawed Ahsan | Sultan Alshehri | Thomas J. Webster | Uma Ranjan Lal
Source: International Journal of Nanomedicine (review, 2019-03-31)
Field: Chemistry — Organic Chemistry

&lt;p&gt;Recent insights on nanomedicine for augmented infection control&lt;/p&gt; Antimicrobial agents have been widely investigated for protecting against microbial infections in modern health. Drug-related limitations, poor bioavailability, toxicity to mammalian cells, and frequent bacteria drug resistance are major challenges faced when exploited in nanomedicine forms. Specific attention has been paid to control nanomaterial-based infection against numerous challenging pathogens in addition to improved drug delivery, targeting, and pharmacokinetic (PK) profiles, and thus, efficient antimicrobials have been fabricated using diverse components (metals, metal oxides, synthetic and semisynthetic polymers, natural or biodegradable polymers, etc). The present review covers several nanocarriers delivered through various routes of administration, highlighting major findings to control microbial infection as compared to using the free drug. Results over the past decade support the consistent development of various nanomedicines capable of improving biological significance and therapeutic benefits against an array of microbial strains. Depending on the intended application of nanomedicine, infection control will be challenged by various factors such as weighing the risk-benefits in healthcare settings, nanomaterial-induced (eco)toxicological hazards, frequent development of antibiotic resistance, scarcity of in vivo toxicity data, and a poor understanding of microbial interactions with nanomedicine at the molecular level. This review summarizes well-established informative data for nanomaterials used for infection control and safety concerns of nanomedicines to healthcare sectors followed by the significance of a unique "safe-by-design" approach. Nanomedicine ; Nanocarriers ; Antimicrobial ; Drug delivery ; Biosafety ; Drug ; Nanotechnology ; Pharmacology ; Medicine ; Biotechnology ; Biology ; Materials science ; Microbiology ; Nanoparticle Antimicrobial agents and applications ; Nanoparticles: synthesis and applications ; Advancements in Transdermal Drug Delivery
Authors: Johanna Nykyri | Anke M. Herrmann | Sebastian Håkansson
Source: BMC Microbiology (article, 2019-03-21)
Field: Chemistry — Physical and Theoretical Chemistry

Isothermal microcalorimetry for thermal viable count of microorganisms in pure cultures and stabilized formulations Thermal viable count methods are novel methods for the rapid quantification of divergent bacterial and fungal species and enhance the speed, sensitivity, and accuracy of routine viable counts of pure cultures and controlled microbiomes such as plant seed coatings. Biology ; Isothermal microcalorimetry ; Viable count ; Serial dilution ; Microorganism ; Lactobacillus reuteri ; Bacillus amyloliquefaciens ; Microbiology ; Food science ; Lactobacillus ; Fermentation ; Bacteria thermodynamics and calorimetric analyses ; Essential Oils and Antimicrobial Activity ; Listeria monocytogenes in Food Safety
Authors: Roman Anufriev | Masahiro Nomura
Source: Nanomaterials (article, 2019-01-22)
Field: Materials Science — Materials Chemistry

Coherent Thermal Conduction in Silicon Nanowires with Periodic Wings Artificial periodic nanostructures, known as phononic crystals, promise to control the thermal properties of nanostructures in the coherent regime, which can be achieved in semiconductors at low temperatures. Here, we study coherent thermal conduction in silicon nanowires with added periodic wings at sub-Kelvin temperature. Our simulations show that the added periodic wings flatten the phonon dispersion and thus reduce the thermal conductance. We investigate the dependence of this reduction on the size of the wings and conclude that the reduction is mainly caused by the periodicity of the wings, rather than by local resonances in them. These findings help to better understand the mechanisms controlling coherent heat conduction in periodic resonant nanostructures. Thermal conduction ; Silicon ; Materials science ; Nanowire ; Phonon ; Thermal conductivity ; Nanostructure ; Condensed matter physics ; Semiconductor ; Thermal ; Silicon nanowires ; Dispersion (optics) ; Semiconductor nanostructures ; Nanotechnology ; Optoelectronics ; Optics ; Physics ; Composite material ; Thermodynamics Thermal properties of materials ; Thermal Radiation and Cooling Technologies ; Advanced Thermoelectric Materials and Devices
Authors: Qayyum Husain | A Kaur | U Gupta | S Ansari | Q Husain | Y Jiang | H Wang | S Li | W Wen | C Rao | S Vivekchand | K Biswasa | A Govindaraja | M Faramarzi | A Sadighi | Khomutov | S Gubin | P Raveendran | J Fu | S Wallen | B He | J Tan | K Liew | H Liu | R Bhattacharya | S Saha | K Vithiya | S Sen | H Korbekandi | S Iravani | S Abbasi | S Mirmohammadi | B Zolfaghari1 | S Prabhu | E Poulose | N Kulkarni | U Muddapur | X Li | H Xu | Z-S Chen | G Chen | R Kshatriya | Y Shaikh | G Nazeruddin | S Sunkar | C Nachiyar | M Khan | S Qayyum | F Alam | A Azam | H Schneidewind | T Schler | K Strelau | K Weber | D Cialla | M Diegel | R Mattheis | A Berger | R Mller | J Popp | A Jha | K Prasad | A Kulkarni | C Jayaseelan | A Rahuman | A Kirthi | S Marimuthu | T Santhoshkumar | A Bagavan | K Gaurav | L Karthik | K Bhaskara Rao | N Sandana | C Rose | U Jan | M Saleemuddin | S Bankar | M Bule | R Singhal | L Ananthanarayan | K Yasui
Source: Biointerface Research in Applied Chemistry (article, 2019-10-15)
Field: Materials Science — Materials Chemistry

An overview on the green synthesis of nanoparticles and other nano-materials using enzymes and their potential applications The applications of nanoparticles (NPs) and another nanomaterial (NM) are widely increasing in various fields including biomedical and clinical sciences. Conventional methods used for the synthesis of NM have several demerits like chemical procedures producing toxic materials and physical methods being costly and forming particles of non-uniform sizes. The use of such NM has prevented their applications in biomedical fields especially in clinical applications. In order to use NPs in clinical fields, there is a need to use reliable, nontoxic and eco-friendly methods for their synthesis. The use of eco-friendly and biological methods for the synthesis of NPs and other NM has attracted the attention of nanobiotechnologists due to synthesis of such particles by using nontoxic method. The enzymatic synthesis of NPs is highly specific as this procedure results in the formation of nontoxic materials of controlled shape, size and high stability. In this chapter an effort has been made to critically review recent developments in the area of biosynthesis of several types of NM by using enzymes of diverse groups such as oxidoreductases, transferases, hydrolases, lyases and ligases. The mechanisms of enzyme catalyzedsynthesis of NPs and the reaction conditions to control their shape, size, and stability of NPs have also been described. Numerous kinds of techniques employed for the identification and characterization of NM have been discussed. The biomedical and other applications of as-synthesized NM have also been mentioned in this article. Nanotechnology ; Nanoparticle ; Nanomaterials ; Characterization (materials science) ; Environmentally friendly ; Materials science ; Biology Nanoparticles: synthesis and applications ; Enzyme Catalysis and Immobilization ; Enzyme Production and Characterization
Authors: S.K. Gunavathy | H. Benita Sherine
Source: International Journal of Scientific Research in Biological Sciences (article, 2019-06-30)
Field: Chemistry — Analytical Chemistry

Determination of heavy metals and phytochemical analysis of some selected medicinal plants The International Scientific Research Organization for Science, Engineering and Technology (ISROSET) is a Non-Profit Organization; The ISROSET is dedicated to improvement in academic sectors of Science (Chemistry, Bio-chemistry, Zoology, Botany, Biotechnology, Pharmaceutical Science, Bioscience, Bioinformatics, Biometrics, Biostatistics, Microbiology, Environmental Management, Medical Science, Forensic Science, Home Science, Library Science, Material Science Military Science, Physical Science, Physical Education Science, Educational Science, Fisheries, seed technology, Agriculture, Forestry Science, Mathematics, Physics, Statistics and Geology/Earth Science), Computer Science, Engineering and Information Technology, Commerce, Management, Economics Sociology and Social Science. Biostatistics ; Applied science ; Medical science ; Engineering ethics ; Science education ; Environmental engineering science ; Agriculture ; Engineering ; Library science ; Social science ; Earth science ; Sociology ; Mathematics ; Computer science ; Ecology ; Mathematics education ; Medicine ; Biology ; Medical education ; Geology Heavy Metals in Plants
Authors: Baekjun Kim | Sangwon Lee | Jihan Kim
Source: ChemRxiv (preprint, 2019-04-12)
Field: Materials Science — Materials Chemistry

Inverse Design in Porous Materials Using Artificial Neural Networks Generating optimal nanomaterials using artificial neural networks can potentially lead to a significant revolution in future materials design. Although progress has been made in creating small and simple molecules, complex materials such as crystalline porous materials have yet to be generated using any of the neural networks. In this work, we have for the first time implemented a generative adversarial network that uses a training set of 31,713 known zeolites to produce 14 crystalline porous materials. Our neural network takes in inputs in the form of energy and material dimensions and we show that zeolites with a user-desired range of 4 kJ/mol methane heat of adsorption can be reliably produced using our neural network. The fine-tuning of user-desired capability can potentially accelerate materials development as it demonstrates a successful case of inverse design in porous materials. Artificial neural network ; Porous medium ; Inverse ; Porosity ; Computer science ; Materials science ; Generative grammar ; Process engineering ; Nanotechnology ; Artificial intelligence ; Engineering ; Mathematics ; Composite material Machine Learning in Materials Science ; Anodic Oxide Films and Nanostructures ; Zeolite Catalysis and Synthesis
Authors: Alberto Fabrizio | Benjamin Meyer | Raimón Fabregat | Clémence Corminbœuf
Source: CHIMIA International Journal for Chemistry (article, 2019-12-18)
Field: Materials Science — Materials Chemistry

Quantum Chemistry Meets Machine Learning In this account, we demonstrate how statistical learning approaches can be leveraged across a range of different quantum chemical areas to transform the scaling, nature, and complexity of the problems that we are tackling. Selected examples illustrate the power brought by kernel-based approaches in the large-scale screening of homogeneous catalysis, the prediction of fundamental quantum chemical properties and the free-energy landscapes of flexible organic molecules. While certainly non-exhaustive, these examples provide an intriguing glimpse into our own research efforts. Homogeneous ; Quantum chemical ; Scaling ; Computer science ; Quantum ; Kernel (algebra) ; Range (aeronautics) ; Quantum chemistry ; Scale (ratio) ; Quantum machine learning ; Machine learning ; Nanotechnology ; Artificial intelligence ; Statistical physics ; Quantum computer ; Molecule ; Physics ; Quantum mechanics ; Mathematics ; Materials science Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: Tomasz Badowski | Ewa Gajewska | Karol Molga | Bartosz A. Grzybowski
Source: Angewandte Chemie (article, 2019-11-21)
Field: Materials Science — Materials Chemistry

Synergy Between Expert and Machine‐Learning Approaches Allows for Improved Retrosynthetic Planning Abstract When computers plan multistep syntheses, they can rely either on expert knowledge or information machine‐extracted from large reaction repositories. Both approaches suffer from imperfect functions evaluating reaction choices: expert functions are heuristics based on chemical intuition, whereas machine learning (ML) relies on neural networks (NNs) that can make meaningful predictions only about popular reaction types. This paper shows that expert and ML approaches can be synergistic—specifically, when NNs are trained on literature data matched onto high‐quality, expert‐coded reaction rules, they achieve higher synthetic accuracy than either of the methods alone and, importantly, can also handle rare/specialized reaction types. Computer science ; Artificial intelligence ; Machine learning ; Heuristics ; Intuition ; Imperfect ; Expert system ; Artificial neural network ; Retrosynthetic analysis ; Plan (archaeology) ; Chemistry ; Cognitive science Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Chemical Synthesis and Analysis
Authors: Jingxia Cui | Wenze Li | Chao Fang | Shunting Su | Jiaoyang Luan | Ting Gao | Lihong Hu | Yinghua Lu | GuanHua Chen
Source: IEEE Access (article, 2019-01-01)
Field: Chemistry — Physical and Theoretical Chemistry

AdaBoost Ensemble Correction Models for TDDFT Calculated Absorption Energies Molecular excited states are important for molecular optical properties, which can be feasibly explored by quantum chemical calculations. However, the computation is highly demanding due to their complicated characteristic features. Therefore, high accuracy and unambiguous descriptions are strongly desired for excited state investigations. This paper proposes accurate, robust, and efficient ensemble correction models for absorption calculations with the most used quantum chemical method, time-dependent density functional theory (TDDFT). Models are built by AdaBoost framework with both weak machine learning: support vector machine (SVM), general regression neural network (GRNN), and an ensemble learning: the random forest (RF) regression method. With the models, the low accuracy calculations, TDDFT calculated absorption energies (λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">max</sub> ) for 433 organic molecules with the minimum basis set STO-3G, are significantly improved. The mean absolute error (MAE) and the root mean square error (RMSE) of the calculated λmax are reduced from 0.62 and 0.79 eV to 0.11 and 0.14 eV, respectively. The validation parameters of the proposed correction model can reach up to R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> (0.97), Q <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> (0.98), and Q <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">cv</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> (0.99), which suggests the great goodness-of-fit and predictability. This investigation illustrates that the proposed ensemble correction models by sophisticated algorithms are highly efficient and accurate. Therefore, it may serve as an alternative tool to establish good correction models for TDDFT absorption calculations, which could significantly improve the accuracy of TDDFT calculations and extend machine learning algorithms on other feature calculations of excited states. AdaBoost ; Time-dependent density functional theory ; Artificial intelligence ; Mean squared error ; Support vector machine ; Excited state ; Density functional theory ; Computer science ; Machine learning ; Physics ; Mathematics ; Statistics ; Atomic physics ; Quantum mechanics Photochemistry and Electron Transfer Studies ; Spectroscopy and Quantum Chemical Studies ; Spectroscopy and Laser Applications