jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Pieter De Gauquier | Kenno Vanommeslaeghe | Yvan Vander Heyden | Debby Mangelings
Source: Analytica Chimica Acta (review, 2021-07-22)
Field: Chemistry — Spectroscopy

Modelling approaches for chiral chromatography on polysaccharide-based and macrocyclic antibiotic chiral selectors: A review Chemistry ; Enantiomer ; Molecular descriptor ; Molecular model ; Molecular dynamics ; Biological system ; Enantioselective synthesis ; Computational chemistry ; Linear regression ; Quantitative structure–activity relationship ; Stereochemistry ; Organic chemistry ; Machine learning ; Computer science Analytical Chemistry and Chromatography ; Microfluidic and Capillary Electrophoresis Applications ; Chromatography in Natural Products
Authors: Daniel E. Widdowson | Marco M. Mosca | Angeles Pulido | Andrew I. Cooper | Vitaliy Kurlin
Source: match Communications in Mathematical and in Computer Chemistry (article, 2021-12-01)
Field: Chemistry — Physical and Theoretical Chemistry

Average minimum distances of periodic point sets – foundational invariants for mapping periodic crystals The fundamental model of any solid crystalline material (crystal) at the atomic scale is a periodic point set. The strongest natural equivalence of crystals is rigid motion or isometry that preserves all inter-atomic distances. Past comparisons of periodic structures often used manual thresholds, symmetry groups and reduced cells, which are discontinuous under perturbations or thermal vibrations of atoms. This work defines the infinite sequence of continuous isometry invariants (Average Minimum Distances) to progressively capture distances between neighbors. The asymptotic behaviour of the new invariants is theoretically proved in all dimensions for a wide class of sets including non-periodic. The proposed near linear time algorithm identified all different crystals in the world's largest Cambridge Structural Database within a few hours on a modest desktop. The ultra fast speed and proved continuity provide rigorous foundations to continuously parameterise the space of all periodic crystals as a high-dimensional extension of Mendeleev's table of elements. Isometry (Riemannian geometry) ; Periodic sequence ; Sequence (biology) ; Periodic table ; Mathematics ; Motion (physics) ; Equivalence (formal languages) ; Point (geometry) ; Periodic point ; Class (philosophy) ; Pure mathematics ; Geometry ; Mathematical analysis ; Physics ; Classical mechanics ; Computer science ; Chemistry ; Quantum mechanics History and advancements in chemistry ; Quasicrystal Structures and Properties ; X-ray Diffraction in Crystallography
Authors: Maria Carolina Muniz | Thomas E. Gartner | Marc Riera | Christopher Knight | Shuwen Yue | Francesco Paesani | Athanassios Z. Panagiotopoulos
Source: The Journal of Chemical Physics (article, 2021-06-02)
Field: Materials Science — Materials Chemistry

Vapor–liquid equilibrium of water with the MB-pol many-body potential Among the many existing molecular models of water, the MB-pol many-body potential has emerged as a remarkably accurate model, capable of reproducing thermodynamic, structural, and dynamic properties across water's solid, liquid, and vapor phases. In this work, we assessed the performance of MB-pol with respect to an important set of properties related to vapor-liquid coexistence and interfacial behavior. Through direct coexistence classical molecular dynamics simulations at temperatures of 400 K < T < 600 K, we calculated properties such as equilibrium coexistence densities, vapor-liquid interfacial tension, vapor pressure, and enthalpy of vaporization and compared the MB-pol results to experimental data. We also compared rigid vs fully flexible variants of the MB-pol model and evaluated system size effects for the properties studied. We found that the MB-pol model predictions are in good agreement with experimental data, even for temperatures approaching the vapor-liquid critical point; this agreement was largely insensitive to system sizes or the rigid vs flexible treatment of the intramolecular degrees of freedom. These results attest to the chemical accuracy of MB-pol and its high degree of transferability, thus enabling MB-pol's application across a large swath of water's phase diagram. Molecular dynamics ; Enthalpy ; Vaporization ; Phase diagram ; Phase (matter) ; Degree (music) ; Stability (learning theory) ; Lennard-Jones potential Block Copolymer Self-Assembly ; Phase Equilibria and Thermodynamics ; Material Dynamics and Properties
Authors: Marta Barea-Sepúlveda | Marta Ferreiro‐González | José Luis P. Calle | Gerardo F. Barbero | Jesús Ayuso | Miguel Palma
Source: Microchemical Journal (article, 2021-10-07)
Field: Chemistry — Analytical Chemistry

Comparison of different processing approaches by SVM and RF on HS-MS eNose and NIR Spectrometry data for the discrimination of gasoline samples In the quality control of flammable and combustible liquids, such as gasoline, both rapid analysis and automated data processing are of great importance from an economical viewpoint for the petroleum industry. The present work aims to evaluate the chemometric tools to be applied on the Headspace Mass Spectrometry (HS-MS eNose) and Near-Infrared Spectroscopy (NIRS) results to discriminate gasoline according to their Research Octane Number (RON). For this purpose, data from a total of 50 gasoline samples of two types of RON-95 and 98-analyzed by the two above-mentioned techniques were studied. The HS-MS eNose and NIRS data were combined with non-supervised exploratory techniques, such as Hierarchical Cluster Analysis (HCA), as well as other supervised classification techniques, namely Support Vector Machine (SVM) and Random Forest (RF). For supervised classification, the low-level data fusion was additionally applied to evaluate if the combined use of the data increases the scope of relevant information. The HCA results showed a clear clustering trend of the gasoline samples according to their RON with HS-MS eNose data. SVM in combination with 5-Fold Cross-Validation successfully classified 100% of the samples with the HS-MS eNose data set. The RF algorithm in combination with 5-Fold Cross-Validation achieved the best accuracy rate for the test set with the low-level data fusion system. Furthermore, it allowed us to identify the most important features that could define the differences between RON 95 and RON 98 gasoline. On the other hand, using the HS-MS eNose and NIRS low-level data fusion reached better results than those obtained using NIRS data individually, with accuracy rates of 100% in both SVM and RF performances with the test set. In general, the performance of the SVM and RF algorithms was found to be similar. Gasoline ; Support vector machine ; Random forest ; Data set ; Sensor fusion ; Pattern recognition (psychology) ; Artificial intelligence ; Computer science ; Data mining ; Chemistry Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Rebecca-Jo Vestergaard | Hiteshkumar B. Vasava | Doug Aspinall | Songchao Chen | Adam Gillespie | Viacheslav I. Adamchuk | Asim Biswas
Source: Sensors (article, 2021-10-11)
Field: Chemistry — Analytical Chemistry

Evaluation of Optimized Preprocessing and Modeling Algorithms for Prediction of Soil Properties Using VIS-NIR Spectroscopy The absorbance spectra for air-dried and ground soil samples from Ontario, Canada were collected in the visible and near-infrared (VIS-NIR) region from 343 to 2200 nm. The study examined thirteen combination of six preprocessing (1st derivative, 2nd derivative, Savitzky-Golay, Gap, SNV and Detrend) method included in 'prospectr' R package along with four modeling approaches: partial least square regression (PLSR), cubist, random forest (RF), and extreme learning machine (ELM) for prediction of the soil organic matter (SOM). The 1st derivative + gap, 2nd derivative + gap and standard normal variance (SNV) were the best preprocessing algorithms. Thus, only these three preprocessing algorithms along with four modeling approaches were used for prediction of soil pH, electrical conductively (EC), %sand, %silt, %clay, %very coarse sand (VCS), %coarse sand (CS), %medium sand (ms) and %fine sand (fs). The results showed that OM, pH, %sand, %silt and %CS were all predicted with confidence (R<sup>2</sup> > 0.60) and the combination of 1st derivative + gap and RF gained the best performance. A detailed comparison of the preprocessing and modeling algorithms for various soil properties in this study demonstrate that for better prediction of soil properties using VIS-NIR spectroscopy requires different preprocessing and modeling algorithms. However, in general RF and 1st derivative + gap can be labeled at the best combination of preprocessing and modelling algorithms. Preprocessor ; Algorithm ; Spectroscopy ; Computer science ; Data mining ; Artificial intelligence ; Physics Spectroscopy and Chemometric Analyses ; Soil Geostatistics and Mapping ; Mineral Processing and Grinding
Authors: Rakesh K. Sindhu | Agnieszka Najda | Prabhjot Kaur | Muddaser Shah | Harmanpreet Singh | Parneet Kaur | Simona Cavalu | Monika Jaroszuk-Sierocińska | Md. Habibur Rahman
Source: Materials (review, 2021-10-11)
Field: Materials Science — Materials Chemistry

Potentiality of Nanoenzymes for Cancer Treatment and Other Diseases: Current Status and Future Challenges Studies from past years have observed various enzymes that are artificial, which are issued to mimic naturally occurring enzymes based on their function and structure. The nanozymes possess nanomaterials that resemble natural enzymes and are considered an innovative class. This innovative class has achieved a brilliant response from various developments and researchers owing to this unique property. In this regard, numerous nanomaterials are inspected as natural enzyme mimics for multiple types of applications, such as imaging, water treatment, therapeutics, and sensing. Nanozymes have nanomaterial properties occurring with an inheritance that provides a single substitute and multiple platforms. Nanozymes can be controlled remotely via stimuli including heat, light, magnetic field, and ultrasound. Collectively, these all can be used to increase the therapeutic as well as diagnostic efficacies. These nanozymes have major biomedical applications including cancer therapy and diagnosis, medical diagnostics, and bio sensing. We summarized and emphasized the latest progress of nanozymes, including their biomedical mechanisms and applications involving synergistic and remote control nanozymes. Finally, we cover the challenges and limitations of further improving therapeutic applications and provide a future direction for using engineered nanozymes with enhanced biomedical and diagnostic applications. Nanotechnology ; Computer science ; Cancer therapy ; Biochemical engineering ; Cancer ; Materials science ; Medicine ; Engineering Advanced Nanomaterials in Catalysis ; Nanocluster Synthesis and Applications ; Advanced biosensing and bioanalysis techniques
Authors: Yanyan Cheng | Ling Liang | Fanggui Ye | Shulin Zhao
Source: Biosensors (article, 2021-06-23)
Field: Materials Science — Materials Chemistry

Ce-MOF with Intrinsic Haloperoxidase-Like Activity for Ratiometric Colorimetric Detection of Hydrogen Peroxide Metal-organic framework (MOF) nanozymes, as emerging members of the nanozymes, have received more and more attention due to their composition and structural characteristics. In this work, we report that mixed-valence state Ce-MOF (MVCM) has intrinsic haloperoxidase-mimicking activity. MVCM was synthesized by partial oxidation method using Ce-MOF as a precursor. In the presence of H<sub>2</sub>O<sub>2</sub> and Br<sup>-</sup>, MVCM can catalyze oxidative bromination of chromogenic substrate phenol red (PR) to produce the blue product bromophenol blue (Br<sub>4</sub>PR), showing good haloperoxidase-like activity. Because of the special chromogenic substrate, we constructed a ratiometric colorimetric-sensing platform by detecting the absorbance of the MVCM-(PR, Br<sup>-</sup>) system at wavelengths of 590 and 430, for quantifying H<sub>2</sub>O<sub>2</sub>, where the detection limit of the H<sub>2</sub>O<sub>2</sub> is 3.25 μM. In addition, the haloperoxidase-mimicking mechanism of the MVCM is proposed. Moreover, through enzyme kinetics monitoring, the <i>K<sub>m</sub></i> (H<sub>2</sub>O<sub>2</sub> and NH<sub>4</sub>Br) of the MVCM is lower than that of cerium oxide nanomaterials, indicating that the MVCM has a stronger binding affinity for H<sub>2</sub>O<sub>2</sub> and NH<sub>4</sub>Br than other materials. This work provides more application prospects for the development of nanozymes in the field of biosensors in the future. Chemistry ; Chromogenic ; Hydrogen peroxide ; Substrate (aquarium) ; Absorbance ; Biosensor ; Colorimetry ; Nanomaterials ; Combinatorial chemistry ; Detection limit ; Cerium ; Inorganic chemistry ; Nuclear chemistry ; Chromatography ; Nanotechnology ; Organic chemistry ; Biochemistry ; Materials science Advanced Nanomaterials in Catalysis ; Nanocluster Synthesis and Applications ; Advanced biosensing and bioanalysis techniques
Authors: Karol Molga | Sara Szymkuć | Bartosz A. Grzybowski
Source: Accounts of Chemical Research (article, 2021-01-11)
Field: Materials Science — Materials Chemistry

Chemist Ex Machina: Advanced Synthesis Planning by Computers Teaching computers to plan multistep syntheses of arbitrary target molecules-including natural products-has been one of the oldest challenges in chemistry, dating back to the 1960s. This Account recapitulates two decades of our group's work on the software platform called Chematica, which very recently achieved this long-sought objective and has been shown capable of planning synthetic routes to complex natural products, several of which were validated in the laboratory.For the machine to plan syntheses at an expert level, it must know the rules describing chemical reactions and use these rules to expand and search the networks of synthetic options. The rules must be of high quality: They must delineate accurately the scope of admissible substituents, capture all relevant stereochemical information, detect potential reactivity conflicts, and protection requirements. They should yield only those synthons that are chemically stable and energetically allowed (e.g., not too strained) and should be able to extrapolate beyond examples already published in the literature. In parallel, the network-search algorithms must be able to assign meaningful scores to the sets of synthons they encounter, make judicious choices which of the network's branches to expand, and when to withdraw from unpromising ones. They must be able to strategize over multiple steps to resolve intermittent reactivity conflicts, exchange functional groups, or overcome local maxima of molecular complexity.Meeting all these requirements makes the problem of computer-driven retrosynthesis very multifaceted, combining expert and AI approaches further supplemented by quantum-mechanical and molecular-mechanics calculations. Development of Chematica has been a very long and gradual process because all these components are needed. Any shortcuts-for example, reliance on only expert or only data-based approaches-yield chemically naïve and often erroneous syntheses, especially for complex targets. On the bright side, once all the requisite algorithms are implemented-as they now are-they not only streamline conventional synthetic planning but also enable completely new modalities that would challenge any human chemist, for example, synthesis with multiple constraints imposed simultaneously or library-wide syntheses in which the machine constructs "global plans" leading to multiple targets and benefiting from the use of common intermediates. These types of analyses will have profound impact on the practice of chemical industry, designing more economical, more green, and less hazardous pathways. Retrosynthetic analysis ; Synthon ; Scope (computer science) ; Computer science ; Plan (archaeology) ; Reactivity (psychology) ; Artificial intelligence ; Chemistry ; Total synthesis ; Programming language ; Organic chemistry Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Catalysis and Oxidation Reactions
Authors: Sukanta Nandi | Sumana Kumar | Abha Misra
Source: Materials Advances (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Zinc oxide heterostructures: advances in devices from self-powered photodetectors to self-charging supercapacitors ZnO—a versatile nanostructure for self-powered devices. Supercapacitor ; Heterojunction ; Materials science ; Zinc ; Nanostructure ; Photodetector ; Nanotechnology ; Optoelectronics ; Self-discharge ; Oxide ; Chemistry ; Capacitance ; Metallurgy ; Electrode ZnO doping and properties ; Supercapacitor Materials and Fabrication ; Advanced Sensor and Energy Harvesting Materials
Authors: Catalina Biglione | Thi Mai Phuong Neumann‐Tran | Sidra Kanwal | Daniel Klinger
Source: Journal of Polymer Science (article, 2021-10-19)
Field: Materials Science — Materials Chemistry

Amphiphilic micro‐ and nanogels: Combining properties from internal hydrogel networks, solid particles, and micellar aggregates Abstract Polymeric micro‐ and nanogels are defined by their water‐swollen hydrophilic networks that can often impart outstanding biocompatibility and high‐colloidal stability. Unfortunately, this highly hydrophilic nature limits their potential in areas where hydrophobic or amphiphilic interactions are required, for example, the delivery of hydrophobic cargoes or tailored interactions with amphipathic (bio‐)surfaces. To overcome this limitation, amphiphilic micro−/nanogels are emerging as new colloidal materials that combine properties from hydrogel networks with hydrophobic segments, known from solid hydrophobic polymer particles or micellar cores. The ability to accurately adjust the balance of hydrophobic and hydrophilic components in such amphiphilic colloidal systems enables new tailored properties. This opens up new applications ranging from the controlled and sustained delivery of hydrophobic drugs, over carriers for catalytic moieties, to their assembly at hydrophilic/hydrophobic interfaces, for example, as advanced stabilizers in Pickering emulsions. While promising, the synthetic realization of such amphiphilic materials remains challenging since hydrophobic and hydrophilic moieties need to be combined in a single colloidal system. As a result, adjusting the micro−/nanogel amphiphilicity often changes the colloidal features too. To overcome these limitations, various strategies have been reported. The aim of this review is to give a brief overview of important synthetic tools, considering both advantages and disadvantages, thus critically evaluating their potential in different research fields. Amphiphile ; Nanogel ; Nanotechnology ; Biocompatibility ; Materials science ; Colloid ; Polymer ; Hydrophobic effect ; Self-healing hydrogels ; Hydrophobe ; Chemical engineering ; Drug delivery ; Chemistry ; Organic chemistry ; Copolymer ; Polymer chemistry Pickering emulsions and particle stabilization ; Advanced Polymer Synthesis and Characterization ; Polymer Surface Interaction Studies
Authors: Chenxi Peng | Xue Chen | Meiling Chen | Shenci Lu | Yu Wang | Suli Wu | Xiaowang Liu | Wei Huang
Source: Research (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Afterglow Carbon Dots: From Fundamentals to Applications The ability of carbon dots (CDs) to emit afterglow emission in addition to fluorescence in response to UV-to-visible excitation allows them to be a new class of luminescent materials. When compared with traditional organic or inorganic afterglow materials, CDs have a set of advantages, including small size, ease of synthesis, and absence of highly toxic metal ions. In addition, high dependence of their afterglow color output on temperature, excitation wavelength, and aggregation degrees adds remarkable flexibility in the creation of multimode luminescence of CDs without the need for changing their intrinsic attributes. These characteristics make CDs particularly attractive in the fields of sensing, anticounterfeiting, and data encryption. In this review, we first describe the general attributes of afterglow CDs and their fundamental afterglow mechanism. We then highlight recent strategic advances in the generation or activation of the afterglow luminescence of CDs. Considerable emphasis is placed on the summarization of their emergent afterglow properties in response to external stimulation. We further highlight the emerging applications of afterglow CDs on the basis of their unique optical features and present the key challenges needed to be addressed before the realization of their full practical utility. Afterglow ; Luminescence ; Materials science ; Flexibility (engineering) ; Nanotechnology ; Optoelectronics ; Physics ; Astrophysics ; Mathematics ; Gamma-ray burst Carbon and Quantum Dots Applications ; Luminescence and Fluorescent Materials ; Nanocluster Synthesis and Applications
Authors: Xin Chen | Cian Bartlam | Vicent Lloret | Narine Moses Badlyan | Stefan Wolff | Roland Gillen | Tanja Stimpel‐Lindner | Janina Maultzsch | Georg S. Duesberg | Kathrin C. Knirsch | Andreas Hirsch
Source: Angewandte Chemie International Edition (article, 2021-03-26)
Field: Materials Science — Materials Chemistry

Covalent Bisfunctionalization of Two‐Dimensional Molybdenum Disulfide Covalent functionalization of two-dimensional molybdenum disulfide (2D MoS<sub>2</sub> ) holds great promise in developing robust organic-MoS<sub>2</sub> hybrid structures. Herein, for the first time, we demonstrate an approach to building up a bisfunctionalized MoS<sub>2</sub> hybrid structure through successively reacting activated MoS<sub>2</sub> with alkyl iodide and aryl diazonium salts. This approach can be utilized to modify both colloidal and substrate supported MoS<sub>2</sub> nanosheets. We have discovered that compared to the adducts formed through the reactions of MoS<sub>2</sub> with diazonium salts, those formed through the reactions of MoS<sub>2</sub> with alkyl iodides display higher reactivity towards further reactions with electrophiles. We are convinced that our systematic study on the formation and reactivity of covalently functionalized MoS<sub>2</sub> hybrids will provide some practical guidance on multi-angle tailoring of the properties of 2D MoS<sub>2</sub> for various potential applications. Covalent bond ; Alkyl ; Electrophile ; Reactivity (psychology) ; Molybdenum disulfide ; Chemistry ; Surface modification ; Aryl ; Adduct ; Molybdenum ; Combinatorial chemistry ; Iodide ; Substrate (aquarium) ; Disulfide bond ; Hybrid material ; Polymer chemistry ; Organic chemistry ; Materials science ; Catalysis 2D Materials and Applications ; Covalent Organic Framework Applications ; MXene and MAX Phase Materials