jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: R. Pandiselvam | V. Prithviraj | M. R. Manikantan | Anjineyulu Kothakota | Alexandru Rusu | Monica Trif | Amin Mousavi Khaneghah
Source: Frontiers in Nutrition (review, 2022-10-12)
Field: Chemistry — Analytical Chemistry

Recent advancements in NIR spectroscopy for assessing the quality and safety of horticultural products: A comprehensive review The qualitative and quantitative evaluation of agricultural products has often been carried out using traditional, i.e., destructive, techniques. Due to their inherent disadvantages, non-destructive methods that use near-infrared spectroscopy (NIRS) coupled with chemometrics could be useful for evaluating various agricultural products. Advancements in computational power, machine learning, regression models, artificial neural networks (ANN), and other predictive tools have made their way into NIRS, improving its potential to be a feasible alternative to destructive measurements. Moreover, the incorporation of suitable preprocessing techniques and wavelength selection methods has arguably proven its practical feasibility. This review focuses on the various computation methods used for processing the spectral data collected and discusses the potential applications of NIRS for evaluating the quality and safety of agricultural products. The challenges associated with this technology are also discussed, as well as potential future perspectives. We conclude that NIRS is a potentially useful tool for the rapid assessment of the quality and safety of agricultural products. Chemometrics ; Computer science ; Quality (philosophy) ; Artificial neural network ; Biochemical engineering ; Preprocessor ; Risk analysis (engineering) ; Machine learning ; Artificial intelligence ; Engineering ; Business Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Water Quality Monitoring and Analysis
Authors: Amal Kaddoumi | Thomas S. Denney | Gopikrishna Deshpande | Jennifer L. Robinson | Ronald J. Beyers | David T. Redden | Domenico Praticò | Tassos C. Kyriakides | Bonian Lu | Anna N. Kirby | Darren T. Beck | Nancy D. Merner
Source: Nutrients (article, 2022-12-01)
Field: Chemistry — Organic Chemistry

Extra-Virgin Olive Oil Enhances the Blood–Brain Barrier Function in Mild Cognitive Impairment: A Randomized Controlled Trial Mild cognitive impairment (MCI) and early Alzheimer's disease (AD) are characterized by blood-brain barrier (BBB) breakdown leading to abnormal BBB permeability ahead of brain atrophy or dementia. Previous findings in AD mouse models have reported the beneficial effect of extra-virgin olive oil (EVOO) against AD, which improved BBB and memory functions and reduced brain amyloid-β (Aβ) and related pathology. This work aimed to translate these preclinical findings to humans in individuals with MCI. We examined the effect of daily consumption of refined olive oil (ROO) and EVOO for 6 months in MCI subjects on BBB permeability (assessed by contrast-enhanced MRI), and brain function (assessed using functional-MRI) as the primary outcomes. Cognitive function and AD blood biomarkers were also assessed as the secondary outcomes. Twenty-six participants with MCI were randomized with 25 participants completed the study. EVOO significantly improved clinical dementia rating (CDR) and behavioral scores. EVOO also reduced BBB permeability and enhanced functional connectivity. While ROO consumption did not alter BBB permeability or brain connectivity, it improved CDR scores and increased functional brain activation to a memory task in cortical regions involved in perception and cognition. Moreover, EVOO and ROO significantly reduced blood Aβ<sub>42</sub>/Aβ<sub>40</sub> and p-tau/t-tau ratios, suggesting that both altered the processing and clearance of Aβ. In conclusion, EVOO and ROO improved CDR and behavioral scores; only EVOO enhanced brain connectivity and reduced BBB permeability, suggesting EVOO biophenols contributed to such an effect. This proof-of-concept study justifies further clinical trials to assess olive oil's protective effects against AD and its potential role in preventing MCI conversion to AD and related dementias. Dementia ; Episodic memory ; Blood–brain barrier ; Atrophy ; Cognitive decline ; Medicine ; Clinical Dementia Rating ; Cognition ; Cognitive impairment ; Olive oil ; Neuroscience ; Internal medicine ; Disease ; Psychology ; Biology ; Central nervous system ; Food science Edible Oils Quality and Analysis ; Neurological Disease Mechanisms and Treatments ; Cholesterol and Lipid Metabolism
Authors: Lorenzo Lisuzzo | Giuseppe Cavallaro | Stefana Milioto | Giuseppe Lazzara
Source: Advanced Materials Interfaces (article, 2022-02-05)
Field: Materials Science — Materials Chemistry

Pickering Emulsions Stabilized by Halloysite Nanotubes: From General Aspects to Technological Applications Abstract Besides surfactants, which decrease the interfacial tension between two immiscible liquids, also interfacially active particles can successfully stabilize an emulsion system by attaching at the liquid–liquid interface. The preparation of the resulting Pickering emulsions has been so far investigated starting from the study of the interactions arising between the dispersed droplets and the stabilizers, till the application of these systems in a wide range of different fields. This work is intended to provide an overall overview about the development of Pickering emulsions by considering the most general aspects and scanning the diverse types of solid stabilizers. Among them, Halloysite nanotubes play a major role as naturally derived clay with emulsifying capability owing to their cheap, abundant, green and biocompatible properties. Therefore, the design of Halloysite stabilized Pickering emulsions is the main content of this review, which will survey the role of nanotubes in providing colloidal stability and will comprehensively sum up the use of these particles in technological and industrial purposes: from environmental to catalytic, from health to cultural heritage related applications. Halloysite ; Pickering emulsion ; Materials science ; Nanotechnology ; Emulsion ; Surface tension ; Chemical engineering ; Composite material ; Nanoparticle ; Engineering Pickering emulsions and particle stabilization ; Clay minerals and soil interactions ; Therapeutic Uses of Natural Elements
Authors: Anirban Mondal | Ryojun Toyoda | Romain Costil | Ben L. Feringa
Source: Angewandte Chemie International Edition (review, 2022-07-19)
Field: Chemistry — Organic Chemistry

Chemically Driven Rotatory Molecular Machines Molecular machines are at the frontier of biology and chemistry. The ability to control molecular motion and emulating the movement of biological systems are major steps towards the development of responsive and adaptive materials. Amazing progress has been seen for the design of molecular machines including light-induced unidirectional rotation of overcrowded alkenes. However, the feasibility of inducing unidirectional rotation about a single bond as a result of chemical conversion has been a challenging task. In this Review, an overview of approaches towards the design, synthesis, and dynamic properties of different classes of atropisomers which can undergo controlled switching or rotation under the influence of a chemical stimulus is presented. They are categorized as molecular switches, rotors, motors, and autonomous motors according to their type of response. Furthermore, we provide a future perspective and challenges focusing on building sophisticated molecular machines. Computer science Supramolecular Chemistry and Complexes ; Porphyrin and Phthalocyanine Chemistry ; Photoreceptor and optogenetics research
Authors: Fakhria Al-Joufi | Aseem Setia | Mounir Salem-Bekhit | Ram Sahu | Fulwah Alqahtani | Retno Widyowati | Fadilah Aleanizy
Source: Nanomaterials (article, 2022-01-04)
Field: Materials Science — Biomaterials

Molecular Pathogenesis of Colorectal Cancer with an Emphasis on Recent Advances in Biomarkers, as Well as Nanotechnology-Based Diagnostic and Therapeutic Approaches Colorectal cancer (CRC) is a serious disease that affects millions of people throughout the world, despite considerable advances in therapy. The formation of colorectal adenomas and invasive adenocarcinomas is the consequence of a succession of genetic and epigenetic changes in the normal colonic epithelium. Genetic and epigenetic processes associated with the onset, development, and metastasis of sporadic CRC have been studied in depth, resulting in identifying biomarkers that might be used to predict behaviour and prognosis beyond staging and influence therapeutic options. A novel biomarker, or a group of biomarkers, must be discovered in order to build an accurate and clinically useful test that may be used as an alternative to conventional methods for the early detection of CRC and to identify prospective new therapeutic intervention targets. To minimise the mortality burden of colorectal cancer, new screening methods with higher accuracy and nano-based diagnostic precision are needed. Cytotoxic medication has negative side effects and is restricted by medication resistance. One of the most promising cancer treatment techniques is the use of nano-based carrier system as a medication delivery mechanism. To deliver cytotoxic medicines, targeted nanoparticles might take advantage of differently expressed molecules on the surface of cancer cells. The use of different compounds as ligands on the surface of nanoparticles to interact with cancer cells, enabling the efficient delivery of antitumor medicines. Formulations based on nanoparticles might aid in early cancer diagnosis and help to overcome the limitations of traditional treatments, including low water solubility, nonspecific biodistribution, and restricted bioavailability. This article addresses about the molecular pathogenesis of CRC and highlights about biomarkers. It also provides conceptual knowledge of nanotechnology-based diagnostic techniques and therapeutic approaches for malignant colorectal cancer. Colorectal cancer ; Cancer ; Epigenetics ; Metastasis ; Disease ; Precision medicine ; Molecular diagnostics Nanoparticle-Based Drug Delivery ; Colorectal Cancer Treatments and Studies ; Colorectal Cancer Screening and Detection
Authors: Suxi Wang | Pin Jin Ong | Songlin Liu | Warintorn Thitsartarn | Maureen Janet Beng Hoon Tan | Ady Suwardi | Qiang Zhu | Xian Jun Loh
Source: Chemistry - An Asian Journal (review, 2022-07-22)
Field: Materials Science — Biomaterials

Recent Advances in Host‐Guest Supramolecular Hydrogels for Biomedical Applications The recognition-directed host-guest interaction is recognized as a valuable tool for creating supramolecular polymers. Functional hydrogels constructed through the dynamic and reversible host-guest complexation are endowed with a great many appealing features, such as superior self-healing, injectability, flexibility, stimuli-responsiveness and biocompatibility, which are crucial for biological and medicinal applications. With numerous topological structures and host-guest combinations established previously, recent breakthroughs in this area mostly focus on further improvement and fine-tuning of various properties for practical utilizations. The current contribution provides a comprehensive overview of the latest developments in host-guest supramolecular hydrogels, with a particular emphasis on the innovative molecular-level design strategies and hydrogel formation methodologies targeting at a wide range of active biomedical domains, including drug delivery, 3D printing, wound healing, tissue engineering, artificial actuators, biosensors, etc. Furthermore, a brief conclusion and discussion on the steps forward to bring these smart hydrogels to clinical practice is also presented. Self-healing hydrogels ; Nanotechnology ; Supramolecular chemistry ; Flexibility (engineering) ; Drug delivery ; Computer science ; Biocompatibility ; Tissue engineering ; Materials science ; Biomedical engineering ; Chemistry ; Engineering Supramolecular Self-Assembly in Materials ; Hydrogels: synthesis, properties, applications ; Advanced Polymer Synthesis and Characterization
Authors: Rakesh R. Panicker | Akella Sivaramakrishna
Source: Coordination Chemistry Reviews (article, 2022-02-10)
Field: Chemistry — Organic Chemistry

Remarkably flexible 2,2′:6′,2″-terpyridines and their group 8–10 transition metal complexes – Chemistry and applications Chemistry ; Ligand (biochemistry) ; Transition metal ; Coordination complex ; Catalysis ; Terpyridine ; Combinatorial chemistry ; Pyridine ; Organometallic chemistry ; Halogen ; Main group element ; Metal ; Nanotechnology ; Organic chemistry Synthesis and Biological Evaluation ; N-Heterocyclic Carbenes in Organic and Inorganic Chemistry ; Synthesis and Reactivity of Heterocycles
Authors: Qiang Yue | Bin Liu | Gang Liao | Bing‐Feng Shi
Source: ACS Catalysis (article, 2022-07-18)
Field: Chemistry — Organic Chemistry

Binaphthyl Scaffold: A Class of Versatile Structure in Asymmetric C–H Functionalization Over the past decades, transition metal-catalyzed enantioselective C–H functionalization has emerged as a straightforward and powerful tool for the rapid access to chiral molecules. The enormous advances achieved in this emerging area largely rely on the development of chiral ligands that can enable both high levels of enantiocontrol and efficiency. Chiral ligands bearing binaphthyl scaffolds have been proven to be versatile in asymmetric C–H functionalization due to their availability, unique stereochemical features, and ease of fine-tuning steric and electronic properties. In this Review, we summarized the advance in the applications of chiral ligands on the basis of the binaphthyl scaffold in asymmetric C–H functionalization. Surface modification ; Enantioselective synthesis ; Steric effects ; Combinatorial chemistry ; Scaffold ; Nanotechnology ; Chemistry ; Catalysis ; Molecule ; Materials science ; Stereochemistry ; Organic chemistry ; Computer science Catalytic C–H Functionalization Methods ; Synthesis and Catalytic Reactions ; Asymmetric Hydrogenation and Catalysis
Authors: Sakiat Hossain | Daisuke Hirayama | Ayaka Ikeda | Mai Ishimi | Sota Funaki | Arpan Samanta | Tokuhisa Kawawaki | Yuichi Negishi
Source: Aggregate (article, 2022-07-30)
Field: Materials Science — Materials Chemistry

Atomically precise thiolate‐protected gold nanoclusters: Current status of designability of the structure and physicochemical properties Abstract Thiolate (SR)‐protected gold nanoclusters (Au n (SR) m NCs) are a rare type of material capable of simultaneously exhibiting multiple physicochemical properties well‐suited to specific applications, including photoluminescence, thermocatalysis, electrocatalysis, photocatalysis, magnetism, and optical activity. Over the past several decades, there has been tremendous progress in our understanding of the structure and physicochemical properties of Au n (SR) m NCs, resulting in the ability to fine‐tune the characteristics of these materials. It is therefore helpful to examine the extent to which the properties of Au n (SR) m and related metal NCs can now be adjusted based on design. This review presents representative examples of previous studies concerning the geometry, electronic structure, luminescence properties, catalysis, magnetism and optical activity of Au n (SR) m and related metal NCs and discusses the current status of the designability of these NCs to impart specific structural and physicochemical characteristics. This information is expected to accelerate the fabrication of highly functional materials based on Au n (SR) m and related metal NCs. Nanoclusters ; Magnetism ; Photoluminescence ; Nanotechnology ; Materials science ; Fabrication ; Electrocatalyst ; Metal ; Luminescence ; Chemistry ; Physical chemistry ; Optoelectronics ; Metallurgy ; Physics ; Electrochemistry ; Condensed matter physics Nanocluster Synthesis and Applications ; Advanced Nanomaterials in Catalysis ; Quantum Dots Synthesis And Properties
Authors: Akim Khobotov‐Bakishev | Laura Hernández‐López | Cornelia von Baeckmann | Jorge Albalad | Arnau Carné‐Sánchez | Daniel Maspoch
Source: Advanced Science (review, 2022-02-04)
Field: Chemistry — Inorganic Chemistry

Metal–Organic Polyhedra as Building Blocks for Porous Extended Networks Metal-organic polyhedra (MOPs) are a subclass of coordination cages that can adsorb and host species in solution and are permanently porous in solid-state. These characteristics, together with the recent development of their orthogonal surface chemistry and the assembly of more stable cages, have awakened the latent potential of MOPs to be used as building blocks for the synthesis of extended porous networks. This review article focuses on exploring the key developments that make the extension of MOPs possible, highlighting the most remarkable examples of MOP-based soft materials and crystalline extended frameworks. Finally, the article ventures to offer future perspectives on the exploitation of MOPs in fields that still remain ripe toward the use of such unorthodox molecular porous platforms. Polyhedron ; Porosity ; Nanotechnology ; Porous medium ; Metal-organic framework ; Materials science ; Adsorption ; Computer science ; Chemistry ; Geometry ; Mathematics ; Physical chemistry ; Composite material Metal-Organic Frameworks: Synthesis and Applications ; Supramolecular Chemistry and Complexes ; Supramolecular Self-Assembly in Materials
Authors: Lingyu Huang | Kang Xu | Dandan Yuan | Jin Hu | Xinwei Wang | Shaolin Xu
Source: Nature Communications (article, 2022-10-03)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Sub-wavelength patterned pulse laser lithography for efficient fabrication of large-area metasurfaces Rigorously designed sub-micrometer structure arrays are widely used in metasurfaces for light modulation. One of the glaring restrictions is the unavailability of easily accessible fabrication methods to efficiently produce large-area and freely designed structure arrays with nanoscale resolution. We develop a patterned pulse laser lithography (PPLL) approach to create structure arrays with sub-wavelength feature resolution and periods from less than 1 μm to over 15 μm on large-area thin films with substrates under ambient conditions. Separated ultrafast laser pulses with patterned wavefront by quasi-binary phase masks rapidly create periodic ablated/modified structures by high-speed scanning. The gradient intensity boundary and circular polarization of the wavefront weaken diffraction and polarization-dependent asymmetricity effects during light propagation for high uniformity. Structural units of metasurfaces are obtained on metal and inorganic photoresist films, such as antennas, catenaries, and nanogratings. We demonstrate a large-area metasurface (10 × 10 mm<sup>2</sup>) revealing excellent infrared absorption (3-7 μm), which comprises 250,000 concentric rings and takes only 5 minutes to produce. Materials science ; Optics ; Wavefront ; Lithography ; Laser ; Fabrication ; Optoelectronics ; Photoresist ; Wavelength ; Ultrashort pulse ; Diffraction ; Photolithography ; Holography ; Polarization (electrochemistry) ; Nanotechnology ; Physics Metamaterials and Metasurfaces Applications ; Orbital Angular Momentum in Optics ; Random lasers and scattering media
Authors: Huziel E. Sauceda | Luis E. Gálvez-González | Stefan Chmiela | Lauro Oliver Paz‐Borbón | Klaus‐Robert Müller | Alexandre Tkatchenko
Source: Nature Communications (article, 2022-06-29)
Field: Materials Science — Materials Chemistry

BIGDML—Towards accurate quantum machine learning force fields for materials Machine-learning force fields (MLFF) should be accurate, computationally and data efficient, and applicable to molecules, materials, and interfaces thereof. Currently, MLFFs often introduce tradeoffs that restrict their practical applicability to small subsets of chemical space or require exhaustive datasets for training. Here, we introduce the Bravais-Inspired Gradient-Domain Machine Learning (BIGDML) approach and demonstrate its ability to construct reliable force fields using a training set with just 10-200 geometries for materials including pristine and defect-containing 2D and 3D semiconductors and metals, as well as chemisorbed and physisorbed atomic and molecular adsorbates on surfaces. The BIGDML model employs the full relevant symmetry group for a given material, does not assume artificial atom types or localization of atomic interactions and exhibits high data efficiency and state-of-the-art energy accuracies (errors substantially below 1 meV per atom) for an extended set of materials. Extensive path-integral molecular dynamics carried out with BIGDML models demonstrate the counterintuitive localization of benzene-graphene dynamics induced by nuclear quantum effects and their strong contributions to the hydrogen diffusion coefficient in a Pd crystal for a wide range of temperatures. Computer science ; Molecular dynamics ; Atom (system on chip) ; Force field (fiction) ; Statistical physics ; Domain (mathematical analysis) ; Chemical physics ; Physics ; Materials science ; Nanotechnology ; Artificial intelligence ; Quantum mechanics ; Mathematics Machine Learning in Materials Science ; Nuclear Physics and Applications ; X-ray Diffraction in Crystallography
Authors: Tian Xie | Arthur France‐Lanord | Yanming Wang | Jeffrey Lopez | Michael A. Stolberg | Megan R. Hill | Graham Leverick | Rafael Gómez‐Bombarelli | Jeremiah A. Johnson | Yang Shao‐Horn | Jeffrey C. Grossman
Source: Nature Communications (article, 2022-06-14)
Field: Materials Science — Materials Chemistry

Accelerating amorphous polymer electrolyte screening by learning to reduce errors in molecular dynamics simulated properties Polymer electrolytes are promising candidates for the next generation lithium-ion battery technology. Large scale screening of polymer electrolytes is hindered by the significant cost of molecular dynamics (MD) simulation in amorphous systems: the amorphous structure of polymers requires multiple, repeated sampling to reduce noise and the slow relaxation requires long simulation time for convergence. Here, we accelerate the screening with a multi-task graph neural network that learns from a large amount of noisy, unconverged, short MD data and a small number of converged, long MD data. We achieve accurate predictions of 4 different converged properties and screen a space of 6247 polymers that is orders of magnitude larger than previous computational studies. Further, we extract several design principles for polymer electrolytes and provide an open dataset for the community. Our approach could be applicable to a broad class of material discovery problems that involve the simulation of complex, amorphous materials. Amorphous solid ; Computer science ; Molecular dynamics ; Electrolyte ; Relaxation (psychology) ; Polymer ; Noise (video) ; Materials science ; Artificial intelligence ; Chemistry ; Computational chemistry Machine Learning in Materials Science ; Fuel Cells and Related Materials ; Advanced Battery Materials and Technologies
Authors: Chunyu Guo | Xingjun Duan | Zhi Fang | Yunsong Zhao | Tao Yang | Enhui Wang | Xinmei Hou
Source: Acta Materialia (article, 2022-09-22)
Field: Materials Science — Materials Chemistry

A new strategy for long-term complex oxidation of MAX phases: Database generation and oxidation kinetic model establishment with aid of machine learning Computer science ; Term (time) ; Work (physics) ; Artificial intelligence ; Materials science ; Machine learning ; Thermodynamics ; Physics MXene and MAX Phase Materials ; Machine Learning in Materials Science ; Advanced Photocatalysis Techniques