jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Basma A. Omran | Kwang-Hyun Baek
Source: Molecules (review, 2021-11-21)
Field: Materials Science — Materials Chemistry

Nanoantioxidants: Pioneer Types, Advantages, Limitations, and Future Insights Free radicals are generated as byproducts of normal metabolic processes as well as due to exposure to several environmental pollutants. They are highly reactive species, causing cellular damage and are associated with a plethora of oxidative stress-related diseases and disorders. Antioxidants can control autoxidation by interfering with free radical propagation or inhibiting free radical formation, reducing oxidative stress, improving immune function, and increasing health longevity. Antioxidant functionalized metal nanoparticles, transition metal oxides, and nanocomposites have been identified as potent nanoantioxidants. They can be formulated in monometallic, bimetallic, and multi-metallic combinations via chemical and green synthesis techniques. The intrinsic antioxidant properties of nanomaterials are dependent on their tunable configuration, physico-chemical properties, crystallinity, surface charge, particle size, surface-to-volume ratio, and surface coating. Nanoantioxidants have several advantages over conventional antioxidants, involving increased bioavailability, controlled release, and targeted delivery to the site of action. This review emphasizes the most pioneering types of nanoantioxidants such as nanoceria, silica nanoparticles, polydopamine nanoparticles, and nanocomposite-, polysaccharide-, and protein-based nanoantioxidants. This review overviews the antioxidant potential of biologically synthesized nanomaterials, which have emerged as significant alternatives due to their biocompatibility and high stability. The promising nanoencapsulation nanosystems such as solid lipid nanoparticles, nanostructured lipid carriers, and liposome nanoparticles are highlighted. The advantages, limitations, and future insights of nanoantioxidant applications are discussed. Nanomaterials ; Nanotechnology ; Nanoparticle ; Biocompatibility ; Chemistry ; Oxidative stress ; Antioxidant ; Nanocomposite ; Materials science ; Organic chemistry ; Biochemistry Advanced Nanomaterials in Catalysis ; Nanoparticles: synthesis and applications ; Gold and Silver Nanoparticles Synthesis and Applications
Authors: Nicolò Mauro | Mara Andrea Utzeri | Paola Varvarà | Gennara Cavallaro
Source: Molecules (review, 2021-05-21)
Field: Materials Science — Materials Chemistry

Functionalization of Metal and Carbon Nanoparticles with Potential in Cancer Theranostics Cancer theranostics is a new concept of medical approach that attempts to combine in a unique nanoplatform diagnosis, monitoring and therapy so as to provide eradication of a solid tumor in a non-invasive fashion. There are many available solutions to tackle cancer using theranostic agents such as photothermal therapy (PTT) and photodynamic therapy (PDT) under the guidance of imaging techniques (e.g., magnetic resonance-MRI, photoacoustic-PA or computed tomography-CT imaging). Additionally, there are several potential theranostic nanoplatforms able to combine diagnosis and therapy at once, such as gold nanoparticles (GNPs), graphene oxide (GO), superparamagnetic iron oxide nanoparticles (SPIONs) and carbon nanodots (CDs). Currently, surface functionalization of these nanoplatforms is an extremely useful protocol for effectively tuning their structures, interface features and physicochemical properties. This approach is much more reliable and amenable to fine adjustment, reaching both physicochemical and regulatory requirements as a function of the specific field of application. Here, we summarize and compare the most promising metal- and carbon-based theranostic tools reported as potential candidates in precision cancer theranostics. We focused our review on the latest developments in surface functionalization strategies for these nanosystems, or hybrid nanocomposites consisting of their combination, and discuss their main characteristics and potential applications in precision cancer medicine. Photothermal therapy ; Nanotechnology ; Surface modification ; Materials science ; Cancer therapy ; Nanodot ; Nanomedicine ; Photoacoustic imaging in biomedicine ; Photodynamic therapy ; Nanoparticle ; Cancer ; Medicine ; Chemistry Carbon and Quantum Dots Applications ; Graphene and Nanomaterials Applications ; Nanoplatforms for cancer theranostics
Authors: Alberto Sensini | Gabriele Massafra | Carlo Gotti | Andrea Zucchelli | Luca Cristofolini
Source: Frontiers in Bioengineering and Biotechnology (review, 2021-03-02)
Field: Materials Science — Biomaterials

Tissue Engineering for the Insertions of Tendons and Ligaments: An Overview of Electrospun Biomaterials and Structures The musculoskeletal system is composed by hard and soft tissue. These tissues are characterized by a wide range of mechanical properties that cause a progressive transition from one to the other. These material gradients are mandatory to reduce stress concentrations at the junction site. Nature has answered to this topic developing optimized interfaces, which enable a physiological transmission of load in a wide area over the junction. The interfaces connecting tendons and ligaments to bones are called entheses, while the ones between tendons and muscles are named myotendinous junctions. Several injuries can affect muscles, bones, tendons, or ligaments, and they often occur at the junction sites. For this reason, the main aim of the innovative field of the interfacial tissue engineering is to produce scaffolds with biomaterial gradients and mechanical properties to guide the cell growth and differentiation. Among the several strategies explored to mimic these tissues, the electrospinning technique is one of the most promising, allowing to generate polymeric nanofibers similar to the musculoskeletal extracellular matrix. Thanks to its extreme versatility, electrospinning has allowed the production of sophisticated scaffolds suitable for the regeneration of both the entheses and the myotendinous junctions. The aim of this review is to analyze the most relevant studies that applied electrospinning to produce scaffolds for the regeneration of the enthesis and the myotendinous junction, giving a comprehensive overview on the progress made in the field, in particular focusing on the electrospinning strategies to produce these scaffolds and their mechanical, <i>in vitro</i>, and <i>in vivo</i> outcomes. Enthesis ; Electrospinning ; Tissue engineering ; Materials science ; Biomedical engineering ; Biomaterial ; Fibrocartilage ; Extracellular matrix ; Mechanobiology ; Nanotechnology ; Tendon ; Anatomy ; Chemistry ; Composite material ; Polymer ; Articular cartilage ; Engineering ; Medicine Electrospun Nanofibers in Biomedical Applications ; Tendon Structure and Treatment ; Tissue Engineering and Regenerative Medicine
Authors: Sang‐Hyeok Yang | Wooseon Choi | Byeong Wook Cho | Frederick Agyapong-Fordjour | Sehwan Park | Seok Joon Yun | Hyung‐Jin Kim | Young‐Kyu Han | Young Hee Lee | Ki Kang Kim | Young‐Min Kim
Source: Advanced Science (article, 2021-06-03)
Field: Materials Science — Materials Chemistry

Deep Learning‐Assisted Quantification of Atomic Dopants and Defects in 2D Materials Abstract Atomic dopants and defects play a crucial role in creating new functionalities in 2D transition metal dichalcogenides (2D TMDs). Therefore, atomic‐scale identification and their quantification warrant precise engineering that widens their application to many fields, ranging from development of optoelectronic devices to magnetic semiconductors. Scanning transmission electron microscopy with a sub‐Å probe has provided a facile way to observe local dopants and defects in 2D TMDs. However, manual data analytics of experimental images is a time‐consuming task, and often requires subjective decisions to interpret observed signals. Therefore, an approach is required to automate the detection and classification of dopants and defects. In this study, based on a deep learning algorithm, fully convolutional neural network that shows a superior ability of image segmentation, an efficient and automated method for reliable quantification of dopants and defects in TMDs is proposed with single‐atom precision. The approach demonstrates that atomic dopants and defects are precisely mapped with a detection limit of ≈1 × 10 12 cm −2 , and with a measurement accuracy of ≈98% for most atomic sites. Furthermore, this methodology is applicable to large volume of image data to extract atomic site‐specific information, thus providing insights into the formation mechanisms of various defects under stimuli. Dopant ; Atomic units ; Materials science ; Convolutional neural network ; Computer science ; Nanotechnology ; Semiconductor ; Artificial intelligence ; Atom (system on chip) ; Doping ; Optoelectronics ; Physics ; Embedded system Machine Learning in Materials Science ; Gas Sensing Nanomaterials and Sensors ; Ga2O3 and related materials
Authors: Tongqi Wen | Rui Wang | Lingyu Zhu | Linfeng Zhang | Handong Wang | David J. Srolovitz | Zhaoxuan Wu
Source: npj Computational Materials (article, 2021-12-16)
Field: Materials Science — Materials Chemistry

Specialising neural network potentials for accurate properties and application to the mechanical response of titanium Abstract Large scale atomistic simulations provide direct access to important materials phenomena not easily accessible to experiments or quantum mechanics-based calculation approaches. Accurate and efficient interatomic potentials are the key enabler, but their development remains a challenge for complex materials and/or complex phenomena. Machine learning potentials, such as the Deep Potential (DP) approach, provide robust means to produce general purpose interatomic potentials. Here, we provide a methodology for specialising machine learning potentials for high fidelity simulations of complex phenomena, where general potentials do not suffice. As an example, we specialise a general purpose DP method to describe the mechanical response of two allotropes of titanium (in addition to other defect, thermodynamic and structural properties). The resulting DP correctly captures the structures, energies, elastic constants and γ -lines of Ti in both the HCP and BCC structures, as well as properties such as dislocation core structures, vacancy formation energies, phase transition temperatures, and thermal expansion. The DP thus enables direct atomistic modelling of plastic and fracture behaviour of Ti. The approach to specialising DP interatomic potential, DPspecX, for accurate reproduction of properties of interest “X”, is general and extensible to other systems and properties. Interatomic potential ; Materials science ; Statistical physics ; Titanium ; Dislocation ; Molecular dynamics ; Titanium alloy ; Embedded atom model ; Vacancy defect ; Computer science ; Nanotechnology ; Chemical physics ; Physics ; Condensed matter physics ; Computational chemistry ; Chemistry ; Alloy Machine Learning in Materials Science ; Nuclear Materials and Properties ; Titanium Alloys Microstructure and Properties
Authors: Jacob Madsen | Toma Susi
Source: Open Research Europe (article, 2021-05-21)
Field: Materials Science — Surfaces, Coatings and Films

The abTEM code: transmission electron microscopy from first principles Simulation of transmission electron microscopy (TEM) images or diffraction patterns is often required to interpret experimental data. Since nuclear cores dominate electron scattering, the scattering potential is typically described using the independent atom model, which completely neglects valence bonding and its effect on the transmitting electrons. As instrumentation has advanced, new measurements have revealed subtle details of the scattering potential that were previously not accessible to experiment. We have created an open-source simulation code designed to meet these demands by integrating the ability to calculate the potential via density functional theory (DFT) with a flexible modular software design. abTEM can simulate most standard imaging modes and incorporates the latest algorithmic developments. The development of new techniques requires a program that is accessible to domain experts without extensive programming experience. abTEM is written purely in Python and designed for easy modification and extension. The effective use of modern open-source libraries makes the performance of abTEM highly competitive with existing optimized codes on both CPUs and GPUs and allows us to leverage an extensive ecosystem of libraries, such as the Atomic Simulation Environment and the DFT code GPAW. abTEM is designed to work in an interactive Python notebook, creating a seamless and reproducible workflow from defining an atomic structure, calculating molecular dynamics (MD) and electrostatic potentials, to the analysis of results, all in a single, easy-to-read document. This article provides ongoing documentation of abTEM development. In this first version, we show use cases for hexagonal boron nitride, where valence bonding can be detected, a 4D-STEM simulation of molybdenum disulfide including ptychographic phase reconstruction, a comparison of MD and frozen phonon modeling for convergent-beam electron diffraction of a 2.6-million-atom silicon system, and a performance comparison of our fast implementation of the PRISM algorithm for a decahedral 20000-atom gold nanoparticle. Python (programming language) ; Computer science ; Computational science ; Source code ; Workflow ; Leverage (statistics) ; Software ; Scattering ; Valence (chemistry) ; Computer engineering ; Physics ; Programming language ; Artificial intelligence ; Optics Electron and X-Ray Spectroscopy Techniques ; Advanced Electron Microscopy Techniques and Applications ; Machine Learning in Materials Science
Authors: Parshant Kumar Sharma | A. Ruotolo | Raju Khan | Yogendra Kumar Mishra | Nagendra Kumar Kaushik | Nam‐Young Kim | Ajeet Kaushik
Source: Materials Letters (article, 2021-10-18)
Field: Materials Science — Materials Chemistry

Perspectives on 2D-borophene flatland for smart bio-sensing Borophene ; Biosensor ; Nanotechnology ; Materials science ; Substrate (aquarium) ; Smart material ; Surface modification ; Computer science ; Engineering ; Chemical engineering ; Monolayer MXene and MAX Phase Materials ; Advanced biosensing and bioanalysis techniques ; 2D Materials and Applications
Authors: Igor Levchenko | Shuyan Xu | Oleg Baranov | Olha Bazaka | Elena P. Ivanova | Kateryna Bazaka
Source: Molecules (review, 2021-07-05)
Field: Materials Science — Surfaces, Coatings and Films

Plasma and Polymers: Recent Progress and Trends Plasma-enhanced synthesis and modification of polymers is a field that continues to expand and become increasingly more sophisticated. The highly reactive processing environments afforded by the inherently dynamic nature of plasma media are often superior to ambient or thermal environments, offering substantial advantages over other processing methods. The fluxes of energy and matter toward the surface enable rapid and efficient processing, whereas the charged nature of plasma-generated particles provides a means for their control. The range of materials that can be treated by plasmas is incredibly broad, spanning pure polymers, polymer-metal, polymer-wood, polymer-nanocarbon composites, and others. In this review, we briefly outline some of the recent examples of the state-of-the-art in the plasma-based polymer treatment and functionalization techniques. Polymer ; Surface modification ; Plasma ; Plasma processing ; Nanotechnology ; Materials science ; Materials processing ; Chemical engineering ; Process engineering ; Composite material ; Physics ; Engineering Surface Modification and Superhydrophobicity ; Plasma Diagnostics and Applications ; Electrohydrodynamics and Fluid Dynamics
Authors: Songqing Zhang | Junliang Liu | Maxwell Merle Kirchner | Han Wang | Yongling Ren | Wen Lei
Source: Journal of Physics D Applied Physics (article, 2021-07-21)
Field: Materials Science — Materials Chemistry

Two-dimensional heterostructures and their device applications: progress, challenges and opportunities—review Abstract This work presents a review of the current progress, challenges, and potential future development opportunities for two-dimensional (2D) material-based heterostructures, including their fabrication techniques as well as their applications in various functional devices. The fabrication techniques for 2D material-based vertical heterostructures are first reviewed and discussed, including artificial stacking, chemical vapor deposition (CVD), molecular beam epitaxy, and others. Then, 2D material-based lateral heterostructure growth techniques are reviewed, including CVD and others. Subsequently, various functional device applications based on 2D material-based heterostructures are systematically reviewed and discussed, including electronic devices, optoelectronic devices, electrochemical devices, and others. The advantages and disadvantages for each fabrication/growth technique are compared and analyzed, including those for both vertical and lateral heterostructures. In addition, the current primary challenges for further development of 2D material-based heterostructures and their functional devices are discussed and analyzed, including lack of precise control, low interface/surface quality, surface passivation issue, low light absorption, lack of system integration and application, complex device fabrication process, as well as low device fabrication efficiency. Various potential solutions are proposed that have the potential to overcome these existing primary challenges to achieve better device performance and thus their ultimate industry applications for2D material-based heterostructures. Heterojunction ; Fabrication ; Materials science ; Passivation ; Nanotechnology ; Stacking ; Optoelectronics ; Computer science ; Chemistry ; Layer (electronics) 2D Materials and Applications ; Perovskite Materials and Applications ; MXene and MAX Phase Materials
Authors: Saptaparni Chanda | Dilpreet S. Bajwa
Source: REVIEWS ON ADVANCED MATERIALS SCIENCE (review, 2021-01-01)
Field: Materials Science — Biomaterials

A review of current physical techniques for dispersion of cellulose nanomaterials in polymer matrices Abstract Cellulose nanomaterials (CNMs) naturally exist in biomass. Recent developments in nanotechnology and extraction procedure of CNMs open up a new era in the polymer composites industry. Abundant, renewable, biodegradable, transparent, light weight, and most importantly, low cost make CNMs the ideal material for packaging, automotive, construction, and infrastructure applications. CNMs are generally used as materials for polymer matrix reinforcement in the composites industry. The industrial-scale manufacturing of CNM/thermoplastic composites remains an unsolved puzzle for both academics and industries. The dispersion of nanocellulose in polymer matrix is the central problem inhibiting the manufacturing of CNM/polymer composites at an industrial scale. Several attempts were made to disperse nanocellulose effectively in a polymer matrix and improve compatibility between the matrix and CNMs. Chemical-aided surface modification of CNMs has been effective in several cases; however, chemical toxicity, high price, and critical control of reactions make them unsuitable. This current review paper focuses on novel eco-friendly physical dispersion techniques of CNMs and their future scope of research. The physical dispersion techniques such as plasma-induced surface modification, ultrasonication, magnetic and electric field discharge, electrospinning, or drawing can visibly improve the dispersion state of CNMs. But several factors affect physical techniques’ performance, e.g. CNM type and forms, process conditions and parameters, etc. Moreover, the material-related factors interplay with the process-related factors. This review addresses the current state of knowledge on the physical dispersion techniques for CNMs and identifies challenges that are critical to adoption of these novel materials at commercial scale for future applications. Materials science ; Nanocellulose ; Nanomaterials ; Polymer ; Nanotechnology ; Dispersion (optics) ; Nanocomposite ; Electrospinning ; Polymer nanocomposite ; Composite material ; Process engineering ; Cellulose ; Chemical engineering ; Engineering Advanced Cellulose Research Studies ; Electrospun Nanofibers in Biomedical Applications ; Nanocomposite Films for Food Packaging
Authors: Alberto Álvarez‐Fernández | Cian Cummins | Matthias Saba | Ullrich Steiner | Guillaume Fleury | Virginie Ponsinet | Stefan Guldin
Source: Advanced Optical Materials (article, 2021-05-13)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Block Copolymer Directed Metamaterials and Metasurfaces for Novel Optical Devices Abstract Optical metamaterials are artificially engineered architectures that exhibit desired optical properties not found in nature. Bespoke design requires the ability to define shape, size, orientation, and composition of material structures on the nanometer length scale. Bottom‐up self‐assembly methods, such as block copolymer (BCP) templating, offer unique pathways to tailored features, at spatial resolution not routinely achieved by conventional top‐down techniques. In this review, the authors provide the general readership with basic concepts of the underlying fabrication processes and examine optical phenomena arising from BCP‐derived metamaterials and nanoresonators, with both dielectric and plasmonic characteristics. A number of diverse structural conformations designed by BCP templating and their implementation in optical devices is evaluated. The discussion includes 3D metamaterials, such as gyroidal and hyperbolic arrangements, as well as 2D metasurfaces. Based on recent developments in exploring these emerging structural and material configurations, the review further highlights unexplored opportunities offered by BCP self‐assembly for novel metamaterials and metasurface devices. Metamaterial ; Materials science ; Photonic metamaterial ; Nanotechnology ; Bespoke ; Fabrication ; Lithography ; Photonics ; Dielectric ; Plasmon ; Optoelectronics Metamaterials and Metasurfaces Applications ; Block Copolymer Self-Assembly ; Liquid Crystal Research Advancements
Authors: Teng Wang | Kefei Zhang | Jesse Van Griensven Thé | Hesheng Yu
Source: Computational Materials Science (article, 2021-09-27)
Field: Materials Science — Materials Chemistry

Accurate prediction of band gap of materials using stacking machine learning model Stacking ; Benchmark (surveying) ; Computer science ; Artificial intelligence ; Machine learning ; Band gap ; Materials science ; Algorithm ; Physics ; Optoelectronics Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Ga2O3 and related materials