jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Qiang Zhang | Yingnan Zhang | Yu Wan | Wildemar S.P. Carvalho | Liang Hu | Michael J. Serpe
Source: Progress in Polymer Science (article, 2021-03-10)
Field: Materials Science — Polymers and Plastics

Stimuli-Responsive Polymers for Sensing and Reacting to Environmental Conditions Polymer ; Polymer science ; Materials science ; Nanotechnology ; Chemical engineering ; Environmental science ; Engineering ; Composite material Conducting polymers and applications ; Advanced Sensor and Energy Harvesting Materials ; Polydiacetylene-based materials and applications
Authors: Julius Kühne | Juan Wang | Thomas Weber | Lucca Kühner | Stefan A. Maier | Andreas Tittl
Source: Nanophotonics (article, 2021-09-03)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Fabrication robustness in BIC metasurfaces Abstract All‐dielectric metasurfaces supporting photonic bound states in the continuum (BICs) are an exciting toolkit for achieving resonances with ultranarrow linewidths. However, the transition from theory to experimental realization can significantly reduce the optical performance of BIC‐based nanophotonic systems, severely limiting their application potential. Here, we introduce a combined numerical/experimental methodology for predicting how unavoidable tolerances in nanofabrication such as random geometrical variations affect the performance of different BIC metasurface designs. We compare several established all‐dielectric BIC unit cell geometries with broken in‐plane inversion symmetry including tilted ellipses, asymmetric double rods, and split rings. Significantly, even for low fabrication‐induced geometrical changes, both the BIC resonance amplitude and its quality factor (Q‐factor) are significantly reduced. We find that the all‐dielectric ellipses maintain the highest Q‐factors throughout the geometrical variation range, whereas the rod and split ring geometries fall off more quickly. The same behavior is confirmed experimentally, where geometrical variation values are derived from automated processing of sets of scanning electron microscopy (SEM) images. Our methodology provides crucial insights into the performance degradation of BIC metasurfaces when moving from simulations to fabricated samples and will enable the development of robust, high‐Q, and easy to manufacture nanophotonic platforms for applications ranging from biomolecular sensing to higher harmonic generation. Nanophotonics ; Robustness (evolution) ; Dielectric ; Photonics ; Optics ; Ellipse ; Materials science ; Fabrication ; Physics ; Optoelectronics ; Chemistry Metamaterials and Metasurfaces Applications ; Plasmonic and Surface Plasmon Research ; Microwave Engineering and Waveguides
Authors: Dedi Wang | Pratyush Tiwary
Source: The Journal of Chemical Physics (article, 2021-04-05)
Field: Materials Science — Materials Chemistry

State predictive information bottleneck The ability to make sense of the massive amounts of high-dimensional data generated from molecular dynamics simulations is heavily dependent on the knowledge of a low-dimensional manifold (parameterized by a reaction coordinate or RC) that typically distinguishes between relevant metastable states, and which captures the relevant slow dynamics of interest. Methods based on machine learning and artificial intelligence have been proposed over the years to deal with learning such low-dimensional manifolds, but they are often criticized for a disconnect from more traditional and physically interpretable approaches. To deal with such concerns, in this work we propose a deep learning based state predictive information bottleneck approach to learn the RC from high-dimensional molecular simulation trajectories. We demonstrate analytically and numerically how the RC learnt in this approach is connected to the committor in chemical physics and can be used to accurately identify transition states. A crucial hyperparameter in this approach is the time delay or how far into the future the algorithm should make predictions about. Through careful comparisons for benchmark systems, we demonstrate that this hyperparameter choice gives useful control over how coarse-grained we want the metastable state classification of the system to be. We thus believe that this work represents a step forward in systematic application of deep learning based ideas to molecular simulations. Bottleneck ; Hyperparameter ; Benchmark (surveying) ; Computer science ; Artificial intelligence ; Parameterized complexity ; Information bottleneck method ; Machine learning ; Metastability ; State (computer science) ; Algorithm ; Physics Machine Learning in Materials Science ; Protein Structure and Dynamics ; Spectroscopy and Quantum Chemical Studies
Authors: Fahad Albalawi | Mohd Zobir Hussein | Sharida Fakurazi | Mas Jaffri Masarudin
Source: International Journal of Nanomedicine (review, 2021-01-01)
Field: Materials Science — Materials Chemistry

Engineered Nanomaterials: The Challenges and Opportunities for Nanomedicines The emergence of nanotechnology as a key enabling technology over the past years has opened avenues for new and innovative applications in nanomedicine. From the business aspect, the nanomedicine market was estimated to worth USD 293.1 billion by 2022 with a perception of market growth to USD 350.8 billion in 2025. Despite these opportunities, the underlying challenges for the future of engineered nanomaterials (ENMs) in nanomedicine research became a significant obstacle in bringing ENMs into clinical stages. These challenges include the capability to design bias-free methods in evaluating ENMs' toxicity due to the lack of suitable detection and inconsistent characterization techniques. Therefore, in this literature review, the state-of-the-art of engineered nanomaterials in nanomedicine, their toxicology issues, the working framework in developing a toxicology benchmark and technical characterization techniques in determining the toxicity of ENMs from the reported literature are explored. Nanomedicine ; Nanotechnology ; Biochemical engineering ; Risk analysis (engineering) ; Engineering ; Business ; Materials science ; Nanoparticle Nanoparticles: synthesis and applications ; Graphene and Nanomaterials Applications ; Nanoparticle-Based Drug Delivery
Authors: Hefei Zhao | Yinglun Zhan | Zheng Xu | Joshua Nduwamungu | Yuzhen Zhou | Robert Powers | Changmou Xu
Source: Food Chemistry (article, 2021-10-26)
Field: Chemistry — Analytical Chemistry

The application of machine-learning and Raman spectroscopy for the rapid detection of edible oils type and adulteration Raman spectroscopy ; Principal component analysis ; Artificial intelligence ; Edible oil ; Pattern recognition (psychology) ; Spectroscopy ; Chemometrics ; Biological system ; Chromatography ; Chemistry ; Gas chromatography ; Machine learning ; Computer science ; Analytical Chemistry (journal) ; Food science ; Physics ; Biology ; Optics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Raji Atchudan | Thomas Nesakumar Jebakumar Immanuel Edison | Suguna Perumal | Rajangam Vinodh | Ashok K. Sundramoorthy | R. Suresh Babu | Yong Rok Lee
Source: Chemosensors (article, 2021-07-02)
Field: Materials Science — Materials Chemistry

Leftover Kiwi Fruit Peel-Derived Carbon Dots as a Highly Selective Fluorescent Sensor for Detection of Ferric Ion Recently, the use of natural products for the synthesis of carbon dots (CDs) has received much attention. Herein, leftover kiwi (Actinidia Deliciosa) fruit peels were successfully turned into beneficial fluorescent carbon dots (KN-CDs) via the hydrothermal-carbonization route. KN-CDs 1 and KN-CDs 2 were prepared without and with ammonium hydroxide, respectively. KN-CDs 1 and KN-CDs 2 were systematically characterized by various analytical techniques. Synthesized KN-CDs showed spherical-shaped morphology with narrow size distribution and excellent optical properties with excitation-independent behaviors. The quantum yields of KN-CDs 1 and KN-CDs 2 were calculated as 14 and 19%, respectively. Additionally, the KN-CDs possess excellent prolonging and photostability. Because of the excellent optical properties of KN-CDs, they were utilized as fluorescent sensors. The strong fluorescence of the KN-CDs was selectively quenched by Fe3+ ion, and quenching behavior showed a linear correlation with the concentrations of Fe3+ ion. KN-CDs 1 and KN-CDs 2 showed the detection of Fe3+ ions within the concentration range of 5–25 µM with the detection limit of 0.95 and 0.85 µM, respectively. Based on the turn-off sensing by the detection of Fe3+ ions, KN-CDs would be a promising candidate as a selective and sensitive fluorescent sensor. Fluorescence ; Chemistry ; Detection limit ; Carbonization ; Ion ; Carbon fibers ; Quantum yield ; Hydrothermal carbonization ; Quenching (fluorescence) ; Photochemistry ; Analytical Chemistry (journal) ; Nuclear chemistry ; Materials science ; Organic chemistry ; Chromatography Carbon and Quantum Dots Applications ; Nanocluster Synthesis and Applications ; Advanced Nanomaterials in Catalysis
Authors: Xiaoling Luo | Guanda Yang | Dirk W. Schubert
Source: Advanced Composites and Hybrid Materials (article, 2021-09-30)
Field: Materials Science — Polymers and Plastics

Electrically conductive polymer composite containing hybrid graphene nanoplatelets and carbon nanotubes: synergistic effect and tunable conductivity anisotropy Abstract Pristine carbon nanotubes (CNTs) and functionalized carbon nanotubes (f-CNTs) were introduced into conductive poly(methyl methacrylate)/graphene nanoplatelet (PMMA/GNP) composites to achieve a synergistic effect in the enhancement of the conductivity and the reduction in the percolation threshold by forming a 3-Dimensional(3-D) hybrid structure. Both the in-plane and perpendicular electrical properties were investigated. The synergies of hybrid fillers in the in-plane direction were more dependent on the total filler loading, while those in the perpendicular direction were significantly influenced by the GNP/CNT or GNP/f-CNT ratios. Typically, a schematic diagram of the evolution of the 3-D conductive pathways of PMMA/GNP/f-CNT composite at different GNP/f-CNT ratios was presented to explain this phenomenon. Moreover, tunable conductivity anisotropy (defined as the ratio of in-plane conductivity to perpendicular conductivity) ranging from 0.01 to 1000 was achieved, simply by constructing different conductive structures at various filler loadings or ratios in composites. Graphical abstract The synergistic effect of GNPs and f-CNTs varies with the microstructural conductive network evolution at different filler ratios. Materials science ; Carbon nanotube ; Percolation threshold ; Composite material ; Graphene ; Conductivity ; Composite number ; Electrical conductor ; Percolation (cognitive psychology) ; Anisotropy ; Perpendicular ; Electrical resistivity and conductivity ; Nanotechnology ; Geometry ; Chemistry Conducting polymers and applications ; Carbon Nanotubes in Composites ; Advanced Sensor and Energy Harvesting Materials
Authors: Clara Nyby | Xiaolei Guo | James E. Saal | Szu‐Chia Chien | Angela Y. Gerard | Huibin Ke | Tianshu Li | Pin Lu | Christian Oberdörfer | Sarita Sahu | Sirui Li | Christopher D. Taylor | Wolfgang Windl | John R. Scully | G. S. Frankel
Source: Scientific Data (article, 2021-02-11)
Field: Materials Science — Metals and Alloys

Electrochemical metrics for corrosion resistant alloys Corrosion is an electrochemical phenomenon. It can occur via different modes of attack, each having its own mechanisms, and therefore there are multiple metrics for evaluating corrosion resistance. In corrosion resistant alloys (CRAs), the rate of localized corrosion can exceed that of uniform corrosion by orders of magnitude. Therefore, instead of uniform corrosion rate, more complex electrochemical parameters are required to capture the salient features of corrosion phenomena. Here, we collect a database with an emphasis on metrics related to localized corrosion. The six sections of the database include data on various metal alloys with measurements of (1) pitting potential, E<sub>pit</sub>, (2) repassivation potential, E<sub>rp</sub>, (3) crevice corrosion potential, E<sub>crev</sub>, (4) pitting temperature, T<sub>pit</sub>, (5) crevice corrosion temperature, T<sub>crev</sub>, and (6) corrosion potential, E<sub>corr</sub>, corrosion current density, i<sub>corr</sub>, passivation current density, i<sub>pass</sub>, and corrosion rate. The experimental data were collected from 85 publications and include Al- and Fe-based alloys, high entropy alloys (HEAs), and a Ni-Cr-Mo ternary system. This dataset could be used in the design of highly corrosion resistant alloys. Corrosion ; Electrochemistry ; Metallurgy ; Materials science ; Chemistry ; Electrode Hydrogen embrittlement and corrosion behaviors in metals ; Machine Learning in Materials Science ; Corrosion Behavior and Inhibition
Authors: Yongkang Yao | Yutao Zhang | Chenxu Yan | Weihong Zhu | Zhiqian Guo
Source: Chemical Science (review, 2021-01-01)
Field: Chemistry — Spectroscopy

Enzyme-activatable fluorescent probes for β-galactosidase: from design to biological applications β-Galactosidase (β-gal), a typical hydrolytic enzyme, is a vital biomarker for cell senescence and primary ovarian cancers. Developing precise and rapid methods to monitor β-gal activity is crucial for early cancer diagnoses and biological research. Over the past decade, activatable optical probes have become a powerful tool for real-time tracking and <i>in vivo</i> visualization with high sensitivity and specificity. In this review, we summarize the latest advances in the design of β-gal-activatable probes <i>via</i> spectral characteristics and responsiveness regulation for biological applications, and particularly focus on the molecular design strategy from turn-on mode to ratiometric mode, from aggregation-caused quenching (ACQ) probes to aggregation-induced emission (AIE)-active probes, from near-infrared-I (NIR-I) imaging to NIR-II imaging, and from one-mode to dual-mode of chemo-fluoro-luminescence sensing β-gal activity. Fluorescence ; Dual mode ; Chemistry ; Nanotechnology ; Enzyme ; Luminescence ; Combinatorial chemistry ; Biophysics ; Materials science ; Biochemistry ; Optoelectronics ; Biology ; Optics ; Engineering Molecular Sensors and Ion Detection ; Luminescence and Fluorescent Materials ; Nanoplatforms for cancer theranostics
Authors: Samantha Lo | Mh Busra Fauzi
Source: Pharmaceutics (review, 2021-02-28)
Field: Materials Science — Biomaterials

Current Update of Collagen Nanomaterials—Fabrication, Characterisation and Its Applications: A Review Tissue engineering technology is a promising alternative approach for improvement in health management. Biomaterials play a major role, acting as a provisional bioscaffold for tissue repair and regeneration. Collagen a widely studied natural component largely present in the extracellular matrix (ECM) of the human body. It provides mechanical stability with suitable elasticity and strength to various tissues, including skin, bone, tendon, cornea and others. Even though exogenous collagen is commonly used in bioscaffolds, largely in the medical and pharmaceutical fields, nano collagen is a relatively new material involved in nanotechnology with a plethora of unexplored potential. Nano collagen is a form of collagen reduced to a nanoparticulate size, which has its advantages over the common three-dimensional (3D) collagen design, primarily due to its nano-size contributing to a higher surface area-to-volume ratio, aiding in withstanding large loads with minimal tension. It can be produced through different approaches including the electrospinning technique to produce nano collagen fibres resembling natural ECM. Nano collagen can be applied in various medical fields involving bioscaffold insertion or fillers for wound healing improvement; skin, bone, vascular grafting, nerve tissue and articular cartilage regeneration as well as aiding in drug delivery and incorporation for cosmetic purposes. Regeneration (biology) ; Extracellular matrix ; Tissue engineering ; Regenerative medicine ; Drug delivery ; Biomedical engineering ; Wound healing ; Nanotechnology ; Tendon ; Materials science ; Cartilage ; Chemistry ; Anatomy ; Surgery ; Medicine ; Cell biology ; Biology Electrospun Nanofibers in Biomedical Applications ; Collagen: Extraction and Characterization ; Silk-based biomaterials and applications
Authors: Sharanya Sankar | Kate O’Neill | Maurice Bagot d'Arc | Florian Rebeca | Marie Buffier | Elton Aleksi | Melanie Fan | Noriaki Matsuda | Eun Seok Gil | Lisa Spirio
Source: Frontiers in Bioengineering and Biotechnology (review, 2021-06-02)
Field: Materials Science — Biomaterials

Clinical Use of the Self-Assembling Peptide RADA16: A Review of Current and Future Trends in Biomedicine RADA16 is a synthetic peptide that exists as a viscous solution in an acidic formulation. In an acidic aqueous environment, the peptides spontaneously self-assemble into β-sheet nanofibers. Upon exposure and buffering of RADA16 solution to the physiological pH of biological fluids such as blood, interstitial fluid and lymph, the nanofibers begin physically crosslinking within seconds into a stable interwoven transparent hydrogel 3-D matrix. The RADA16 nanofiber hydrogel structure closely resembles the 3-dimensional architecture of native extracellular matrices. These properties make RADA16 formulations ideal topical hemostatic agents for controlling bleeding during surgery and to prevent post-operative rebleeding. A commercial RADA16 formulation is currently used for hemostasis in cardiovascular, gastrointestinal, and otorhinolaryngological surgical procedures, and studies are underway to investigate its use in wound healing and adhesion reduction. Straightforward application of viscous RADA16 into areas that are not easily accessible circumvents technical challenges in difficult-to-reach bleeding sites. The transparent hydrogel allows clear visualization of the surgical field and facilitates suture line assessment and revision. The shear-thinning and thixotropic properties of RADA16 allow its easy application through a narrow nozzle such as an endoscopic catheter. RADA16 hydrogels can fill tissue voids and do not swell so can be safely used in close proximity to pressure-sensitive tissues and in enclosed non-expandable regions. By definition, the synthetic peptide avoids potential microbiological contamination and immune responses that may occur with animal-, plant-, or mineral-derived topical hemostats. <i>In vitro</i> experiments, animal studies, and recent clinical experiences suggest that RADA16 nanofibrous hydrogels can act as surrogate extracellular matrices that support cellular behavior and interactions essential for wound healing and for tissue regenerative applications. In the future, the unique nature of RADA16 may also allow us to use it as a depot for precisely regulated drug and biopharmaceutical delivery. Self-healing hydrogels ; Nanofiber ; Thixotropy ; Nanotechnology ; Extracellular matrix ; Materials science ; Chemistry ; Polymer chemistry ; Composite material ; Biochemistry Supramolecular Self-Assembly in Materials ; Electrospun Nanofibers in Biomedical Applications ; Silk-based biomaterials and applications
Authors: Peter A. Gilhooly‐Finn | Ceyla Asker | Kening Wan | Emiliano Bilotti | Oliver Fenwick | Christian B. Nielsen
Source: Frontiers in Electronic Materials (article, 2021-07-20)
Field: Materials Science — Materials Chemistry

Thermoelectric Materials: Current Status and Future Challenges Examples of semiconducting polymers and dopants investigated for thermoelectric applications; (B) Frontier energy diagrams illustrating n-and p-type doping of an organic semiconductor (OSC) by charge transfer from a chemical dopant molecule. Current (fluid) ; Thermoelectric effect ; Thermoelectric materials ; Engineering physics ; Materials science ; Engineering ethics ; Engineering ; Physics ; Electrical engineering Advanced Thermoelectric Materials and Devices ; Perovskite Materials and Applications ; Chalcogenide Semiconductor Thin Films
Authors: Ivo Stachiv | Eduardo Alarcón | Miroslav Lamac
Source: Metals (article, 2021-03-03)
Field: Materials Science — Polymers and Plastics

Shape Memory Alloys and Polymers for MEMS/NEMS Applications: Review on Recent Findings and Challenges in Design, Preparation, and Characterization Rapid progress in material science and nanotechnology has led to the development of the shape memory alloys (SMA) and the shape memory polymers (SMP) based functional multilayered structures that, due to their capability to achieve the properties not feasible by most natural materials, have attracted a significant attention from the scientific community. These shape memory materials can sustain large deformations, which can be recovered once the appropriate value of an external stimulus is applied. Moreover, the SMAs and SMPs can be reprogrammed to meet several desired functional properties. As a result, SMAs and SMPs multilayered structures benefit from the unprecedented physical and material properties such as the shape memory effect, superelasticity, large displacement actuation, changeable mechanical properties, and the high energy density. They hold promises in the design of advanced functional micro- and nano-electro-mechanical systems (MEMS/NEMS). In this review, we discuss the recent understanding and progress in the fields of the SMAs and SMPs. Particular attention will be given to the existing challenges, critical issues, limitations, and achievements in the preparation and characterization of the SMPs and NiTi-based SMAs thin films, and their heterostructures for MEMS/NEMS applications including both experimental and computational approaches. Examples of the recent MEMS/NEMS devices utilizing the unique properties of SMAs and SMPs such as micropumps, microsensors or tunable metamaterial resonators are highlighted. In addition, we also introduce the prospective future research directions in the fields of SMAs and SMPs for the nanotechnology applications. Nanoelectromechanical systems ; Microelectromechanical systems ; Shape-memory alloy ; Materials science ; Pseudoelasticity ; Nanotechnology ; Characterization (materials science) ; Shape-memory polymer ; Actuator ; Mechanical engineering ; Computer science ; Engineering ; Nanoparticle ; Microstructure ; Artificial intelligence Polymer composites and self-healing ; Shape Memory Alloy Transformations ; Transition Metal Oxide Nanomaterials