jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Chunyan Lv | Wangwang Liu | Qing Luo | Haiyan Yi | Huakang Yu | Zhongmin Yang | Bo Zou | Yujian Zhang
Source: Chemical Science (article, 2020-01-01)
Field: Materials Science — Materials Chemistry

A highly emissive AIE-active luminophore exhibiting deep-red to near-infrared piezochromism and high-quality lasing Further development of high-efficiency and low-cost organic fluorescent materials is intrinsically hampered by the energy gap law and spin statistics, especially in the near-infrared (NIR) region. Here we design a novel building block with aggregation-induced emission (AIE) activity for realizing highly efficient luminophores covering the deep-red and NIR region, which originates from an increase in the orbital overlap and electron-withdrawing ability. An organic donor-acceptor molecule (<b>BPMT</b>) with the building block is prepared and can readily form J-type molecular columns with multiple C-H⋯N/O interactions. Notably, such synthesized materials can emit fluorescence centered at 701 nm with extremely high photoluminescence quantum yields (PLQYs) of 48.7%. Experimental and theoretical investigations reveal that the formation of the hybridized local and charge-transfer (HLCT) state and substantial C-H⋯N/O interactions contribute to a fast radiative decay rate and a slow nonradiative decay rate, respectively, resulting in high PLQYs in the solid state covering the NIR range. Remarkably, such <b>BPMT</b> crystals, as a first example, reveal strong-penetrability piezochromism along with a distinct PL change from the deep-red (<i>λ</i> <sub>max</sub> = 704 nm) to NIR (<i>λ</i> <sub>max</sub> = 821 nm) region. Moreover, such typical AIE-active luminophores are demonstrated to be a good candidate as a lasing medium. Together with epoxy resin by a self-assembly method, a microlaser is successfully illustrated with a lasing wavelength of 735.2 nm at a threshold of 22.3 kW cm<sup>-2</sup>. These results provide a promising approach to extend the contents of deep-red/NIR luminophores and open a new avenue to enable applications ranging from chemical sensing to lasing. Luminophore ; Lasing threshold ; Infrared ; Materials science ; Quality (philosophy) ; Optoelectronics ; Chemistry ; Optics ; Physics ; Luminescence Luminescence and Fluorescent Materials ; Photoreceptor and optogenetics research ; Random lasers and scattering media
Authors: Bernd Strehmel | Christian Schmitz | Ceren Kütahya | Yulian Pang | Anke Drewitz | Heinz Mustroph
Source: Beilstein Journal of Organic Chemistry (review, 2020-03-18)
Field: Materials Science — Materials Chemistry

Photophysics and photochemistry of NIR absorbers derived from cyanines: key to new technologies based on chemistry 4.0 Cyanines derived from heptamethines were mainly discussed regarding their functionalization to broaden the solubility in different surroundings exhibiting either hydrophilic or hydrophobic properties and to tailor made the Δ<i>G</i> <sub>et</sub> photopysical properties with respect to absorption and fluorescence. Electrochemical properties were additionally considered for some selected examples. The cyanines chosen comprised as end groups either indolenine, benzo[<i>e</i>]- or benzo[<i>cd</i>]indolium pattern, which facilitated to shift the absorption between 750-1000 nm. This enabled their use in applications with light sources emitting in the near-infrared (NIR) region selected from high power LEDs or lasers with line-shaped focus. The absorbers considered were discussed regarding their function as sensitizer for applications related to Chemistry 4.0 standards. These were mainly photopolymer coatings, which can be found for applications in the graphic industry or to protect selected substrates. The huge release of heat on demand upon turning ON or OFF the NIR light source enables them for photothermal treatment in processes requesting heat to initiate either chemical (activated reactions) or physical (melting, evaporation) events. Chemistry ; Photothermal therapy ; Absorption (acoustics) ; Fluorescence ; Photochemistry ; Nanotechnology ; Evaporation ; Near-infrared spectroscopy ; Optics ; Materials science Photochromic and Fluorescence Chemistry ; Nanoplatforms for cancer theranostics ; Luminescence and Fluorescent Materials
Authors: Thomas J. P. Hersbach | Marc T. M. Koper
Source: Current Opinion in Electrochemistry (article, 2020-11-16)
Field: Materials Science — Materials Chemistry

Cathodic corrosion: 21st century insights into a 19th century phenomenon Cathodic corrosion is an enigmatic electrochemical process that etches metallic electrodes at potentials below 0 V versus the normal hydrogen electrode. Although this phenomenon was discovered in the late 1800s by Fritz Haber, it remained mostly unnoticed during the 20th century and only attracted increased attention in the past decade. This recent attention has generated marked improvements in both the fundamental knowledge and the applications of cathodic corrosion. Fundamental new insights were gained into the effects and possible reaction intermediates of cathodic corrosion. Complementing these insights, recent advances involve applications of cathodic corrosion for nanoparticle synthesis and electrocatalyst modification. Both these applied and fundamental advances will be discussed in this short review on cathodic corrosion. Cathodic protection ; Corrosion ; Electrochemistry ; Materials science ; Electrode ; Electrocatalyst ; Metallurgy ; Nanotechnology ; Chemistry ; Physical chemistry Corrosion Behavior and Inhibition ; Electrocatalysts for Energy Conversion ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Juan Wang | Dekai Ye | Qing Meng | Chong‐an Di | Daoben Zhu
Source: Advanced Materials Technologies (article, 2020-05-27)
Field: Materials Science — Polymers and Plastics

Advances in Organic Transistor‐Based Biosensors Abstract Organic transistors are promising candidates for various biosensing applications owing to their flexibility, biocompatibility, and large‐scale processability. Until now, the construction of state‐of‐the‐art biosensors based on organic transistors, which relies on the fine‐tuned interaction between active layers and target analytes, is highly desired but remains challenging. Herein, the key strategies for constructing sensitive and selective biosensors based on organic transistors via device engineering are summarized. Recent achievements, including the molecular design of organic semiconductors, bio‐receptors assembly through the molecular immobilization, and strategies for overcoming the Debye screening effect, are discussed in a focused manner. Biosensor ; Nanotechnology ; Transistor ; Materials science ; Flexibility (engineering) ; Organic field-effect transistor ; Field-effect transistor ; Engineering ; Electrical engineering Conducting polymers and applications ; Analytical Chemistry and Sensors ; Advanced Memory and Neural Computing
Authors: Xiaotong Chu | Zhuoqun Lu | Baolei Tang | Bin Liu | Kaiqi Ye | Hongyu Zhang
Source: The Journal of Physical Chemistry Letters (article, 2020-06-16)
Field: Materials Science — Materials Chemistry

Engineering Mechanical Compliance of an Organic Compound toward Flexible Crystal Lasing Media Recently, organic crystals with mechanical flexibility have been emerging as a hot research topic due to their great potentials in flexible optoelectronics. However, organic crystals exhibiting elastic bending or plastic bending are relatively rare. In this study, we proposed a strategy to improve the probability of crystal flexibility as well as to regulate the mechanical properties by controlling polymorphism. Three different emissive organic polymorphs Cry-<b>G</b>, Cry-<b>Y</b>, and Cry-<b>O</b> with elastic, plastic, and brittle natures, respectively, were obtained by fine-tuning crystallization conditions of a diaryl β-diketone compound. Cry-<b>G</b> was found to transduce light and amplify the self-waveguided emission efficiently along the crystal body in the elastically bent state, demonstrating its multifunctional applications in flexible optical devices. This study is of great scientific significance not only to engineer mechanical compliance of organic crystals but also to highlight the utility of "crystal flexibility". Lasing threshold ; Materials science ; Flexibility (engineering) ; Crystal (programming language) ; Bending ; Crystallization ; Brittleness ; Bent molecular geometry ; Crystal engineering ; Optoelectronics ; Nanotechnology ; Composite material ; Crystal structure ; Crystallography ; Wavelength ; Chemistry ; Computer science ; Organic chemistry ; Supramolecular chemistry Luminescence and Fluorescent Materials ; Organic Electronics and Photovoltaics ; Perovskite Materials and Applications
Authors: Bingqing Lin | Xi Wu | Lin Xie | Yongqiang Kang | Hongda Du | Feiyu Kang | Jia Li | Lin Gan
Source: Angewandte Chemie International Edition (article, 2020-07-04)
Field: Materials Science — Materials Chemistry

Atomic Imaging of Subsurface Interstitial Hydrogen and Insights into Surface Reactivity of Palladium Hydrides Resolving interstitial hydrogen atoms at the surfaces and interfaces is crucial for understanding the mechanical and physicochemical properties of metal hydrides. Although palladium (Pd) hydrides hold important applications in hydrogen storage and electrocatalysis, the atomic position of interstitial hydrogen at Pd hydride near surfaces still remains undetermined. We report the first direct imaging of subsurface hydrogen atoms absorbed in Pd nanoparticles by using differentiated and integrated differential phase contrast within an aberration-corrected scanning transmission electron microscope. In contrast to the well-established octahedral interstitial sites for hydrogen in the bulk, subsurface hydrogen atoms are directly identified to occupy the tetrahedral interstices. DFT calculations show that the amount and the occupation type of subsurface hydrogen atoms play an indispensable role in fine-tuning the electronic structure and associated chemical reactivity of the Pd surface. Palladium ; Reactivity (psychology) ; Hydrogen ; Materials science ; Chemistry ; Catalysis ; Medicine ; Organic chemistry ; Pathology Nuclear Materials and Properties ; Hydrogen Storage and Materials ; Advanced Chemical Physics Studies
Authors: Héctor Torres-Pierna | Daniel Ruiz‐Molina | Claudio Roscini
Source: Materials Horizons (article, 2020-01-01)
Field: Materials Science — Materials Chemistry

Highly transparent photochromic films with a tunable and fast solution-like response Transparent, tunable and fast-response polymeric photochromic films are obtained through the entrapment of nanodroplets made of oil solutions of photochromic dyes. Photochromism ; Materials science ; Chemical engineering ; Photochemistry ; Optoelectronics ; Nanotechnology ; Chemistry Photochromic and Fluorescence Chemistry ; Polydiacetylene-based materials and applications ; Olfactory and Sensory Function Studies
Authors: Ghada G. Abdo | Moustafa M. Zagho | Ashraf Khalil
Source: Emergent Materials (article, 2020-06-01)
Field: Materials Science — Biomaterials

Recent advances in stimuli-responsive drug release and targeting concepts using mesoporous silica nanoparticles Abstract Being a developed and promising approach, nanotechnology has attracted a lot of attention in biomedical and pharmaceutical therapy applications. Among nanostructured materials, mesoporous silica nanoparticles (MSNs) are effectively used as nanocarriers for drug delivery systems. MSNs can be tailored-designed by different synthetic techniques. Their morphological characteristics dictate the type of application of such materials. Recently, polymer-based materials have been employed to functionalize the MSNs surface. These modified nanocarriers are loaded with the drug and can unload their “cargo” upon exposure to either endogenous or exogenous types of stimuli. In this study, different targeting concepts, including passive, active, vascular, nuclear, and multistage targeting, are discussed. Nanocarriers ; Mesoporous silica ; Nanotechnology ; Drug delivery ; Nanoparticle ; Materials science ; Targeted drug delivery ; Mesoporous material ; Chemistry Nanoparticle-Based Drug Delivery ; Mesoporous Materials and Catalysis ; Dendrimers and Hyperbranched Polymers
Authors: Hongli Yin | Mengjie Zheng | Huan Chen | Siyao Wang | Qingqing Zhou | Qiang Zhang | Ping Wang
Source: Journal of the American Chemical Society (article, 2020-07-27)
Field: Chemistry — Organic Chemistry

Stereoselective and Divergent Construction of β-Thiolated/Selenolated Amino Acids via Photoredox-Catalyzed Asymmetric Giese Reaction Sulfur and selenium occupy a distinguished position in biology owing to their redox activities, high nucleophilicity, and acyl transfer capabilities. Thiolated/selenolated amino acids, including cysteine, selenocysteine, and their derivatives, play critical roles in regulating the conformation and function of proteins and serve as an important motif for peptide design and bioconjugation. Unfortunately, a general and concise method to attain enantiopure β-thiolated/selenolated amino acids remains an unsolved problem. Herein, we present a photoredox-catalyzed asymmetric method for the preparation of enantiopure β-thiolated/selenolated amino acids using a simple chiral auxiliary, which controls the diastereoselectivity of the key alkylation step and acts as an orthogonal protecting group in the subsequent peptide synthesis. Our protocol can be used to prepare a wide range of β-thiolated/selenolated amino acids on a gram scale, which would otherwise be difficult to obtain using conventional methods. The effect of our chemistry was further highlighted and validated through the preparation of a series of peptidyl thiol/selenol analogues, including cytochrome <i>c</i> oxidase subunit protein 7C and oxytocin. Chemistry ; Enantiopure drug ; Amino acid ; Combinatorial chemistry ; Peptide ; Photoredox catalysis ; Peptide synthesis ; Nucleophile ; Cysteine ; Alkylation ; Bioconjugation ; Stereochemistry ; Enantioselective synthesis ; Organic chemistry ; Catalysis ; Biochemistry ; Enzyme Sulfur-Based Synthesis Techniques ; Chemical Synthesis and Analysis ; Synthesis and Catalytic Reactions
Authors: Juvissan Aguedo | Lenka Lorencová | Marek Baráth | Pavol Farkaš | Jan Tkáč
Source: Chemosensors (article, 2020-12-07)
Field: Materials Science — Materials Chemistry

Electrochemical Impedance Spectroscopy on 2D Nanomaterial MXene Modified Interfaces: Application as a Characterization and Transducing Tool This review presents the basic characteristics of MXene, a novel 2D nanomaterial with many outstanding properties applicable to electrochemical sensing and biosensing. The second part deals with electrochemical impedance spectroscopy (EIS) and its beneficial features applicable to ultrasensitive electrochemical sensing and label-free biosensing. The main part of the review presents recent advances in the integration of MXene to design electrochemical interfaces. EIS was used to evaluate the effect of anodic potential on MXene and the effect of the MXene preparation route and for characterization of MXene grafted with polymers. It also included the application of EIS as the main transducing tool for antibody- and aptamer-based biosensors or biosensors integrating molecularly imprinted polymers. Biosensor ; Dielectric spectroscopy ; Nanomaterials ; Nanotechnology ; Characterization (materials science) ; Aptamer ; Materials science ; Electrochemistry ; Electrode ; Chemistry MXene and MAX Phase Materials ; Advanced biosensing and bioanalysis techniques ; Advanced Memory and Neural Computing
Authors: Marios Sophocleous | L. Contat‐Rodrigo | Eduardo García‐Breijo | Julius Georgiou
Source: IEEE Sensors Journal (review, 2020-10-23)
Field: Materials Science — Polymers and Plastics

Organic Electrochemical Transistors as an Emerging Platform for Bio-Sensing Applications: A Review Organic electrochemical transistors (OECTs) have been recognized as a major emerging technology in the area of flexible electronics in the last decade. Although they have yet to be incorporated in common electronic fabrication technologies, they have considerably advanced as an emerging platform for biosensing applications. The paper provides a comprehensive and critical review of the most important advances in the field of OECT-based biosensors. A brief description of the device physics is given with the most important equations and a comparison has been made with the conventional MOSFET devices and characteristic equations. The use of OECTs as an emerging biosensing platform has been explored and their application as biomolecule, enzyme, bacteria, viruses, cells, nucleotide detectors as well as electrophysiological and wearable sensors has been reported. Furthermore, trends have been extracted and described in the paper in terms of fabrication technologies, electrode materials and most importantly, the semiconducting polymer. Additionally, future perspectives on the development and fabrication technologies of these devices have been further explored. Biosensor ; Nanotechnology ; Fabrication ; Electronics ; Transistor ; Wearable computer ; Wearable technology ; Bioelectronics ; Materials science ; Computer science ; Engineering ; Electrical engineering ; Voltage ; Embedded system Conducting polymers and applications ; Analytical Chemistry and Sensors ; Electrochemical sensors and biosensors
Authors: Higor Y. D. Sigaki | E. K. Lenzi | Rafael S. Zola | Matjaž Perc | Haroldo V. Ribeiro
Source: Scientific Reports (article, 2020-05-06)
Field: Materials Science — Materials Chemistry

Learning physical properties of liquid crystals with deep convolutional neural networks Machine learning algorithms have been available since the 1990s, but it is much more recently that they have come into use also in the physical sciences. While these algorithms have already proven to be useful in uncovering new properties of materials and in simplifying experimental protocols, their usage in liquid crystals research is still limited. This is surprising because optical imaging techniques are often applied in this line of research, and it is precisely with images that machine learning algorithms have achieved major breakthroughs in recent years. Here we use convolutional neural networks to probe several properties of liquid crystals directly from their optical images and without using manual feature engineering. By optimizing simple architectures, we find that convolutional neural networks can predict physical properties of liquid crystals with exceptional accuracy. We show that these deep neural networks identify liquid crystal phases and predict the order parameter of simulated nematic liquid crystals almost perfectly. We also show that convolutional neural networks identify the pitch length of simulated samples of cholesteric liquid crystals and the sample temperature of an experimental liquid crystal with very high precision. Convolutional neural network ; Liquid crystal ; Artificial neural network ; Computer science ; Deep learning ; Artificial intelligence ; Feature (linguistics) ; Crystal (programming language) ; Sample (material) ; Simple (philosophy) ; Materials science ; Algorithm ; Machine learning ; Physics ; Optoelectronics Machine Learning in Materials Science ; Optical Polarization and Ellipsometry ; Complex Systems and Time Series Analysis
Authors: Linlin Zhou | Huange Fu | Ting Lv | Chengbo Wang | Hui Gao | Daqian Li | Leimin Deng | Wei Xiong
Source: Nanomaterials (review, 2020-11-16)
Field: Materials Science — Materials Chemistry

Nonlinear Optical Characterization of 2D Materials Characterizing the physical and chemical properties of two-dimensional (2D) materials is of great significance for performance analysis and functional device applications. As a powerful characterization method, nonlinear optics (NLO) spectroscopy has been widely used in the characterization of 2D materials. Here, we summarize the research progress of NLO in 2D materials characterization. First, we introduce the principles of NLO and common detection methods. Second, we introduce the recent research progress on the NLO characterization of several important properties of 2D materials, including the number of layers, crystal orientation, crystal phase, defects, chemical specificity, strain, chemical dynamics, and ultrafast dynamics of excitons and phonons, aiming to provide a comprehensive review on laser-based characterization for exploring 2D material properties. Finally, the future development trends, challenges of advanced equipment construction, and issues of signal modulation are discussed. In particular, we also discuss the machine learning and stimulated Raman scattering (SRS) technologies which are expected to provide promising opportunities for 2D material characterization. Characterization (materials science) ; Ultrashort pulse ; Materials science ; Raman spectroscopy ; Nanotechnology ; Nonlinear optics ; Phonon ; Raman scattering ; Nonlinear system ; Laser ; Computer science ; Optoelectronics ; Optics ; Physics 2D Materials and Applications ; Graphene research and applications ; Nanowire Synthesis and Applications
Authors: Michael G. Taylor | Tzuhsiung Yang | Sean Lin | Aditya Nandy | Jon Paul Janet | Chenru Duan | Heather J. Kulik
Source: The Journal of Physical Chemistry A (article, 2020-03-28)
Field: Materials Science — Materials Chemistry

Seeing Is Believing: Experimental Spin States from Machine Learning Model Structure Predictions Determination of ground-state spins of open-shell transition-metal complexes is critical to understanding catalytic and materials properties but also challenging with approximate electronic structure methods. As an alternative approach, we demonstrate how structure alone can be used to guide assignment of ground-state spin from experimentally determined crystal structures of transition-metal complexes. We first identify the limits of distance-based heuristics from distributions of metal-ligand bond lengths of over 2000 unique mononuclear Fe(II)/Fe(III) transition-metal complexes. To overcome these limits, we employ artificial neural networks (ANNs) to predict spin-state-dependent metal-ligand bond lengths and classify experimental ground-state spins based on agreement of experimental structures with the ANN predictions. Although the ANN is trained on hybrid density functional theory data, we exploit the method-insensitivity of geometric properties to enable assignment of ground states for the majority (ca. 80-90%) of structures. We demonstrate the utility of the ANN by data-mining the literature for spin-crossover (SCO) complexes, which have experimentally observed temperature-dependent geometric structure changes, by correctly assigning almost all (>95%) spin states in the 46 Fe(II) SCO complex set. This approach represents a promising complement to more conventional energy-based spin-state assignment from electronic structure theory at the low cost of a machine learning model. Spins ; Ground state ; Heuristics ; Electronic structure ; Density functional theory ; Crystal structure prediction ; Artificial neural network ; Spin states ; Spin (aerodynamics) ; Bond length ; Chemistry ; Statistical physics ; Machine learning ; Artificial intelligence ; Materials science ; Computer science ; Physics ; Computational chemistry ; Condensed matter physics ; Atomic physics ; Thermodynamics ; Crystallography ; Crystal structure Machine Learning in Materials Science ; Electrocatalysts for Energy Conversion ; Protein Structure and Dynamics