jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Jianan Dai | Xin Zhang
Source: Chemical & Biomedical Imaging (review, 2023-10-26)
Field: Materials Science — Materials Chemistry

Chemical Regulation of Fluorescence Lifetime Fluorescence lifetime has significant applications in the field of fluorescence microscopy. Effective modulation of fluorescence lifetime can be achieved by controlling the radiative versus nonradiative processes of fluorophores. In this review, we systematically analyze and summarize chemical approaches that achieve fluorescence lifetime modulation for three different types of fluorophores, including small molecules, quantum dots, and metal complexes. In particular, this review is focused on the chemical mechanisms underlying fluorescence lifetime, the structure-function relationship that defines how chemical regulation is achieved, and the chemical principles that can be used to modulate different scaffolds of fluorophores. We aim to provide important resources for gaining a deeper understanding of fluorescence lifetime modulation, through in-depth investigation into the modulation mechanisms of various fluorescence systems. Perspectives are also proposed to enable future investigation on fluorescence lifetime modulation, a field that bears promises to drive the advancement and application of fluorescence imaging technology. Fluorescence ; Fluorescence in the life sciences ; Modulation (music) ; Nanotechnology ; Fluorescence microscope ; Fluorescence-lifetime imaging microscopy ; Quantum dot ; Materials science ; Chemistry ; Resonance fluorescence ; Physics ; Optics Luminescence and Fluorescent Materials ; Nanoplatforms for cancer theranostics ; Molecular Sensors and Ion Detection
Authors: Marzena Pander | Rodrigo Gil-San-Millán | Pedro Delgado | Cristina Perona | Urszula Kostrzewa | Karol Kaczkowski | Dominik J. Kubicki | Jorge A. R. Navarro | Wojciech Bury
Source: Materials Horizons (article, 2023-01-01)
Field: Chemistry — Inorganic Chemistry

MOF/polymer hybrids through <i>in situ</i> free radical polymerization in metal-organic frameworks We use the free radical polymerization initiator 4,4'-azobis(cyanovaleric acid) coordinated to the open metal sites of metal-organic frameworks (MOFs) to give rise to highly uniform MOF/polymer hybrids. We demonstrate this strategy on two robust zirconium MOFs (NU-1000 and MOF-808), which are the most effective catalysts for degradation of chemical warfare nerve agents. The resulting hybrid materials maintain their hydrolytic catalytic activity and have substantially improved adhesion to polypropylene and activated carbon textile fibers, yielding highly robust MOF/polymer/textile hybrid systems. These composites are suitable for the green production of active protective clothing and filters capable of detoxifying organophosphorus warfare agents. In situ ; Metal-organic framework ; Materials science ; Polymer ; Radical polymerization ; Polymerization ; Metal ; Polymer chemistry ; Chemical engineering ; Nanotechnology ; Chemistry ; Organic chemistry ; Composite material ; Metallurgy Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications ; Advanced Nanomaterials in Catalysis
Authors: Molly E. McFadden | Ross W. Barber | Anna C. Overholts | Maxwell J. Robb
Source: Chemical Science (review, 2023-01-01)
Field: Materials Science — Materials Chemistry

Naphthopyran molecular switches and their emergent mechanochemical reactivity Naphthopyran molecular switches undergo a ring-opening reaction upon external stimulation to generate intensely colored merocyanine dyes. Their unique modularity and synthetic accessibility afford exceptional control over their properties and stimuli-responsive behavior. Commercial applications of naphthopyrans as photoswitches in photochromic ophthalmic lenses have spurred an extensive body of work exploring naphthopyran-merocyanine structure-property relationships. The recently discovered mechanochromic behavior of naphthopyrans has led to their emergent application in the field of polymer mechanochemistry, enabling advances in the design of force-responsive materials as well as fundamental insights into mechanochemical reactivity. The structure-property relationships established in the photochemical literature serve as a convenient blueprint for the design of naphthopyran molecular force probes with precisely tuned properties. On the other hand, the mechanochemical reactivity of naphthopyran diverges in many cases from the conventional photochemical pathways, resulting in unexpected properties and opportunities for deeper understanding and innovation in polymer mechanochemistry. Here, we highlight the features of the naphthopyran scaffold that render it a powerful platform for the design of mechanochromic materials and review recent advances in naphthopyran mechanochemistry. Merocyanine ; Molecular switch ; Reactivity (psychology) ; Chemistry ; Ring (chemistry) ; Photochromism ; Nanotechnology ; Photochemistry ; Materials science ; Combinatorial chemistry ; Molecule ; Organic chemistry Luminescence and Fluorescent Materials ; Photochromic and Fluorescence Chemistry ; Polydiacetylene-based materials and applications
Authors: Radhakrishnan Sreena | A. Joseph Nathanael
Source: Materials (review, 2023-03-15)
Field: Materials Science — Biomaterials

Biodegradable Biopolymeric Nanoparticles for Biomedical Applications-Challenges and Future Outlook Biopolymers are polymers obtained from either renewable or non-renewable sources and are the most suitable candidate for tailor-made nanoparticles owing to their biocompatibility, biodegradability, low toxicity and immunogenicity. Biopolymeric nanoparticles (BPn) can be classified as natural (polysaccharide and protein based) and synthetic on the basis of their origin. They have been gaining wide interest in biomedical applications such as tissue engineering, drug delivery, imaging and cancer therapy. BPn can be synthesized by various fabrication strategies such as emulsification, ionic gelation, nanoprecipitation, electrospray drying and so on. The main aim of the review is to understand the use of nanoparticles obtained from biodegradable biopolymers for various biomedical applications. There are very few reviews highlighting biopolymeric nanoparticles employed for medical applications; this review is an attempt to explore the possibilities of using these materials for various biomedical applications. This review highlights protein based (albumin, gelatin, collagen, silk fibroin); polysaccharide based (chitosan, starch, alginate, dextran) and synthetic (Poly lactic acid, Poly vinyl alcohol, Poly caprolactone) BPn that has recently been used in many applications. The fabrication strategies of different BPn are also being highlighted. The future perspective and the challenges faced in employing biopolymeric nanoparticles are also reviewed. Biocompatibility ; Nanotechnology ; Materials science ; Nanoparticle ; Vinyl alcohol ; Gelatin ; Biofabrication ; Chitosan ; Fibroin ; Drug delivery ; Tissue engineering ; Polymer ; Chemistry ; Biomedical engineering ; SILK ; Organic chemistry ; Medicine biodegradable polymer synthesis and properties ; Collagen: Extraction and Characterization ; Electrospun Nanofibers in Biomedical Applications
Authors: Bo Zhang | Yanli Sun | Hong Xu | Xiangming He
Source: Carbon Neutralization (article, 2023-10-03)
Field: Chemistry — Inorganic Chemistry

Hydrogen storage mechanism of metal–organic framework materials based on metal centers and organic ligands Abstract The effective storage and utilization of hydrogen energy is expected to solve the problems of energy shortage and environmental pollution currently faced by human society. Metal–organic framework materials (MOFs) have been shown by scientists to be very potential hydrogen storage materials. However, the current design methods and strategies for MOFs are still generally in the trial‐and‐error stage, and the research works are at the overall level. To solve the problems of directional design and rational construction of new MOFs, this work uses the principles and methods of coordination chemistry and crystal engineering to carry out the theoretical design and mechanism research of new MOFs for high‐efficiency hydrogen storage application scenarios. In this study, the structures selected for theoretical calculation were divided into two types: different ligands for the same metal (IRMOFs, MOF‐205, and DUT‐23‐Zn) and different metals for the same ligand (DUT‐23‐M [(M = Co, Ni, Cu, and Zn]). The model construction process, hydrogen loading with temperature, specific surface area, hydrogen adsorption energy, charge density and hydrogen storage mechanism of the above structures were analyzed, and the key indicators that may affect the hydrogen storage performance of MOFs were summarized: type and quantity of coordination metals, temperature, pressure, adsorption site and specific surface area. Hydrogen storage ; Metal-organic framework ; Hydrogen ; Adsorption ; Energy storage ; Environmental pollution ; Materials science ; Economic shortage ; Metal ; Process engineering ; Nanotechnology ; Environmental science ; Chemistry ; Metallurgy ; Engineering ; Organic chemistry ; Thermodynamics Metal-Organic Frameworks: Synthesis and Applications ; Hydrogen Storage and Materials ; Carbon dioxide utilization in catalysis
Authors: Mirosław Kwaśny | Aneta Bombalska
Source: Sensors (review, 2023-03-05)
Field: Chemistry — Spectroscopy

Optical Methods of Methane Detection Methane is the most frequently analyzed gas with different concentrations ranging from single ppm or ppb to 100%. There are a wide range of applications for gas sensors including urban uses, industrial uses, rural measurements, and environment monitoring. The most important applications include the measurement of anthropogenic greenhouse gases in the atmosphere and methane leak detection. In this review, we discuss common optical methods used for detecting methane such as non-dispersive infrared (NIR) technology, direct tunable diode spectroscopy (TDLS), cavity ring-down spectroscopy (CRDS), cavity-enhanced absorption spectroscopy (CEAS), lidar techniques, and laser photoacoustic spectroscopy. We also present our own designs of laser methane analyzers for various applications (DIAL, TDLS, NIR). Methane ; Photoacoustic spectroscopy ; Tunable diode laser absorption spectroscopy ; Spectroscopy ; Materials science ; Cavity ring-down spectroscopy ; Environmental science ; Laser ; Greenhouse gas ; Lidar ; Optoelectronics ; Tunable laser ; Analytical Chemistry (journal) ; Remote sensing ; Optics ; Chemistry ; Environmental chemistry ; Physics ; Geology Spectroscopy and Laser Applications ; Atmospheric and Environmental Gas Dynamics ; Atmospheric Ozone and Climate
Authors: Song Wang | Jun Jiang
Source: ACS Catalysis (article, 2023-05-18)
Field: Materials Science — Materials Chemistry

Interpretable Catalysis Models Using Machine Learning with Spectroscopic Descriptors The complexity and dynamics of catalytic systems make it challenging to study the catalysts and catalytic reactions. Fortunately, the advance of machine learning (ML) has made descriptor-based catalyst screening and rational design a mainstream research approach. Herein, the spectroscopic descriptors reported in recent years are highlighted in the field of catalysis. Both vibrational spectra and X-ray absorption spectra have demonstrated strong ability to predict catalytic structures and properties. Through several cases, the interpretable ML models based on spectroscopic descriptors are discussed to reveal physical knowledge and catalytic mechanism and to exhibit superiority in transfer learning tasks and imperfect data scenarios. Finally, in this Viewpoint, we illustrate the challenges in the research field of interpretable ML models with spectroscopic descriptors and provide perspectives. Catalysis ; Field (mathematics) ; Imperfect ; Chemistry ; Molecular descriptor ; Computer science ; Mechanism (biology) ; Machine learning ; Rational design ; Artificial intelligence ; Biochemical engineering ; Computational chemistry ; Biological system ; Quantitative structure–activity relationship ; Nanotechnology ; Materials science ; Physics ; Organic chemistry ; Mathematics ; Engineering ; Quantum mechanics Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Metabolomics and Mass Spectrometry Studies
Authors: Andrew J. Lew | Kai Jin | Markus J. Buehler
Source: npj Computational Materials (article, 2023-05-26)
Field: Materials Science — Materials Chemistry

Designing architected materials for mechanical compression via simulation, deep learning, and experimentation Abstract Architected materials can achieve enhanced properties compared to their plain counterparts. Specific architecting serves as a powerful design lever to achieve targeted behavior without changing the base material. Thus, the connection between architected structure and resultant properties remains an open field of great interest to many fields, from aerospace to civil to automotive applications. Here, we focus on properties related to mechanical compression, and design hierarchical honeycomb structures to meet specific values of stiffness and compressive stress. To do so, we employ a combination of techniques in a singular workflow, starting with molecular dynamics simulation of the forward design problem, augmenting with data-driven artificial intelligence models to address the inverse design problem, and verifying the behavior of de novo structures with experimentation of additively manufactured samples. We thereby demonstrate an approach for architected design that is generalizable to multiple material properties and agnostic to the identity of the base material. Workflow ; Computer science ; Aerospace ; Compression (physics) ; Stiffness ; Focus (optics) ; Mechanical engineering ; Engineering ; Materials science ; Structural engineering ; Aerospace engineering Machine Learning in Materials Science ; Cellular and Composite Structures ; Block Copolymer Self-Assembly
Authors: Alexey S. Galushko | Daniil A. Boiko | Evgeniy O. Pentsak | Dmitry B. Eremin | Valentine P. Ananikov
Source: Journal of the American Chemical Society (article, 2023-04-13)
Field: Materials Science — Materials Chemistry

Time-Resolved Formation and Operation Maps of Pd Catalysts Suggest a Key Role of Single Atom Centers in Cross-Coupling An approach to the spatially localized characterization of supported catalysts over a reaction course is proposed. It consists of a combination of scanning, transmission, and high-resolution scanning transmission electron microscopy to determine metal particles from arrays of surface nanoparticles to individual nanoparticles and individual atoms. The study of the evolution of specific metal catalyst particles at different scale levels over time, particularly before and after the cross-coupling catalytic reaction, made it possible to approach the concept of 4D catalysis-tracking the positions of catalytic centers in space (3D) over time (+1D). The dynamic behavior of individual palladium atoms and nanoparticles in cross-coupling reactions was recorded with nanometer accuracy via the precise localization of catalytic centers. Single atoms of palladium leach out into solution from the support under the action of the catalytic system, where they exhibit extremely high catalytic activity compared to surface metal nanoparticles. Monoatomic centers, which make up only approximately 1% of palladium in the Pd/C system, provide more than 99% of the catalytic activity. The remaining palladium nanoparticles changed their shape and could move over the surface of the support, which was recorded by processing images of the array of nanoparticles with a neural network and aligning them using automatically detected keypoints. The study reveals a novel opportunity for single-atom catalysis─easier detachment (capture) from (on) the carbon support surface is the origin of superior catalytic activity, rather than the operation of single atomic catalytic centers on the surface of the support, as is typically assumed. Catalysis ; Palladium ; Nanoparticle ; Chemistry ; Scanning transmission electron microscopy ; Metal ; Atom (system on chip) ; Chemical physics ; Coupling (piping) ; Atomic units ; Transmission electron microscopy ; Nanotechnology ; Chemical engineering ; Materials science ; Composite material ; Organic chemistry ; Physics Catalytic Processes in Materials Science ; Nanocluster Synthesis and Applications ; Machine Learning in Materials Science
Authors: Lei Song | Donglei Wang | Xuwang Liu | Aijun Yin | Zhendong Long
Source: Sensors and Actuators A Physical (article, 2023-05-16)
Field: Materials Science — Materials Chemistry

Prediction of mechanical properties of composite materials using multimodal fusion learning Fusion ; Microstructure ; Convolutional neural network ; Multilayer perceptron ; Modal ; Feature (linguistics) ; Material properties ; Materials science ; Component (thermodynamics) ; Computer science ; Artificial neural network ; Composite number ; Pattern recognition (psychology) ; Artificial intelligence ; Algorithm ; Composite material Machine Learning in Materials Science ; Industrial Vision Systems and Defect Detection ; Infrastructure Maintenance and Monitoring
Authors: Haosong Zhang | Mingdu Luo | Hongmiao Wang | Fandong Ren | Yandong Yin | Zheng‐Jiang Zhu
Source: Analytical Chemistry (article, 2023-09-04)
Field: Chemistry — Spectroscopy

AllCCS2: Curation of Ion Mobility Collision Cross-Section Atlas for Small Molecules Using Comprehensive Molecular Representations The development of ion mobility-mass spectrometry (IM-MS) has revolutionized the analysis of small molecules, such as metabolomics, lipidomics, and exposome studies. The curation of comprehensive reference collision cross-section (CCS) databases plays a pivotal role in the successful application of IM-MS for small-molecule analysis. In this study, we presented AllCCS2, an enhanced version of AllCCS, designed for the universal prediction of the ion mobility CCS values of small molecules. AllCCS2 incorporated newly available experimental CCS data, including 10,384 records and 7713 unified values, as training data. By leveraging a neural network trained on diverse molecular representations encompassing mass spectrometry features, molecular descriptors, and graph features extracted using a graph convolutional network, AllCCS2 achieved exceptional prediction accuracy. AllCCS2 achieved median relative error (MedRE) values of 0.31, 0.72, and 1.64% in the training, validation, and testing sets, respectively, surpassing existing CCS prediction tools in terms of accuracy and coverage. Furthermore, AllCCS2 exhibited excellent compatibility with different instrument platforms (DTIMS, TWIMS, and TIMS). The prediction uncertainties in AllCCS2 from the training data and the prediction model were comprehensively investigated by using representative structure similarity and model prediction variation. Notably, small molecules with high structural similarities to the training set and lower model prediction variation exhibited improved accuracy and lower relative errors. In summary, AllCCS2 serves as a valuable resource to support applications of IM-MS technologies. The AllCCS2 database and tools are freely accessible at http://allccs.zhulab.cn/. Chemistry ; Collision ; Atlas (anatomy) ; Molecule ; Small molecule ; Ion ; Section (typography) ; Nanotechnology ; Organic chemistry ; Biochemistry ; Programming language ; Operating system Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Analytical Chemistry and Chromatography
Authors: Hussaini Adam | Subash C. B. Gopinath | M. K. Md Arshad | Tijjani Adam | N. A. Parmin | Irzaman Irzaman | U. Hashim
Source: 3 Biotech (review, 2023-04-27)
Field: Materials Science — Polymers and Plastics

An update on pathogenesis and clinical scenario for Parkinson’s disease: diagnosis and treatment Parkinson's disease ; Disease ; Substantia nigra ; Pars compacta ; Medicine ; Neuroscience ; Dopaminergic ; Psychology ; Pathology ; Dopamine Conducting polymers and applications ; Neuroscience and Neural Engineering ; Parkinson's Disease Mechanisms and Treatments
Authors: S. Minisha | Jerald B. Johnson | Saikh Mohammad Wabaidur | Jeetendra Kumar Gupta | Sikandar Aftab | Masoom Raza Siddiqui | Wen‐Cheng Lai
Source: Sustainability (article, 2023-10-07)
Field: Materials Science — Polymers and Plastics

Synthesis and Characterizations of Fe-Doped NiO Nanoparticles and Their Potential Photocatalytic Dye Degradation Activities Recently, the preparation of smart multifunctional hybrid nanoparticles has captured significant interest in versatile areas, including medicine, environment, and food, due to their enhanced physicochemical properties. The present study focuses on the synthesis of Fe-doped NiO nanoparticles by the coprecipitation method using the sources of nickel (II) acetate tetrahydrate and iron (III) nitrate nonahydrate. The prepared Fe-doped NiO nanoparticles are characterized by X-ray diffraction, Fourier transform infrared spectroscopy, UV–visible spectroscopy, field-emission scanning electron microscopy, transmission electron microscopy, and X-ray photon spectroscopic analysis. The XRD results clearly confirm the face-centered cubic structure and polycrystalline nature of the synthesized Fe-NiO nanoparticles. The Tauc plot analysis revealed that the bandgap energy of the Fe-doped NiO nanoparticles decreased with the increasing concentration of the Fe dopant from 2% to 8%. The XPS analysis of the samples exhibited the existence of elements, including Fe, Ni, and O, with the absence of any surplus compounds. The FE-SEM and TEM analyses proved the formation of nanostructured Fe-NiO with few spherical and mostly unevenly shaped particles. Further, the photocatalytic efficiency of the prepared Fe-doped NiO nanoparticles were identified by using the cationic dye rhodamine B (Rh-B). The photocatalytic results proved the 8% of Fe doped with NiO nanoparticles achieved 99% of Rh-B degradation within 40 min of visible-light irradiation. Hence, the results of the present study exemplified the Fe-doped NiO nanoparticles have acted as a noticeable photocatalyst to degrade the Rh-B dye. Non-blocking I/O ; Materials science ; Photocatalysis ; Rhodamine B ; Nanoparticle ; X-ray photoelectron spectroscopy ; Dopant ; Fourier transform infrared spectroscopy ; Chemical engineering ; Nuclear chemistry ; Visible spectrum ; Doping ; Inorganic chemistry ; Nanotechnology ; Catalysis ; Chemistry ; Organic chemistry Transition Metal Oxide Nanomaterials ; Copper-based nanomaterials and applications ; Gas Sensing Nanomaterials and Sensors