jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Xu Yang | Ahmed K. Rashwan | Ahmed I. Osman | Eman M. Abd El-Monaem | Ahmed M. Elgarahy | Abdelazeem S. Eltaweil | Mirna Omar | Yuting Li | Abul-Hamd E. Mehanni | Wei Chen | David W. Rooney
Source: Environmental Chemistry Letters (review, 2022-09-19)
Field: Chemistry — Inorganic Chemistry

Synthesis and potential applications of cyclodextrin-based metal–organic frameworks: a review Metal-organic frameworks are porous polymeric materials formed by linking metal ions with organic bridging ligands. Metal-organic frameworks are used as sensors, catalysts for organic transformations, biomass conversion, photovoltaics, electrochemical applications, gas storage and separation, and photocatalysis. Nonetheless, many actual metal-organic frameworks present limitations such as toxicity of preparation reagents and components, which make frameworks unusable for food and pharmaceutical applications. Here, we review the structure, synthesis and properties of cyclodextrin-based metal-organic frameworks that could be used in bioapplications. Synthetic methods include vapor diffusion, microwave-assisted, hydro/solvothermal, and ultrasound techniques. The vapor diffusion method can produce cyclodextrin-based metal-organic framework crystals with particle sizes ranging from 200 nm to 400 μm. Applications comprise food packaging, drug delivery, sensors, adsorbents, gas separation, and membranes. Cyclodextrin-based metal-organic frameworks showed loading efficacy of the bioactive compounds ranging from 3.29 to 97.80%. Metal-organic framework ; Materials science ; Nanotechnology ; Cyclodextrin ; Reagent ; Metal ions in aqueous solution ; Chemical engineering ; Metal ; Adsorption ; Organic chemistry ; Chemistry Metal-Organic Frameworks: Synthesis and Applications ; Dendrimers and Hyperbranched Polymers ; Advanced Nanomaterials in Catalysis
Authors: Jacopo Perego | Charl X. Bezuidenhout | Irène Villa | Francesca Cova | Roberta Crapanzano | I.M. Frank | F. Pagano | N. Kratochwil | E. Auffray | Silvia Bracco | A. Vedda | Christophe Dujardin | Piero Sozzani | Francesco Meinardi | Angiolina Comotti | Angelo Monguzzi
Source: Nature Communications (article, 2022-06-17)
Field: Chemistry — Inorganic Chemistry

Highly luminescent scintillating hetero-ligand MOF nanocrystals with engineered Stokes shift for photonic applications Large Stokes shift fast emitters show a negligible reabsorption of their luminescence, a feature highly desirable for several applications such as fluorescence imaging, solar-light managing, and fabricating sensitive scintillating detectors for medical imaging and high-rate high-energy physics experiments. Here we obtain high efficiency luminescence with significant Stokes shift by exploiting fluorescent conjugated acene building blocks arranged in nanocrystals. Two ligands of equal molecular length and connectivity, yet complementary electronic properties, are co-assembled by zirconium oxy-hydroxy clusters, generating crystalline hetero-ligand metal-organic framework (MOF) nanocrystals. The diffusion of singlet excitons within the MOF and the matching of ligands absorption and emission properties enables an ultrafast activation of the low energy emission in the 100 ps time scale. The hybrid nanocrystals show a fluorescence quantum efficiency of ~60% and a Stokes shift as large as 750 meV (~6000 cm<sup>-1</sup>), which suppresses the emission reabsorption also in bulk devices. The fabricated prototypal nanocomposite fast scintillator shows benchmark performances which compete with those of some inorganic and organic commercial systems. Stokes shift ; Materials science ; Luminescence ; Nanocrystal ; Absorption (acoustics) ; Scintillator ; Optoelectronics ; Quantum dot ; Photonics ; Nanotechnology ; Fluorescence ; Optics ; Detector ; Physics Metal-Organic Frameworks: Synthesis and Applications ; Luminescence and Fluorescent Materials ; Nanoplatforms for cancer theranostics
Authors: Margit Lang | Stefan Hirner | Frank Wiesbrock | Peter Fuchs
Source: Polymers (review, 2022-05-19)
Field: Chemistry — Organic Chemistry

A Review on Modeling Cure Kinetics and Mechanisms of Photopolymerization Photopolymerizations, in which the initiation of a chemical-physical reaction occurs by the exposure of photosensitive monomers to a high-intensity light source, have become a well-accepted technology for manufacturing polymers. Providing significant advantages over thermal-initiated polymerizations, including fast and controllable reaction rates, as well as spatial and temporal control over the formation of material, this technology has found a large variety of industrial applications. The reaction mechanisms and kinetics are quite complex as the system moves quickly from a liquid monomer mixture to a solid polymer. Therefore, the study of curing kinetics is of utmost importance for industrial applications, providing both the understanding of the process development and the improvement of the quality of parts manufactured via photopolymerization. Consequently, this review aims at presenting the materials and curing chemistry of such ultrafast crosslinking polymerization reactions as well as the research efforts on theoretical models to reproduce cure kinetics and mechanisms for free-radical and cationic photopolymerizations including diffusion-controlled phenomena and oxygen inhibition reactions in free-radical systems. Photopolymer ; Polymerization ; Curing (chemistry) ; Kinetics ; Cationic polymerization ; Monomer ; Materials science ; Polymer ; Radical polymerization ; Chemical engineering ; Polymer chemistry ; Photochemistry ; Chemistry ; Composite material Photopolymerization techniques and applications ; Additive Manufacturing and 3D Printing Technologies ; Epoxy Resin Curing Processes
Authors: Wenyao Chen | Junbo Cao | Wenzhao Fu | Jing Zhang | Gang Qian | Jia Yang | De Chen | Xinggui Zhou | Weikang Yuan | Xuezhi Duan
Source: Angewandte Chemie International Edition (article, 2022-02-08)
Field: Materials Science — Materials Chemistry

Molecular‐Level Insights into the Notorious CO Poisoning of Platinum Catalyst Carbon monoxide (CO) is notorious for its strong adsorption to poison platinum group metal catalysts in the chemical industry. Here, we conceptually distinguish and quantify the effects of the occupancy and energy of d electrons, emerging as the two vital factors in d-band theory, for CO poisoning of Pt nanocatalysts. The stepwise defunctionalization of carbon support is adopted to fine-tune the 5d electronic structure of supported Pt nanoparticles. Excluding other promotional mechanisms, the increase of Pt 5d band energy strengthens the competitive adsorption of hydrogen against CO for the preferential oxidation of CO, affording the scaling relationship between Pt 5d band energy and CO/H<sub>2</sub> adsorption energy difference. The decrease of Pt 5d band occupancy lowers CO site coverage to promote its association with oxygen for the total oxidation of CO, giving the scaling relationship between Pt 5d occupancy and activation energy. The above insights outline a molecular-level understanding of CO poisoning. CO poisoning ; Nanomaterial-based catalyst ; Catalysis ; Platinum ; Carbon monoxide ; Adsorption ; Chemistry ; Photochemistry ; Materials science ; Nanotechnology ; Physical chemistry ; Organic chemistry Catalytic Processes in Materials Science ; Electrocatalysts for Energy Conversion ; Catalysis and Oxidation Reactions
Authors: Xue Wan | Yang He | Yanju Liu | Jinsong Leng
Source: Additive manufacturing (article, 2022-02-16)
Field: Materials Science — Polymers and Plastics

4D printing of multiple shape memory polymer and nanocomposites with biocompatible, programmable and selectively actuated properties Materials science ; Shape-memory polymer ; Shape-memory alloy ; Nanocomposite ; Smart material ; Stereolithography ; 3D printing ; Controllability ; Nanotechnology ; Polymer ; Biocompatible material ; Composite material ; Biomedical engineering Polymer composites and self-healing ; Advanced Materials and Mechanics ; Advanced Sensor and Energy Harvesting Materials
Authors: Shixuan Feng | Futian Zhai | Huahua Su | Deepak Sridhar | Hassan Algadi | Ben Bin Xu | Rami Adel Pashameah | Eman Alzahrani | Hala M. Abo‐Dief | Yong Ma | Tingxi Li | Zhanhu Guo
Source: Materials Today Physics (article, 2022-12-20)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Progress of metal organic frameworks-based composites in electromagnetic wave absorption Materials science ; Absorption (acoustics) ; Porosity ; Attenuation ; Electromagnetic radiation ; Porous medium ; Composite material ; Nanotechnology ; Optics Electromagnetic wave absorption materials ; Advanced Antenna and Metasurface Technologies ; Metamaterials and Metasurfaces Applications
Authors: Timothée Stoerkler | Thibault Pariat | Adèle D. Laurent | Denis Jacquemin | Gilles Ulrich | Julien Massue
Source: Molecules (review, 2022-04-10)
Field: Materials Science — Materials Chemistry

Excited-State Intramolecular Proton Transfer Dyes with Dual-State Emission Properties: Concept, Examples and Applications Dual-state emissive (DSE) fluorophores are organic dyes displaying fluorescence emission both in dilute and concentrated solution and in the solid-state, as amorphous, single crystal, polycrystalline samples or thin films. This comes in contrast to the vast majority of organic fluorescent dyes which typically show intense fluorescence in solution but are quenched in concentrated media and in the solid-state owing to π-stacking interactions; a well-known phenomenon called aggregation-caused quenching (ACQ). On the contrary, molecular rotors with a significant number of free rotations have been engineered to show quenched emission in solution but strong fluorescence in the aggregated-state thanks to restriction of the intramolecular motions. This is the concept of aggregation-induced emission (AIE). DSE fluorophores have been far less explored despite the fact that they are at the crossroad of ACQ and AIE phenomena and allow targeting applications both in solution (bio-conjugation, sensing, imaging) and solid-state (organic electronics, data encryption, lasing, luminescent displays). Excited-State Intramolecular Proton Transfer (ESIPT) fluorescence is particularly suitable to engineer DSE dyes. Indeed, ESIPT fluorescence, which relies on a phototautomerism between normal and tautomeric species, is characterized by a strong emission in the solid-state along with a large Stokes' shift, an enhanced photostability and a strong sensitivity to the close environment, a feature prone to be used in bio-sensing. A drawback that needs to be overcome is their weak emission intensity in solution, owing to detrimental molecular motions in the excited-state. Several strategies have been proposed in that regard. In the past few years, a growing number of examples of DSE-ESIPT dyes have indeed emerged in the literature, enriching the database of such attractive dyes. This review aims at a brief but concise overview on the exploitation of ESIPT luminescence for the optimization of DSE dyes properties. In that perspective, a synergistic approach between organic synthesis, fluorescence spectroscopy and ab initio calculations has proven to be an efficient tool for the construction and optimization of DSE-ESIPT fluorophores. Fluorescence ; Intramolecular force ; Photochemistry ; Excited state ; Luminescence ; Stacking ; Tautomer ; Chemistry ; Quenching (fluorescence) ; Relaxation (psychology) ; Stokes shift ; Lasing threshold ; Chemical physics ; Aggregation-induced emission ; Materials science ; Optoelectronics ; Optics ; Atomic physics ; Organic chemistry Luminescence and Fluorescent Materials ; Photochemistry and Electron Transfer Studies ; Porphyrin and Phthalocyanine Chemistry
Authors: Maxime Van Haeverbeke | Michiel Stock | Bernard De Baets
Source: IEEE Access (article, 2022-01-01)
Field: Chemistry — Electrochemistry

Equivalent Electrical Circuits and Their Use Across Electrochemical Impedance Spectroscopy Application Domains When studying electrochemical systems, EIS practitioners face the challenge of choosing a relevant equivalent electrical circuit to analyze their measurement data and interpreting the role of its components. In this review, we take a closer look at the use of equivalent electrical circuits (EEC) across various application domains.We aim to aid EIS practitioners in determining and evaluating their EEC-based data analysis methodology in light of recent progress from all EIS application domains. We review EEC usage and its interpretation while additionally providing software to automatically search for equivalent electrical circuits from the relevant application domain literature that fit EIS measurements supplied by users. Finally, we make a comparison of the impedimetric behaviour and circuit modelling approaches of a range of different electrochemical systems and discuss some complementary EIS data analysis strategies. Dielectric spectroscopy ; Equivalent circuit ; Electronic circuit ; Computer science ; Electrical impedance ; Electronic engineering ; Electrical network ; Electrical engineering ; Voltage ; Electrochemistry ; Engineering ; Physics Electrochemical Analysis and Applications ; Analytical Chemistry and Sensors ; Fuel Cells and Related Materials
Authors: Zaheer Ud Din Babar | Bartolomeo Della Ventura | Raffaele Velotta | Vincenzo Iannotti
Source: RSC Advances (review, 2022-01-01)
Field: Materials Science — Materials Chemistry

Advances and emerging challenges in MXenes and their nanocomposites for biosensing applications This review article summarizes the current progress on chemical stability and recent advances/challenges in synthesis of MXenes and their nanocomposites for biosensing applications. MXenes ; Biosensor ; Nanotechnology ; Materials science ; Stacking ; Nanocomposite ; Nanoparticle ; Chemistry MXene and MAX Phase Materials ; Graphene and Nanomaterials Applications ; Advanced biosensing and bioanalysis techniques
Authors: Afreen Sultana | Ajay Kathuria | Kirtiraj K. Gaikwad
Source: Environmental Chemistry Letters (review, 2022-01-11)
Field: Chemistry — Inorganic Chemistry

Metal–organic frameworks for active food packaging. A review Active packaging ; Food packaging ; Metal-organic framework ; Waste management ; Biochemical engineering ; Environmental science ; Nanotechnology ; Materials science ; Chemistry ; Food science ; Organic chemistry ; Engineering Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications ; Advanced Photocatalysis Techniques
Authors: Shu Huang | Jacqueline M. Cole
Source: Journal of Chemical Information and Modeling (article, 2022-05-09)
Field: Materials Science — Materials Chemistry

BatteryBERT: A Pretrained Language Model for Battery Database Enhancement A great number of scientific papers are published every year in the field of battery research, which forms a huge textual data source. However, it is difficult to explore and retrieve useful information efficiently from these large unstructured sets of text. The Bidirectional Encoder Representations from Transformers (BERT) model, trained on a large data set in an unsupervised way, provides a route to process the scientific text automatically with minimal human effort. To this end, we realized six battery-related BERT models, namely, BatteryBERT, BatteryOnlyBERT, and BatterySciBERT, each of which consists of both cased and uncased models. They have been trained specifically on a corpus of battery research papers. The pretrained BatteryBERT models were then fine-tuned on downstream tasks, including battery paper classification and extractive question-answering for battery device component classification that distinguishes anode, cathode, and electrolyte materials. Our BatteryBERT models were found to outperform the original BERT models on the specific battery tasks. The fine-tuned BatteryBERT was then used to perform battery database enhancement. We also provide a website application for its interactive use and visualization. Computer science ; Transformer ; Encoder ; Battery (electricity) ; Language model ; Process (computing) ; Artificial intelligence ; Natural language processing ; Information retrieval ; Data mining ; Power (physics) ; Voltage ; Electrical engineering ; Programming language Machine Learning in Materials Science ; Topic Modeling ; Text and Document Classification Technologies
Authors: Dejin Zang | Haiqing Wang
Source: Polyoxometalates (article, 2022-09-01)
Field: Materials Science — Materials Chemistry

Polyoxometalate-based nanostructures for electrocatalytic and photocatalytic CO <sub>2</sub> reduction Electro/photocatalytic carbon dioxide (CO<sub>2</sub>) reduction to value-added chemicals and fuels is being actively studied as a promising pathway for renewable energy storage and climate change mitigation. Because of inert molecular properties and competing hydrogen generation reactions, high-performance electrocatalysts with high Faradaic efficiency and product selectivity but low overpotential are urgently needed. Polyoxometalates (POMs) are a class of polynuclear metal oxide clusters with a precise atomic structure, providing an ideal research platform to reveal the relationship between macroscopic properties and microstructures. Moreover, their highly tunable redox properties and abundant transition metal atom composition ensure thriving research for POM-based nanostructures toward CO<sub>2</sub> reduction. In this review, we first introduce the specific roles of POMs in electro/photocatalytic CO<sub>2</sub> reduction. Recent advances in POM-based nanostructures ranging from single clusters, assemblies, organic–inorganic hybrids to derivatives are systematically summarized. In particular, the structure–performance relationship of POM-based nanostructures is discussed at the atomic and molecular levels. Finally, the challenges and opportunities in the design of high-efficiency POM-based nanostructures are discussed to promote electro/photocatalytic CO<sub>2</sub> reduction. Polyoxometalate ; Photocatalysis ; Overpotential ; Materials science ; Nanostructure ; Electrochemical reduction of carbon dioxide ; Nanotechnology ; Faraday efficiency ; Oxide ; Catalysis ; Nanomaterials ; Chemical engineering ; Electrochemistry ; Chemistry ; Carbon monoxide ; Physical chemistry ; Electrode ; Organic chemistry Polyoxometalates: Synthesis and Applications ; CO2 Reduction Techniques and Catalysts ; Advanced Photocatalysis Techniques
Authors: Ze Yang | Wang Gao
Source: Advanced Science (review, 2022-03-01)
Field: Materials Science — Materials Chemistry

Applications of Machine Learning in Alloy Catalysts: Rational Selection and Future Development of Descriptors At present, alloys have broad application prospects in heterogeneous catalysis, due to their various catalytic active sites produced by their vast element combinations and complex geometric structures. However, it is the diverse variables of alloys that lead to the difficulty in understanding the structure-property relationship for conventional experimental and theoretical methods. Fortunately, machine learning methods are helpful to address the issue. Machine learning can not only deal with a large number of data rapidly, but also help establish the physical picture of reactions in multidimensional heterogeneous catalysis. The key challenge in machine learning is the exploration of suitable general descriptors to accurately describe various types of alloy catalysts, which help reasonably design catalysts and efficiently screen candidates. In this review, several kinds of machine learning methods commonly used in the design of alloy catalysts is introduced, and the applications of various reactivity descriptors corresponding to different alloy systems is summarized. Importantly, this work clarifies the existing understanding of physical picture of heterogeneous catalysis, and emphasize the significance of rational selection of universal descriptors. Finally, the development of heterogeneous catalytic descriptors for machine learning are presented. Machine learning ; Rational design ; Computer science ; Artificial intelligence ; Selection (genetic algorithm) ; Biochemical engineering ; Nanotechnology ; Materials science ; Engineering Machine Learning in Materials Science ; Electrocatalysts for Energy Conversion ; Catalytic Processes in Materials Science
Authors: Jieyu Lü | Yingkai Zhang
Source: Journal of Chemical Information and Modeling (article, 2022-03-10)
Field: Materials Science — Materials Chemistry

Unified Deep Learning Model for Multitask Reaction Predictions with Explanation There is significant interest and importance to develop robust machine learning models to assist organic chemistry synthesis. Typically, task-specific machine learning models for distinct reaction prediction tasks have been developed. In this work, we develop a unified deep learning model, T5Chem, for a variety of chemical reaction predictions tasks by adapting the "Text-to-Text Transfer Transformer" (T5) framework in natural language processing (NLP). On the basis of self-supervised pretraining with PubChem molecules, the T5Chem model can achieve state-of-the-art performances for four distinct types of task-specific reaction prediction tasks using four different open-source data sets, including reaction type classification on USPTO_TPL, forward reaction prediction on USPTO_MIT, single-step retrosynthesis on USPTO_50k, and reaction yield prediction on high-throughput C-N coupling reactions. Meanwhile, we introduced a new unified multitask reaction prediction data set USPTO_500_MT, which can be used to train and test five different types of reaction tasks, including the above four as well as a new reagent suggestion task. Our results showed that models trained with multiple tasks are more robust and can benefit from mutual learning on related tasks. Furthermore, we demonstrated the use of SHAP (SHapley Additive exPlanations) to explain T5Chem predictions at the functional group level, which provides a way to demystify sequence-based deep learning models in chemistry. T5Chem is accessible through https://yzhang.hpc.nyu.edu/T5Chem. Computer science ; Artificial intelligence ; Deep learning ; Machine learning Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Fault Detection and Control Systems