jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Wenyu Wu | Aurelio Bifulco | Carolina Polisi | Zhenyu Huang | Sabyasachi Gaan
Source: Composites Part B Engineering (article, 2023-03-15)
Field: Materials Science — Polymers and Plastics

Recyclable inherently flame-retardant thermosets: Chemistry, properties and applications Thermosets are polymeric materials that contain permanent networks and thus are difficult to recycle. They are not reprocessable once cured and often do not degrade under mild conditions. Over the past decades, the use of polymeric materials in fire safety applications has increased, and so is the need for them to be more sustainable. From this standpoint, recently two major challenges in designing next-generation thermosets have attracted much attention in the scientific community: embedded fire safety and reprocessability/recyclability. In this review, a detailed report on research progress in design of fire-safe and thermomechanical reprocessable/recyclable thermosets is presented. Such thermosets are designed not only to enable the reuse and recycling of the polymer material but also recover valuable components (carbon fibers or rare additives) that are encapsulated in the matrix. The flame retardant recyclable thermoset materials are categorized based on the chemistry of the labile bonds (covalent adaptable networks): i.e. (i) esters (carboxylic and phosphate esters), (ii) sulfur-containing linkages, (iii) nitrogen-containing structures, and (iv) other phosphorus-containing structures. In addition, the use of bio-based raw materials in constructing these thermosets is also highlighted. The synthetic route, fire performance, recycling method, degradation mechanism, and progress in various approaches being developed by researchers towards recyclable and fire-safe thermosets are summarized in detail in this review. Thermosetting polymer ; Fire retardant ; Reuse ; Raw material ; Materials science ; Chemistry ; Organic chemistry ; Waste management ; Engineering ; Composite material Flame retardant materials and properties ; Polymer composites and self-healing ; Carbon dioxide utilization in catalysis
Authors: Abhilash Rana | Meheli Adhikary | Praveen Kumar Singh | Bhudev C. Das | Seema Bhatnagar
Source: Frontiers in Chemistry (review, 2023-01-04)
Field: Materials Science — Biomaterials

“Smart” drug delivery: A window to future of translational medicine Chemotherapy is the mainstay of cancer treatment today. Chemotherapeutic drugs are non-selective and can harm both cancer and healthy cells, causing a variety of adverse effects such as lack of specificity, cytotoxicity, short half-life, poor solubility, multidrug resistance, and acquiring cancer stem-like characteristics. There is a paradigm shift in drug delivery systems (DDS) with the advent of smarter ways of targeted cancer treatment. Smart Drug Delivery Systems (SDDSs) are stimuli responsive and can be modified in chemical structure in response to light, pH, redox, magnetic fields, and enzyme degradation can be future of translational medicine. Therefore, SDDSs have the potential to be used as a viable cancer treatment alternative to traditional chemotherapy. This review focuses mostly on stimuli responsive drug delivery, inorganic nanocarriers (Carbon nanotubes, gold nanoparticles, Meso-porous silica nanoparticles, quantum dots <i>etc.</i>), organic nanocarriers (Dendrimers, liposomes, micelles), antibody-drug conjugates (ADC) and small molecule drug conjugates (SMDC) based SDDSs for targeted cancer therapy and strategies of targeted drug delivery systems in cancer cells. Nanocarriers ; Drug delivery ; Nanotechnology ; Drug ; Cancer ; Targeted drug delivery ; Nanomedicine ; Pharmacology ; Medicine ; Chemistry ; Materials science ; Nanoparticle ; Internal medicine Nanoparticle-Based Drug Delivery ; Graphene and Nanomaterials Applications ; Nanoplatforms for cancer theranostics
Authors: Qiuyu Ye | Enxian Yuan | Shen Jin | Mingli Ye | Qin Xu | Xiao Hu | Yun Shu | Huan Pang
Source: Advanced Science (article, 2023-08-27)
Field: Materials Science — Materials Chemistry

Amphiphilic Polymer Capped Perovskite Compositing with Nano Zr‐MOF for Nanozyme‐Involved Biomimetic Cascade Catalysis CsPbX<sub>3</sub> perovskite nanocrystal (NC) is considered as an excellent optical material and is widely applied in optoelectronics. However, its poor water stability impedes its study in enzyme-like activity, and further inhibits its application in biomimetic cascade catalysis. Herein, for the first time, the oxidase-like and ascorbate oxidase-like activities of an amphiphilic polymer capped CsPbX<sub>3</sub> are demonstrated, and its catalytic mechanism is further explored. Furthermore, an all-nanozyme cascade system (multifunctional CsPbBr<sub>3</sub> @Zr-metal organic framework (Zr-MOF) and Prussian blue as oxidase-like and peroxidase-like nanozyme) is constructed with a portable paper-based device for realizing the dual-mode (ratiometric fluorescence and colorimetric) detection of ascorbic acid in a point-of-care (POC) fashion. This is the first report on the utilization of all-inorganic CsPbX<sub>3</sub> perovskite NC in biomimetic cascade catalysis, which opens a new avenue for POC clinical disease diagnosis. Prussian blue ; Catalysis ; Nanotechnology ; Materials science ; Perovskite (structure) ; Nanocrystal ; Ascorbic acid ; Glucose oxidase ; Cascade ; Polymer ; Amphiphile ; Chemistry ; Combinatorial chemistry ; Biosensor ; Organic chemistry ; Copolymer Advanced Nanomaterials in Catalysis ; Electrochemical sensors and biosensors ; Advanced biosensing and bioanalysis techniques
Authors: Glenn K. K. Clothier | Thiago R. Guimarães | Steven Thompson | Julia Y. Rho | Sébastien Perrier | Graeme Moad | Per B. Zetterlund
Source: Chemical Society Reviews (review, 2023-01-01)
Field: Chemistry — Organic Chemistry

Multiblock copolymer synthesis<i>via</i>RAFT emulsion polymerization A multiblock copolymer is a polymer of a specific structure that consists of multiple covalently linked segments, each comprising a different monomer type. The control of the monomer sequence has often been described as the "holy grail" of synthetic polymer chemistry, with the ultimate goal being synthetic access to polymers of a "perfect" structure, where each monomeric building block is placed at a desired position along the polymer chain. Given that polymer properties are intimately linked to the microstructure and monomer distribution along the constituent chains, it goes without saying that there exist seemingly endless opportunities in terms of fine-tuning the properties of such materials by careful consideration of the length of each block, the number and order of blocks, and the inclusion of monomers with specific functional groups. The area of multiblock copolymer synthesis remains relatively unexplored, in particular with regard to structure-property relationships, and there are currently significant opportunities for the design and synthesis of advanced materials. The present review focuses on the synthesis of multiblock copolymers <i>via</i> reversible addition-fragmentation chain transfer (RAFT) polymerization implemented as aqueous emulsion polymerization. RAFT emulsion polymerization offers intriguing opportunities not only for the advanced synthesis of multiblock copolymers, but also provides access to polymeric nanoparticles of specific morphologies. Precise multiblock copolymer synthesis coupled with self-assembly offers material morphology control on length scales ranging from a few nanometers to a micrometer. It is imperative that polymer chemists interact with physicists and material scientists to maximize the impact of these materials of the future. Raft ; Copolymer ; Emulsion polymerization ; Reversible addition−fragmentation chain-transfer polymerization ; Polymerization ; Emulsion ; Chain transfer ; Polymer chemistry ; Chemistry ; Chemical engineering ; Materials science ; Radical polymerization ; Polymer ; Organic chemistry Advanced Polymer Synthesis and Characterization ; Radioactive element chemistry and processing ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: Yitao Wu | Meiqi Tang | Zeju Wang | Le Shi | Zhangyi Xiong | Zhijie Chen | Jonathan L. Sessler | Feihe Huang
Source: Nature Communications (article, 2023-08-15)
Field: Chemistry — Inorganic Chemistry

Pillararene incorporated metal–organic frameworks for supramolecular recognition and selective separation Crystalline frameworks containing incorporated flexible macrocycle units can afford new opportunities in molecular recognition and selective separation. However, such functionalized frameworks are difficult to prepare and challenging to characterize due to the flexible nature of macrocycles, which limits the development of macrocycle-based crystalline frameworks. Herein, we report the design and synthesis of a set of metal-organic frameworks (MOFs) containing pillar[5]arene units. The pillar[5]arene units were uniformly embedded in the periodic frameworks. Single crystal X-ray diffraction analysis revealed an interpenetrated network that appears to hinder the rotation of the pillar[5]arene repeating units in the frameworks, and it therefore resulted in the successful determination of the precise pillar[5]arene host structure in a MOF crystal. These MOFs can recognize paraquat and 1,2,4,5-tetracyanobenzene in solution and selectively remove trace pyridine from toluene with relative ease. The work presented here represents a critical step towards the synthesis of macrocycle-incorporated crystalline frameworks with well-defined structures and functional utility. Supramolecular chemistry ; Pillar ; Metal-organic framework ; Materials science ; Nanotechnology ; Molecular recognition ; Molecule ; Pyridine ; Crystal structure ; Combinatorial chemistry ; Crystallography ; Chemistry ; Organic chemistry Metal-Organic Frameworks: Synthesis and Applications ; Supramolecular Chemistry and Complexes ; Molecular Sensors and Ion Detection
Authors: Xiao Xiao | Kaini Xu | Zhong‐Hua Gao | Zhou‐Hao Zhu | Changqing Ye | Baoguo Zhao | Sanzhong Luo | Song Ye | Yong‐Gui Zhou | Senmiao Xu | Shou‐Fei Zhu | Hongli Bao | Wei Sun | Xiaoming Wang | Kuiling Ding
Source: Science China Chemistry (article, 2023-04-25)
Field: Chemistry — Inorganic Chemistry

Biomimetic asymmetric catalysis Biomimetic synthesis ; Chemistry ; Catalysis ; Enantioselective synthesis ; Enzyme catalysis ; Flavin group ; Combinatorial chemistry ; Nanotechnology ; Enzyme ; Stereochemistry ; Organic chemistry ; Materials science Asymmetric Hydrogenation and Catalysis ; Cyclopropane Reaction Mechanisms ; Synthesis and Catalytic Reactions
Authors: Alexandra Pusta | Mihaela Tertiş | Izabell Crăciunescu | Rodica Turcu | Simona Mirel | Cécilia Cristea
Source: Pharmaceutics (review, 2023-07-03)
Field: Materials Science — Biomaterials

Recent Advances in the Development of Drug Delivery Applications of Magnetic Nanomaterials With the predicted rise in the incidence of cancer, there is an ever-growing need for new cancer treatment strategies. Recently, magnetic nanoparticles have stood out as promising nanostructures for imaging and drug delivery systems as they possess unique properties. Moreover, magnetic nanomaterials functionalized with other compounds can lead to multicomponent nanoparticles with innovative structures and synergetic performance. The incorporation of chemotherapeutic drugs or RNA in magnetic drug delivery systems represents a promising alternative that can increase efficiency and reduce the side effects of anticancer therapy. This review presents a critical overview of the recent literature concerning the advancements in the field of magnetic nanoparticles used in drug delivery, with a focus on their classification, characteristics, synthesis and functionalization methods, limitations, and examples of magnetic drug delivery systems incorporating chemotherapeutics or RNA. Drug delivery ; Nanotechnology ; Magnetic nanoparticles ; Nanomaterials ; Targeted drug delivery ; Cancer therapy ; Drug ; Surface modification ; Materials science ; Nanoparticle ; Chemistry ; Cancer ; Pharmacology ; Medicine ; Internal medicine Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; Advanced Nanomaterials in Catalysis
Authors: Zhecheng Yu | Xingyue Shen | Han Yu | Haohong Tu | Chuda Chittasupho | Yunqi Zhao
Source: Pharmaceutics (review, 2023-02-26)
Field: Materials Science — Biomaterials

Smart Polymeric Nanoparticles in Cancer Immunotherapy Cancer develops with unexpected mutations and causes death in many patients. Among the different cancer treatment strategies, immunotherapy is promising with the benefits of high specificity and accuracy, as well as modulating immune responses. Nanomaterials can be used to formulate drug delivery carriers for targeted cancer therapy. Polymeric nanoparticles used in the clinic are biocompatible and have excellent stability. They have the potential to improve therapeutic effects while significantly reducing off-target toxicity. This review classifies smart drug delivery systems based on their components. Synthetic smart polymers used in the pharmaceutical industry, including enzyme-responsive, pH-responsive, and redox-responsive polymers, are discussed. Natural polymers derived from plants, animals, microbes, and marine organisms can also be used to construct stimuli-responsive delivery systems with excellent biocompatibility, low toxicity, and biodegradability. The applications of smart or stimuli-responsive polymers in cancer immunotherapies are discussed in this systemic review. We summarize different delivery strategies and mechanisms that can be used in cancer immunotherapy and give examples of each case. Immunotherapy ; Drug delivery ; Smart polymer ; Cancer immunotherapy ; Biocompatibility ; Nanotechnology ; Cancer therapy ; Cancer ; Drug ; Biocompatible material ; Targeted drug delivery ; Cancer treatment ; Immune system ; Chemistry ; Materials science ; Medicine ; Pharmacology ; Polymer ; Biomedical engineering ; Immunology Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; Advanced Drug Delivery Systems
Authors: Nathan J. Szymanski | Christopher J. Bartel | Yan Zeng | Mouhamad Diallo | Haegyeom Kim | Gerbrand Ceder
Source: npj Computational Materials (article, 2023-03-02)
Field: Materials Science — Materials Chemistry

Adaptively driven X-ray diffraction guided by machine learning for autonomous phase identification Abstract Machine learning (ML) has become a valuable tool to assist and improve materials characterization, enabling automated interpretation of experimental results with techniques such as X-ray diffraction (XRD) and electron microscopy. Because ML models are fast once trained, there is a key opportunity to bring interpretation in-line with experiments and make on-the-fly decisions to achieve optimal measurement effectiveness, which creates broad opportunities for rapid learning and information extraction from experiments. Here, we demonstrate such a capability with the development of autonomous and adaptive XRD. By coupling an ML algorithm with a physical diffractometer, this method integrates diffraction and analysis such that early experimental information is leveraged to steer measurements toward features that improve the confidence of a model trained to identify crystalline phases. We validate the effectiveness of an adaptive approach by showing that ML-driven XRD can accurately detect trace amounts of materials in multi-phase mixtures with short measurement times. The improved speed of phase detection also enables in situ identification of short-lived intermediate phases formed during solid-state reactions using a standard in-house diffractometer. Our findings showcase the advantages of in-line ML for materials characterization and point to the possibility of more general approaches for adaptive experimentation. Diffractometer ; Characterization (materials science) ; Diffraction ; Computer science ; Phase (matter) ; Identification (biology) ; Artificial intelligence ; Machine learning ; Spectrum analyzer ; Materials science ; Algorithm ; Nanotechnology ; Optics ; Scanning electron microscope ; Chemistry ; Physics Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Advancements in Battery Materials
Authors: Ninggui Ma | Yaqin Zhang | Yuhang Wang | Changxiong Huang | Jun Zhao | Bochun Liang | Jun Fan
Source: Applied Surface Science (article, 2023-04-10)
Field: Materials Science — Materials Chemistry

Machine learning-assisted exploration of the intrinsic factors affecting the catalytic activity of ORR/OER bifunctional catalysts Overpotential ; Janus ; Catalysis ; MXenes ; Bifunctional ; Chemistry ; Oxygen evolution ; Nanotechnology ; Materials science ; Chemical physics ; Physical chemistry ; Organic chemistry ; Electrochemistry MXene and MAX Phase Materials ; Electrocatalysts for Energy Conversion ; Fuel Cells and Related Materials
Authors: Alberto Ferrari | Fritz Körmann | Mark Asta | Jörg Neugebauer
Source: Nature Computational Science (article, 2023-03-31)
Field: Materials Science — Materials Chemistry

Simulating short-range order in compositionally complex materials Characterization (materials science) ; Range (aeronautics) ; Interatomic potential ; Scale (ratio) ; Materials science ; Statistical physics ; Computer science ; Nanotechnology ; Engineering physics ; Molecular dynamics ; Physics ; Chemistry ; Computational chemistry Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; High Entropy Alloys Studies
Authors: João Borges | Jinfeng Zeng | Xi Qiu Liu | Hao Chang | Claire Monge | Charlotte Garot | Ke‐feng Ren | Paul Machillot | Nihal Engin Vrana | Philippe Lavall�e | Takami Akagi | Michiya Matsusaki | Jian Ji | Mitsuru Akashi | João F. Mano | Varvara Gribova | Catherine Picart
Source: Advanced Healthcare Materials (review, 2023-12-20)
Field: Materials Science — Surfaces, Coatings and Films

Recent Developments in Layer‐by‐Layer Assembly for Drug Delivery and Tissue Engineering Applications Surfaces with biological functionalities are of great interest for biomaterials, tissue engineering, biophysics, and for controlling biological processes. The layer-by-layer (LbL) assembly is a highly versatile methodology introduced 30 years ago, which consists of assembling complementary polyelectrolytes or biomolecules in a stepwise manner to form thin self-assembled films. In view of its simplicity, compatibility with biological molecules, and adaptability to any kind of supporting material carrier, this technology has undergone major developments over the past decades. Specific applications have emerged in different biomedical fields owing to the possibility to load or immobilize biomolecules with preserved bioactivity, to use an extremely broad range of biomolecules and supporting carriers, and to modify the film's mechanical properties via crosslinking. In this review, the focus is on the recent developments regarding LbL films formed as 2D or 3D objects for applications in drug delivery and tissue engineering. Possible applications in the fields of vaccinology, 3D biomimetic tissue models, as well as bone and cardiovascular tissue engineering are highlighted. In addition, the most recent technological developments in the field of film construction, such as high-content liquid handling or machine learning, which are expected to open new perspectives in the future developments of LbL, are presented. Nanotechnology ; Biomolecule ; Drug delivery ; Tissue engineering ; Adaptability ; Layer by layer ; Computer science ; Materials science ; Layer (electronics) ; Engineering ; Biomedical engineering Polymer Surface Interaction Studies ; Surface Modification and Superhydrophobicity ; Nanofabrication and Lithography Techniques
Authors: Eric S. Muckley | James E. Saal | Bryce Meredig | Christopher S. Roper | John H. Martin
Source: Digital Discovery (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Interpretable models for extrapolation in scientific machine learning On average, simple linear models perform equivalently to black box machine learning models on extrapolation tasks. Extrapolation ; Machine learning ; Simple (philosophy) ; Computer science ; Artificial intelligence ; Black box ; Mathematics ; Statistics ; Epistemology Machine Learning in Materials Science ; Explainable Artificial Intelligence (XAI) ; Machine Learning and Data Classification
Authors: Yazhou Wang | Anil Koklu | Yizhou Zhong | Tianrui Chang | Keying Guo | Chao Zhao | Tania Cecilia Hidalgo Castillo | Zhonggao Bu | Chengyi Xiao | Wan Yue | Wei Ma | Sahika Inal
Source: Advanced Functional Materials (article, 2023-07-27)
Field: Materials Science — Polymers and Plastics

Acceptor Functionalization via Green Chemistry Enables High‐Performance n‐Type Organic Electrochemical Transistors for Biosensing, Memory Applications Abstract The organic electrochemical transistor (OECT) is one of the most versatile building blocks within the bioelectronics device toolbox. While p‐type organic semiconductors have progressed as OECT channel materials, only a few n‐type semiconductors have been reported, precluding the development of advanced sensor‐integrated OECT‐based complementary circuits. Herein, green aldol polymerization is uses to synthesize lactone‐based n‐type conjugated polymers. Fluorination of the lactone‐based acceptor endows a fully locked backbone with a low‐lying lowest unoccupied molecular orbital, facilitating efficient ionic‐to‐electronic charge coupling. The resulting polymer has a record‐high n‐type OECT performance with a high product of mobility and capacitance ( µC * = 108 F cm −1 V −1 s −1 ), excellent mobility (0.912 cm 2 V −1 s −1 ), low threshold voltage (0.02 V), and fast switching speed ( τ ON , τ OFF = 336 µs,108 µs). This work demonstrates two types of device architectures and applications enabled by the high performance of this n‐type OECT, i.e., an artificial synapse and a complementary amplifier for detecting α‐synuclein, a potential biomarker of Parkinson's disease. This study shows that materials that enable high gain and fast speed n‐type OECTs can be developed via a green polymerization route, and the diverse form factors that these devices take promise for exploration of other application areas. Materials science ; Bioelectronics ; Nanotechnology ; Transistor ; Organic electronics ; Acceptor ; Conductive polymer ; HOMO/LUMO ; Combinatorial chemistry ; Biosensor ; Polymer ; Chemistry ; Molecule ; Organic chemistry ; Electrical engineering ; Physics ; Voltage Conducting polymers and applications ; Advanced Sensor and Energy Harvesting Materials ; Organic Electronics and Photovoltaics