jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Abhi Bhadran | Tejas Shah | Godwin K. Babanyinah | Himanshu Polara | Somayeh Taslimy | Michael C. Biewer | Mihaela C. Stefan
Source: Pharmaceutics (review, 2023-07-19)
Field: Materials Science — Biomaterials

Recent Advances in Polycaprolactones for Anticancer Drug Delivery Poly(ε-Caprolactone)s are biodegradable and biocompatible polyesters that have gained considerable attention for drug delivery applications due to their slow degradation and ease of functionalization. One of the significant advantages of polycaprolactone is its ability to attach various functionalities to its backbone, which is commonly accomplished through ring-opening polymerization (ROP) of functionalized caprolactone monomer. In this review, we aim to summarize some of the most recent advances in polycaprolactones and their potential application in drug delivery. We will discuss different types of polycaprolactone-based drug delivery systems and their behavior in response to different stimuli, their ability to target specific locations, morphology, as well as their drug loading and release capabilities. Polycaprolactone ; Drug delivery ; Biocompatible material ; Polyester ; Drug ; Caprolactone ; Nanotechnology ; Chemistry ; Materials science ; Polymerization ; Biomedical engineering ; Pharmacology ; Medicine ; Polymer ; Organic chemistry biodegradable polymer synthesis and properties ; Electrospun Nanofibers in Biomedical Applications ; Advanced Polymer Synthesis and Characterization
Authors: James Damewood | Jessica Karaguesian | Jaclyn R. Lunger | Aik Rui Tan | Mingrou Xie | Jiayu Peng | Rafael Gómez‐Bombarelli
Source: Annual Review of Materials Research (article, 2023-04-18)
Field: Materials Science — Materials Chemistry

Representations of Materials for Machine Learning High-throughput data generation methods and machine learning (ML) algorithms have given rise to a new era of computational materials science by learning the relations between composition, structure, and properties and by exploiting such relations for design. However, to build these connections, materials data must be translated into a numerical form, called a representation, that can be processed by an ML model. Data sets in materials science vary in format (ranging from images to spectra), size, and fidelity. Predictive models vary in scope and properties of interest. Here, we review context-dependent strategies for constructing representations that enable the use of materials as inputs or outputs for ML models. Furthermore, we discuss how modern ML techniques can learn representations from data and transfer chemical and physical information between tasks. Finally, we outline high-impact questions that have not been fully resolved and thus require further investigation. Computer science ; Representation (politics) ; Context (archaeology) ; Fidelity ; Scope (computer science) ; Machine learning ; Ranging ; High fidelity ; Artificial intelligence ; Theoretical computer science ; Data science ; Programming language Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Catalysis and Oxidation Reactions
Authors: Yinlin Chen | Wanpeng Lu | Martin Schröder | Sihai Yang⧫
Source: Accounts of Chemical Research (article, 2023-08-30)
Field: Chemistry — Inorganic Chemistry

Analysis and Refinement of Host–Guest Interactions in Metal–Organic Frameworks ConspectusMetal-organic frameworks (MOFs) are a class of hybrid porous materials characterized by their periodic assembly using metal ions and organic ligands through coordination bonds. Their high crystallinity, extensive surface area, and adjustable pore sizes make them promising candidates for a wide array of applications. These include gas adsorption and separation, substrate binding, and catalysis, of relevance to tackling pressing global issues such as climate change, energy challenges, and pollution. In comparison to traditional porous materials such as zeolites and activated carbons, the design flexibility of organic ligands in MOFs, coupled with their orderly arrangement with associated metal centers, allows for the precise engineering of uniform pore environments. This unique feature enables a rich variety of interactions between the MOF host and adsorbed gas molecules, which are fundamental to understanding the observed uptake capacity and selectivity for target gas molecules and thus the overall performance of the material.In this Account, a data set for three-dimensional MOFs has been constructed based upon the structural analysis of host-guest interactions using the largest experimental database, the Cambridge Structural Database (CSD). A full screening was performed on structures with guest molecules of H<sub>2</sub>, C<sub>2</sub>H<sub>2</sub>, CO<sub>2</sub>, and SO<sub>2</sub>, and the relationship between the primary binding site, the isosteric heats of adsorption (<i>Q</i><sub>st</sub>), and the adsorption uptake was extracted and established. We review the methodologies to refine host-guest interactions based primarily on our studies on the host-guest chemistry of MOFs. The methods include ligand functionalization, variation of metal centers, formation of defects, addition of single atom sites, and control of pore size and structure. <i>In situ</i> structural and dynamic investigations using diffraction and spectroscopic techniques are powerful tools to visualize the details of host-guest interactions upon the above modifications, affording key insights into functional performance at a molecular level. Finally, we give an outlook of future research priorities in the study of host-guest chemistry in MOF materials. We hope this Account will encourage the rational development and improvement of future MOF-based sorbents for applications in challenging gas adsorption, separations, and catalysis. Metal-organic framework ; Adsorption ; Molecule ; Nanotechnology ; Crystallinity ; Ligand (biochemistry) ; Chemistry ; Materials science ; Crystallography ; Physical chemistry ; Organic chemistry Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications ; Crystallography and molecular interactions
Authors: Chamoni W. H. Rajawasam | Obed J. Dodo | M. A. Sachini N. Weerasinghe | Ibrahim O. Raji | Shiwanka V. Wanasinghe | Dominik Konkolewicz | Nethmi De Alwis Watuthanthrige
Source: Polymer Chemistry (article, 2023-12-19)
Field: Chemistry — Organic Chemistry

Educational series: characterizing crosslinked polymer networks Characterization of polymer networks presents unique challenges due to the insolubility of the materials, but this also enables characterization by new techniques that take advantage of the bulk network structure. Characterization (materials science) ; Polymer ; Series (stratigraphy) ; Computer science ; Polymer network ; Polymer science ; Materials science ; Nanotechnology ; Composite material ; Geology Advanced Polymer Synthesis and Characterization ; Photopolymerization techniques and applications ; Polymer composites and self-healing
Authors: Joshua Tropp | Dilara Meli | Jonathan Rivnay
Source: Matter (article, 2023-05-24)
Field: Materials Science — Polymers and Plastics

Organic mixed conductors for electrochemical transistors Bioelectronics ; Neuromorphic engineering ; Nanotechnology ; Leverage (statistics) ; Transistor ; Electronics ; Computer science ; Electrical conductor ; Organic electronics ; Materials science ; Biosensor ; Electrical engineering ; Engineering ; Artificial intelligence ; Voltage Conducting polymers and applications ; Perovskite Materials and Applications ; Advanced Sensor and Energy Harvesting Materials
Authors: Jia Chen | Yuting Wang | Yong‐Liang Yu | Jianhua Wang | Juewen Liu | Hirotaka Ihara | Hongdeng Qiu
Source: Exploration (review, 2023-05-23)
Field: Materials Science — Materials Chemistry

Composite materials based on covalent organic frameworks for multiple advanced applications Covalent organic frameworks (COFs) stand for a class of emerging crystalline porous organic materials, which are ingeniously constructed with organic units through strong covalent bonds. Their excellent design capabilities, and uniform and tunable pore structure make them potential materials for various applications. With the continuous development of synthesis technique and nanoscience, COFs have been successfully combined with a variety of functional materials to form COFs-based composites with superior performance than individual components. This paper offers an overview of the development of different types of COFs-based composites reported so far, with particular focus on the applications of COFs-based composites. Moreover, the challenges and future development prospects of COFs-based composites are presented. We anticipate that the review will provide some inspiration for the further development of COFs-based composites. Composite number ; Covalent bond ; Materials science ; Nanotechnology ; Composite material ; Chemistry ; Organic chemistry Covalent Organic Framework Applications ; Advanced Photocatalysis Techniques ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Meiirbek Islamov | Hasan Babaei | Ryther Anderson | Kutay B. Sezginel | Jeffrey R. Long | Alan J. H. McGaughey | Diego A. Gómez‐Gualdrón | Christopher E. Wilmer
Source: npj Computational Materials (article, 2023-01-20)
Field: Chemistry — Inorganic Chemistry

High-throughput screening of hypothetical metal-organic frameworks for thermal conductivity Abstract Thermal energy management in metal-organic frameworks (MOFs) is an important, yet often neglected, challenge for many adsorption-based applications such as gas storage and separations. Despite its importance, there is insufficient understanding of the structure-property relationships governing thermal transport in MOFs. To provide a data-driven perspective into these relationships, here we perform large-scale computational screening of thermal conductivity k in MOFs, leveraging classical molecular dynamics simulations and 10,194 hypothetical MOFs created using the ToBaCCo 3.0 code. We found that high thermal conductivity in MOFs is favored by high densities (&gt; 1.0 g cm −3 ), small pores (&lt; 10 Å), and four-connected metal nodes. We also found that 36 MOFs exhibit ultra-low thermal conductivity (&lt; 0.02 W m −1 K −1 ), which is primarily due to having extremely large pores (~65 Å). Furthermore, we discovered six hypothetical MOFs with very high thermal conductivity (&gt; 10 W m −1 K −1 ), the structures of which we describe in additional detail. Thermal conductivity ; Metal-organic framework ; Thermal ; Materials science ; Conductivity ; Nanotechnology ; Adsorption ; Metal ; Thermodynamics ; Chemistry ; Physical chemistry ; Physics ; Composite material Metal-Organic Frameworks: Synthesis and Applications ; Machine Learning in Materials Science ; Thermal properties of materials
Authors: Marcos Silva de Sousa | Andersen Escobar Schlogl | Felipe Ramalho Estanislau | Victor Gomes Lauriano Souza | Jane Sélia dos Reis Coimbra | Igor José Boggione Santos
Source: Coatings (article, 2023-08-11)
Field: Materials Science — Biomaterials

Nanotechnology in Packaging for Food Industry: Past, Present, and Future Nanotechnology plays a crucial role in food preservation, offering innovative solutions for food monitoring and enabling the creation of packaging with unique functional properties. The nanomaterials used in the packaging can extend the shelf life of foods, enhance food safety, keep consumers informed about contamination or food spoilage, repair packaging damage, and even release preservatives to prolong the durability of food items. Therefore, this review aims to provide an overview of the diverse applications of nanotechnology in food packaging, highlighting its key advantages. Safety considerations and regulations related to nanotechnology packaging are also addressed, along with the evaluation of potential risks to human health and the environment, emphasizing that this field faces challenges in terms of safety considerations and regulations. Additionally, the development of nanotechnology-based packaging can drive advancements in food preservation by creating safer, more sustainable, and higher-quality packaging. Thus, nanotechnology offers the potential to enhance the efficiency and functionality of packaging, delivering substantial benefits for both manufacturers and consumers. Food packaging ; Active packaging ; SAFER ; Applications of nanotechnology ; Food safety ; Impact of nanotechnology ; Risk analysis (engineering) ; Business ; Food spoilage ; Food engineering ; Nanotechnology ; Food industry ; Engineering ; Societal impact of nanotechnology ; Computer science ; Materials science ; Computer security ; Medicine ; Food science Nanocomposite Films for Food Packaging ; Microplastics and Plastic Pollution ; Nanoparticles: synthesis and applications
Authors: Dingguo Xu | Qiao Zhang | Xiangyu Huo | Yitong Wang | Mingli Yang
Source: Materials Genome Engineering Advances (article, 2023-09-01)
Field: Materials Science — Materials Chemistry

Advances in data‐assisted high‐throughput computations for material design Abstract Extensive trial and error in the variable space is the main cause of low efficiency and high cost in material development. The experimental tasks can be reduced significantly in the case that the variable space is narrowed down by reliable computer simulations. Because of their numerous variables in material design, however, the variable space is still too large to be accessed thoroughly even with a computational approach. High‐throughput computations (HTC) make it possible to complete a material screening in a large space by replacing the conventionally manual and sequential operations with automatic, robust, and concurrent streamlines. The efficiency of HTC, which is one of the pillars of materials genome engineering, has been verified in many studies, but its applications are still limited by demanding computational costs. Introduction of data mining and artificial intelligence into HTC has become an effective approach to solve the problem. In the past years, many studies have focused on the development and application of HTC and data combined approaches, which is considered as a new paradigm in computational materials science. This review focuses on the main advances in the field of data‐assisted HTC for material research and development and provides our outlook on its future development. Computer science ; Variable (mathematics) ; Computation ; Throughput ; Field (mathematics) ; Space (punctuation) ; Computer engineering ; Data science ; Algorithm Machine Learning in Materials Science ; Electron and X-Ray Spectroscopy Techniques ; Ferroelectric and Negative Capacitance Devices
Authors: Jin‐Cheng Shu | Yanlan Zhang | Yong Qin | Mao‐Sheng Cao
Source: Nano-Micro Letters (article, 2023-05-31)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Oxidative Molecular Layer Deposition Tailoring Eco-Mimetic Nanoarchitecture to Manipulate Electromagnetic Attenuation and Self-Powered Energy Conversion Abstract Advanced electromagnetic devices, as the pillars of the intelligent age, are setting off a grand transformation, redefining the structure of society to present pluralism and diversity. However, the bombardment of electromagnetic radiation on society is also increasingly serious along with the growing popularity of "Big Data". Herein, drawing wisdom and inspiration from nature, an eco-mimetic nanoarchitecture is constructed for the first time, highly integrating the advantages of multiple components and structures to exhibit excellent electromagnetic response. Its electromagnetic properties and internal energy conversion can be flexibly regulated by tailoring microstructure with oxidative molecular layer deposition (oMLD), providing a new cognition to frequency-selective microwave absorption. The optimal reflection loss reaches ≈ − 58 dB, and the absorption frequency can be shifted from high frequency to low frequency by increasing the number of oMLD cycles. Meanwhile, a novel electromagnetic absorption surface is designed to enable ultra-wideband absorption, covering almost the entire K and Ka bands. More importantly, an ingenious self-powered device is constructed using the eco-mimetic nanoarchitecture, which can convert electromagnetic radiation into electric energy for recycling. This work offers a new insight into electromagnetic protection and waste energy recycling, presenting a broad application prospect in radar stealth, information communication, aerospace engineering, etc. Electromagnetic radiation ; Materials science ; Absorption (acoustics) ; Attenuation ; Microwave ; Metamaterial ; Optoelectronics ; Computer science ; Nanotechnology ; Telecommunications ; Optics ; Composite material ; Physics Electromagnetic wave absorption materials ; Advanced Antenna and Metasurface Technologies ; Metamaterials and Metasurfaces Applications
Authors: Joshua Tropp | Caralyn P. Collins | Xinran Xie | Rachel E. Daso | Abijeet Singh Mehta | Shiv Patel | Manideep M. Reddy | Sophia E. Levin | Cheng Sun | Jonathan Rivnay
Source: Advanced Materials (article, 2023-09-08)
Field: Materials Science — Polymers and Plastics

Conducting Polymer Nanoparticles with Intrinsic Aqueous Dispersibility for Conductive Hydrogels Conductive hydrogels are promising materials with mixed ionic-electronic conduction to interface living tissue (ionic signal transmission) with medical devices (electronic signal transmission). The hydrogel form factor also uniquely bridges the wet/soft biological environment with the dry/hard environment of electronics. The synthesis of hydrogels for bioelectronics requires scalable, biocompatible fillers with high electronic conductivity and compatibility with common aqueous hydrogel formulations/resins. Despite significant advances in the processing of carbon nanomaterials, fillers that satisfy all these requirements are lacking. Herein, intrinsically dispersible acid-crystalized PEDOT:PSS nanoparticles (ncrys-PEDOT<sub>X</sub> ) are reported which are processed through a facile and scalable nonsolvent induced phase separation method from commercial PEDOT:PSS without complex instrumentation. The particles feature conductivities of up to 410 S cm<sup>-1</sup> , and when compared to other common conductive fillers, display remarkable dispersibility, enabling homogeneous incorporation at relatively high loadings within diverse aqueous biomaterial solutions without additives or surfactants. The aqueous dispersibility of the ncrys-PEDOT<sub>X</sub> particles also allows simple incorporation into resins designed for microstereolithography without sonication or surfactant optimization; complex biomedical structures with fine features (< 150 µm) are printed with up to 10% particle loading . The ncrys-PEDOT<sub>X</sub> particles overcome the challenges of traditional conductive fillers, providing a scalable, biocompatible, plug-and-play platform for soft organic bioelectronic materials. Materials science ; PEDOT:PSS ; Self-healing hydrogels ; Bioelectronics ; Conductive polymer ; Nanoparticle ; Nanotechnology ; Polymer ; Aqueous solution ; Nanomaterials ; Chemical engineering ; Composite material ; Polymer chemistry ; Biosensor ; Organic chemistry ; Chemistry Conducting polymers and applications ; Advanced Sensor and Energy Harvesting Materials ; Electrochemical sensors and biosensors
Authors: Solène Guggari | Fiona Magliozzi | Samuel Malburet | Alain Graillot | Mathias Destarac | Marc Guerre
Source: ACS Sustainable Chemistry & Engineering (article, 2023-04-03)
Field: Materials Science — Polymers and Plastics

Vanillin-Based Epoxy Vitrimers: Looking at the Cystamine Hardener from a Different Perspective Epoxy vitrimers encompass many advantages compared to traditional epoxy materials such as recyclability, repairability, and reprocessability. These properties are induced by the incorporation of dynamic reversible covalent bonds. Recently, the incorporation of aromatic disulfide bridges that are dynamic has expanded the development of new eco-friendly epoxy materials. Herein, we studied a bio-based aliphatic disulfide based on cystamine as a hardener with a vanillin-derived bio-sourced epoxy to prepare fully bio-based epoxy vitrimers. This article provides a comparative study between cystamine and an aromatic disulfide benchmark hardener issued from petrol resources. This work demonstrated that the presence of this aliphatic hardener has a significant influence not only on the reactivity, but most importantly on the resulting dynamic properties. An interesting yet counterintuitive accelerating effect of the dynamic exchanges was clearly demonstrated with only 2 to 20% of molar fraction of cystamine added to the aromatic disulfide formulation. A similar glass transition was obtained compared to the purely aromatic analogue, but relaxation times were decreased by an order of magnitude. Cystamine ; Epoxy ; Vanillin ; Covalent bond ; Chemistry ; Materials science ; Organic chemistry Polymer composites and self-healing ; Oxidative Organic Chemistry Reactions ; Porphyrin and Phthalocyanine Chemistry
Authors: Rachel K. Luu | Markus J. Buehler
Source: Advanced Science (article, 2023-12-25)
Field: Materials Science — Biomaterials

BioinspiredLLM: Conversational Large Language Model for the Mechanics of Biological and Bio‐Inspired Materials The study of biological materials and bio-inspired materials science is well established; however, surprisingly little knowledge is systematically translated to engineering solutions. To accelerate discovery and guide insights, an open-source autoregressive transformer large language model (LLM), BioinspiredLLM, is reported. The model is finetuned with a corpus of over a thousand peer-reviewed articles in the field of structural biological and bio-inspired materials and can be prompted to recall information, assist with research tasks, and function as an engine for creativity. The model has proven that it is able to accurately recall information about biological materials and is further strengthened with enhanced reasoning ability, as well as with Retrieval-Augmented Generation (RAG) to incorporate new data during generation that can also help to traceback sources, update the knowledge base, and connect knowledge domains. BioinspiredLLM also has shown to develop sound hypotheses regarding biological materials design and remarkably so for materials that have never been explicitly studied before. Lastly, the model shows impressive promise in collaborating with other generative artificial intelligence models in a workflow that can reshape the traditional materials design process. This collaborative generative artificial intelligence method can stimulate and enhance bio-inspired materials design workflows. Biological materials are at a critical intersection of multiple scientific fields and models like BioinspiredLLM help to connect knowledge domains. Computer science ; Generative grammar ; Workflow ; Field (mathematics) ; Artificial intelligence ; Data science Calcium Carbonate Crystallization and Inhibition ; Machine Learning in Materials Science ; Corrosion Behavior and Inhibition