jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Wenlong Xiang | Yueping Zhang | Yifei Chen | Changjun Liu | Xin Tu
Source: Journal of Materials Chemistry A (article, 2020-01-01)
Field: Chemistry — Inorganic Chemistry

Synthesis, characterization and application of defective metal–organic frameworks: current status and perspectives An overview of important recent advances on synthesis, characterization and application of defective metal–organic frameworks is provided. Characterization (materials science) ; Current (fluid) ; Metal-organic framework ; Nanotechnology ; Biochemical engineering ; Computer science ; Materials science ; Engineering ; Chemistry ; Organic chemistry ; Electrical engineering Metal-Organic Frameworks: Synthesis and Applications ; Lanthanide and Transition Metal Complexes ; Advanced Nanomaterials in Catalysis
Authors: Chun‐Teh Chen | Grace X. Gu
Source: Advanced Science (article, 2020-01-09)
Field: Materials Science — Materials Chemistry

Generative Deep Neural Networks for Inverse Materials Design Using Backpropagation and Active Learning In recent years, machine learning (ML) techniques are seen to be promising tools to discover and design novel materials. However, the lack of robust inverse design approaches to identify promising candidate materials without exploring the entire design space causes a fundamental bottleneck. A general-purpose inverse design approach is presented using generative inverse design networks. This ML-based inverse design approach uses backpropagation to calculate the analytical gradients of an objective function with respect to design variables. This inverse design approach is capable of overcoming local minima traps by using backpropagation to provide rapid calculations of gradient information and running millions of optimizations with different initial values. Furthermore, an active learning strategy is adopted in the inverse design approach to improve the performance of candidate materials and reduce the amount of training data needed to do so. Compared to passive learning, the active learning strategy is capable of generating better designs and reducing the amount of training data by at least an order-of-magnitude in the case study on composite materials. The inverse design approach is compared with conventional gradient-based topology optimization and gradient-free genetic algorithms and the pros and cons of each method are discussed when applied to materials discovery and design problems. Backpropagation ; Computer science ; Inverse ; Maxima and minima ; Artificial neural network ; Bottleneck ; Generative Design ; Artificial intelligence ; Machine learning ; Inverse problem ; Mathematics ; Engineering Machine Learning in Materials Science ; Topology Optimization in Engineering
Authors: Xiang Gao | Farhad Ramezanghorbani | Olexandr Isayev | Justin S. Smith | Adrián E. Roitberg
Source: Journal of Chemical Information and Modeling (article, 2020-06-22)
Field: Materials Science — Materials Chemistry

TorchANI: A Free and Open Source PyTorch-Based Deep Learning Implementation of the ANI Neural Network Potentials This paper presents TorchANI, a PyTorch-based program for training/inference of ANI (ANAKIN-ME) deep learning models to obtain potential energy surfaces and other physical properties of molecular systems. ANI is an accurate neural network potential originally implemented using C++/CUDA in a program called NeuroChem. Compared with NeuroChem, TorchANI has a design emphasis on being lightweight, user friendly, cross platform, and easy to read and modify for fast prototyping, while allowing acceptable sacrifice on running performance. Because the computation of atomic environmental vectors and atomic neural networks are all implemented using PyTorch operators, TorchANI is able to use PyTorch's autograd engine to automatically compute analytical forces and Hessian matrices, as well as do force training without requiring any additional codes. TorchANI is open-source and freely available on GitHub: https://github.com/aiqm/torchani. Computer science ; Deep learning ; Hessian matrix ; Artificial neural network ; Artificial intelligence ; Inference ; Computation ; Source code ; Deep neural networks ; Machine learning ; Computational science ; Computer architecture ; Computer engineering ; Programming language Machine Learning in Materials Science ; Fuel Cells and Related Materials ; Computational Drug Discovery Methods
Authors: Yunwei Mao | Qi He | Xuanhe Zhao
Source: Science Advances (article, 2020-04-24)
Field: Materials Science — Materials Chemistry

Designing complex architectured materials with generative adversarial networks Architectured materials on length scales from nanometers to meters are desirable for diverse applications. Recent advances in additive manufacturing have made mass production of complex architectured materials technologically and economically feasible. Existing architecture design approaches such as bioinspiration, Edisonian, and optimization, however, generally rely on experienced designers' prior knowledge, limiting broad applications of architectured materials. Particularly challenging is designing architectured materials with extreme properties, such as the Hashin-Shtrikman upper bounds on isotropic elasticity in an experience-free manner without prior knowledge. Here, we present an experience-free and systematic approach for the design of complex architectured materials with generative adversarial networks. The networks are trained using simulation data from millions of randomly generated architectures categorized based on different crystallographic symmetries. We demonstrate modeling and experimental results of more than 400 two-dimensional architectures that approach the Hashin-Shtrikman upper bounds on isotropic elastic stiffness with porosities from 0.05 to 0.75. Limiting ; Isotropy ; Generative grammar ; Adversarial system ; Stiffness ; Materials science ; Nanotechnology ; Computer science ; Mechanical engineering ; Artificial intelligence ; Composite material ; Engineering ; Physics Machine Learning in Materials Science ; Cellular and Composite Structures ; Block Copolymer Self-Assembly
Authors: Wen Yang | Lin Wang | Evan M. Mettenbrink | Paul L. DeAngelis | Stefan Wilhelm
Source: The Annual Review of Pharmacology and Toxicology (review, 2020-08-25)
Field: Materials Science — Materials Chemistry

Nanoparticle Toxicology Nanoparticles from natural and anthropogenic sources are abundant in the environment, thus human exposure to nanoparticles is inevitable. Due to this constant exposure, it is critically important to understand the potential acute and chronic adverse effects that nanoparticles may cause to humans. In this review, we explore and highlight the current state of nanotoxicology research with a focus on mechanistic understanding of nanoparticle toxicity at organ, tissue, cell, and biomolecular levels. We discuss nanotoxicity mechanisms, including generation of reactive oxygen species, nanoparticle disintegration, modulation of cell signaling pathways, protein corona formation, and poly(ethylene glycol)-mediated immunogenicity. We conclude with a perspective on potential approaches to advance current understanding of nanoparticle toxicity. Such improved understanding may lead to mitigation strategies that could enable safe application of nanoparticles in humans. Advances in nanotoxicity research will ultimately inform efforts to establish standardized regulatory frameworks with the goal of fully exploiting the potential of nanotechnology while minimizing harm to humans. Nanotoxicology ; Nanotechnology ; Nanoparticle ; Chemistry ; Materials science Nanoparticles: synthesis and applications ; Air Quality and Health Impacts ; Healthcare and Environmental Waste Management
Authors: Zubair Ahmed Ratan | Mohammad Faisal Haidere | Md Nurunnabi | Sadi Shahriar | A. J. Saleh Ahammad | Youn Young Shim | Martin J. T. Reaney | Jae Youl Cho
Source: Cancers (review, 2020-04-01)
Field: Materials Science — Materials Chemistry

Green Chemistry Synthesis of Silver Nanoparticles and Their Potential Anticancer Effects Nanobiotechnology has grown rapidly and become an integral part of modern disease diagnosis and treatment. Biosynthesized silver nanoparticles (AgNPs) are a class of eco-friendly, cost-effective and biocompatible agents that have attracted attention for their possible biomedical and bioengineering applications. Like many other inorganic and organic nanoparticles, such as AuNPs, iron oxide and quantum dots, AgNPs have also been widely studied as components of advanced anticancer agents in order to better manage cancer in the clinic. AgNPs are typically produced by the action of reducing reagents on silver ions. In addition to numerous laboratory-based methods for reduction of silver ions, living organisms and natural products can be effective and superior source for synthesis of AgNPs precursors. Currently, plants, bacteria and fungi can afford biogenic AgNPs precursors with diverse geometries and surface properties. In this review, we summarized the recent progress and achievements in biogenic AgNPs synthesis and their potential uses as anticancer agents. Silver nanoparticle ; Nanotechnology ; Nanobiotechnology ; Chemistry ; Biocompatible material ; Nanoparticle ; Materials science Nanoparticles: synthesis and applications ; Graphene and Nanomaterials Applications ; Nanoparticle-Based Drug Delivery
Authors: Jiaqi Cheng | Conghua Zhan | Jiahui Wu | Zhixiang Cui | Junhui Si | Qianting Wang | Xiangfang Peng | Lih‐Sheng Turng
Source: ACS Omega (article, 2020-03-02)
Field: Materials Science — Biomaterials

Highly Efficient Removal of Methylene Blue Dye from an Aqueous Solution Using Cellulose Acetate Nanofibrous Membranes Modified by Polydopamine A new type of deacetylated cellulose acetate (DA)@polydopamine (PDA) composite nanofiber membrane was fabricated by electrospinning and surface modification. The membrane was applied as a highly efficient adsorbent for removing methylene blue (MB) from an aqueous solution. The morphology, surface chemistry, surface wettability, and effects of operating conditions on MB adsorption ability, as well as the equilibrium, kinetics, thermodynamics, and mechanism of adsorption, were systematically studied. The results demonstrated that a uniform PDA coating layer was successfully developed on the surface of DA nanofibers. The adsorption capacity of the DA@PDA nanofiber membrane reached up to 88.2 mg/g at a temperature of 25 °C and a pH of 6.5 after adsorption for 30 h, which is about 8.6 times higher than that of DA nanofibers. The experimental results showed that the adsorption behavior of DA@PDA composite nanofibers followed the Weber's intraparticle diffusion model, pseudo-second-order model, and Langmuir isothermal model. A thermodynamic analysis indicated that endothermic, spontaneous, and physisorption processes occurred. Based on the experimental results, the adsorption mechanism of DA@PDA composite nanofibers was also demonstrated. Nanofiber ; Adsorption ; Cellulose acetate ; Chemical engineering ; Electrospinning ; Membrane ; Aqueous solution ; Materials science ; Langmuir adsorption model ; Polymer chemistry ; Chemistry ; Cellulose ; Organic chemistry ; Composite material ; Polymer Electrospun Nanofibers in Biomedical Applications ; Adsorption and biosorption for pollutant removal ; Nanomaterials for catalytic reactions
Authors: Qiang Zhang | Jihong Yu | Avelino Corma
Source: Advanced Materials (review, 2020-07-22)
Field: Chemistry — Inorganic Chemistry

Applications of Zeolites to C1 Chemistry: Recent Advances, Challenges, and Opportunities C1 chemistry, which is the catalytic transformation of C1 molecules including CO, CO<sub>2</sub> , CH<sub>4</sub> , CH<sub>3</sub> OH, and HCOOH, plays an important role in providing energy and chemical supplies while meeting environmental requirements. Zeolites are highly efficient solid catalysts used in the chemical industry. The design and development of zeolite-based mono-, bi-, and multifunctional catalysts has led to a booming application of zeolite-based catalysts to C1 chemistry. Combining the advantages of zeolites and metallic catalytic species has promoted the catalytic production of various hydrocarbons (e.g., methane, light olefins, aromatics, and liquid fuels) and oxygenates (e.g., methanol, dimethyl ether, formic acid, and higher alcohols) from C1 molecules. The key zeolite descriptors that influence catalytic performance, such as framework topologies, nanoconfinement effects, Brønsted acidities, secondary-pore systems, particle sizes, extraframework cations and atoms, hydrophobicity and hydrophilicity, and proximity between acid and metallic sites are discussed to provide a deep understanding of the significance of zeolites to C1 chemistry. An outlook regarding challenges and opportunities for the conversion of C1 resources using zeolite-based catalysts to meet emerging energy and environmental demands is also presented. Zeolite ; Catalysis ; Oxygenate ; Methanol ; Formic acid ; Dimethyl ether ; Molecule ; Materials science ; Methane ; Organic chemistry ; Clean energy ; Chemical engineering ; Chemistry ; Nanotechnology Zeolite Catalysis and Synthesis ; Metal-Organic Frameworks: Synthesis and Applications ; Ammonia Synthesis and Nitrogen Reduction
Authors: Andrew Macklin | Shahbaz Khan | Thomas Kislinger
Source: Clinical Proteomics (review, 2020-05-24)
Field: Chemistry — Spectroscopy

Recent advances in mass spectrometry based clinical proteomics: applications to cancer research Cancer biomarkers have transformed current practices in the oncology clinic. Continued discovery and validation are crucial for improving early diagnosis, risk stratification, and monitoring patient response to treatment. Profiling of the tumour genome and transcriptome are now established tools for the discovery of novel biomarkers, but alterations in proteome expression are more likely to reflect changes in tumour pathophysiology. In the past, clinical diagnostics have strongly relied on antibody-based detection strategies, but these methods carry certain limitations. Mass spectrometry (MS) is a powerful method that enables increasingly comprehensive insights into changes of the proteome to advance personalized medicine. In this review, recent improvements in MS-based clinical proteomics are highlighted with a focus on oncology. We will provide a detailed overview of clinically relevant samples types, as well as, consideration for sample preparation methods, protein quantitation strategies, MS configurations, and data analysis pipelines currently available to researchers. Critical consideration of each step is necessary to address the pressing clinical questions that advance cancer patient diagnosis and prognosis. While the majority of studies focus on the discovery of clinically-relevant biomarkers, there is a growing demand for rigorous biomarker validation. These studies focus on high-throughput targeted MS assays and multi-centre studies with standardized protocols. Additionally, improvements in MS sensitivity are opening the door to new classes of tumour-specific proteoforms including post-translational modifications and variants originating from genomic aberrations. Overlaying proteomic data to complement genomic and transcriptomic datasets forges the growing field of proteogenomics, which shows great potential to improve our understanding of cancer biology. Overall, these advancements not only solidify MS-based clinical proteomics' integral position in cancer research, but also accelerate the shift towards becoming a regular component of routine analysis and clinical practice. Biomarker discovery ; Proteogenomics ; Proteomics ; Computational biology ; Proteome ; Precision medicine ; Cancer biomarkers ; Personalized medicine ; Bioinformatics ; Biomarker ; Translational research ; Medicine ; Genomics ; Data science ; Computer science ; Cancer ; Biology ; Genome ; Pathology ; Internal medicine Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Cancer Genomics and Diagnostics
Authors: Ahmad Almatroudi
Source: Open Life Sciences (review, 2020-11-19)
Field: Materials Science — Materials Chemistry

Silver nanoparticles: synthesis, characterisation and biomedical applications Nanotechnology is a rapidly growing field due to its unique functionality and a wide range of applications. Nanomedicine explores the possibilities of applying the knowledge and tools of nanotechnology for the prevention, treatment, diagnosis and control of disease. In this regard, silver nanoparticles with diameters ranging from 1 to 100 nm are considered most important due to their unique properties, ability to form diverse nanostructures, their extraordinary range of bactericidal and anticancer properties, wound healing and other therapeutic abilities and their cost-effectiveness in production. The current paper reviews various types of physical, chemical and biological methods used in the production of silver nanoparticles. It also describes approaches employing silver nanoparticles as antimicrobial and antibiofilm agents, as antitumour agents, in dentistry and dental implants, as promoters of bone healing, in cardiovascular implants and as promoters of wound healing. The paper also explores the mechanism of action, synthesis methods and morphological characterisation of silver nanoparticles to examine their role in medical treatments and disease management. Nanomedicine ; Nanotechnology ; Silver nanoparticle ; Materials science ; Nanoparticle Nanoparticles: synthesis and applications ; Graphene and Nanomaterials Applications ; Laser-Ablation Synthesis of Nanoparticles
Authors: Ligang Sun | Ge Wu | Qiang Wang | Jian Lü
Source: Materials Today (article, 2020-05-26)
Field: Materials Science — Materials Chemistry

Nanostructural metallic materials: Structures and mechanical properties The trade-off of strength and ductility of metals has long plagued materials scientists. To resolve this issue, great efforts have been devoted over the past decades to developing a variety of technological pathways for effectively tailoring the microstructure of metallic materials. Here, we review the recent advanced nanostructure design strategies for purposely fabricating heterogeneous nanostructures in crystalline and non-crystalline metallic materials. Several representative structural approaches are introduced, including (1) hierarchical nanotwinned (HNT) structures, extreme grain refinement and dislocation architectures etc. for crystalline metals; (2) nanoglass structure for non-crystalline alloys, i.e. metallic glasses (MGs); and (3) a series of supra-nano-dual-phase (SNDP) nanostructures for composite alloys. The mechanical properties are further optimized by manipulating these nanostructures, especially coupling multiple advanced nanostructures into one material. Particularly, the newly developed SNDP nanostructures greatly enrich the nanostructure design strategies by utilizing supra-nano sized crystals and MGs, which exhibit unique size and synergistic effects. The origins of these gratifying properties are discussed in this review. Furthermore, based on a comprehensive understanding of microscopic mechanisms, a broad vision of strategies towards high strength and high ductility are proposed to promote future innovations. Nanostructure ; Materials science ; Ductility (Earth science) ; Nanotechnology ; Microstructure ; Structural material ; Characterization (materials science) ; Composite material ; Creep Microstructure and mechanical properties ; Metallic Glasses and Amorphous Alloys ; nanoparticles nucleation surface interactions
Authors: Shi Su | Peter M. Kang
Source: Nanomaterials (review, 2020-04-01)
Field: Materials Science — Biomaterials

Systemic Review of Biodegradable Nanomaterials in Nanomedicine While each biodegradable nanomaterial has its advantages and disadvantages, with careful design and functionalization, biodegradable nanoparticles hold great future in nanomedicine. Nanomedicine ; Nanotechnology ; Nanomaterials ; Materials science ; Nanoparticle Nanoparticle-Based Drug Delivery ; Graphene and Nanomaterials Applications ; Nanoparticles: synthesis and applications
Authors: Long Kong | Cheng Tang | Hong‐Jie Peng | Jia‐Qi Huang | Qiang Zhang
Source: SmartMat (review, 2020-11-08)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Advanced energy materials for flexible batteries in energy storage: A review Abstract Smart energy storage has revolutionized portable electronics and electrical vehicles. The current smart energy storage devices have penetrated into flexible electronic markets at an unprecedented rate. Flexible batteries are key power sources to enable vast flexible devices, which put forward additional requirements, such as bendable, twistable, stretchable, and ultrathin, to adapt mechanical deformation under the working conditions. This review summarizes the recent advances in construction and configuration of flexible batteries and discusses the general metrics to benchmark various flexible batteries with different materials and chemistries. Moreover, we present advanced prototype flexible batteries developed by some companies to afford general envision of the technological status. Lastly, the critical points are summarized in the development of flexible batteries and remaining challenges are also presented for the future design of flexible batteries in practical perspectives. Energy storage ; Electronics ; Key (lock) ; Benchmark (surveying) ; Computer science ; Engineering ; Systems engineering ; Electrical engineering ; Power (physics) ; Computer security Supercapacitor Materials and Fabrication ; Advanced Battery Materials and Technologies ; Advanced battery technologies research
Authors: Yan Yang | Hua Deng | Qiang Fu
Source: Materials Chemistry Frontiers (article, 2020-01-01)
Field: Materials Science — Polymers and Plastics

Recent progress on PEDOT:PSS based polymer blends and composites for flexible electronics and thermoelectric devices Recent progress on PEDOT:PSS composites by incorporating various polymers and fillers through blending and mixing methods and main focus is put onto the electrical conductivity, stretchability and thermoelectric properties. PEDOT:PSS ; Materials science ; Electronics ; Thermoelectric effect ; Composite material ; Polymer ; Conductive polymer ; Flexible electronics ; Nanotechnology ; Electrical engineering ; Engineering Conducting polymers and applications ; Advanced Thermoelectric Materials and Devices ; Advanced Sensor and Energy Harvesting Materials