jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Mohammad Kiarashi | Parham Mahamed | Nader Ghotbi | Azadeh Tadayonfard | Kamyar Nasiri | Parisa Kazemi | Ashkan Badkoobeh | Saman Yasamineh | Ali Joudaki
Source: Journal of Nanobiotechnology (article, 2024-01-05)
Field: Materials Science — Materials Chemistry

Spotlight on therapeutic efficiency of green synthesis metals and their oxide nanoparticles in periodontitis Periodontitis, one of the most prevalent dental diseases, causes the loss of bone and gum tissue that hold teeth in place. Several bacteria, commonly present in clinically healthy oral cavities, may induce and perpetuate periodontitis when their concentration rises in the gingival sulcus. Antibacterial effect against various Gram-negative and Gram-positive bacteria, including pathogenic and drug-resistant ones, has been shown for several distinct transient metal and metal oxide NPs. Therefore, NPs may be used in biomedicine to treat periodontal problems and in nanotechnology to inhibit the development of microorganisms. Instead of using harmful chemicals or energy-intensive machinery, biosynthesis of metal and metal oxide nanoparticles (NPs) has been suggested. To produce metal and metal oxide NPs, the ideal technique is "Green" synthesis because of its low toxicity and safety for human health and the environment. Gold NPs (AuNPs) appear to be less toxic to mammalian cells than other nanometals because their antibacterial activity is not dependent on reactive oxygen species (ROS). AgNPs also possess chemical stability, catalytic activity, and superior electrical and thermal conductivity, to name a few of their other advantageous characteristics. It was observed that zinc oxide (ZnO) NPs and copper (Cu) NPs exhibited discernible inhibitory effects against gram-positive and gram-negative bacterial strains, respectively. ZnO NPs demonstrated bactericidal activity against the microorganisms responsible for periodontitis. Medications containing magnetic NPs are highly effective against multidrug-resistant bacterial and fungal infections. The titanium dioxide (TiO<sub>2</sub>) NPs are implicated in elevating salivary peroxidase activity in individuals diagnosed with chronic periodontitis. Furthermore, specific metallic NPs have the potential to enhance the antimicrobial efficacy of periodontitis treatments when combined. Therefore, these NPs, as well as their oxide NPs, are only some of the metals and metal oxides that have been synthesized in environmentally friendly ways and shown to have therapeutic benefits against periodontitis. Periodontitis ; Chemistry ; Bacteria ; Antibacterial activity ; Metal ; Antimicrobial ; Reactive oxygen species ; Microbiology ; Biochemistry ; Medicine ; Dentistry ; Biology ; Organic chemistry Nanoparticles: synthesis and applications ; Advanced Nanomaterials in Catalysis ; Anesthesia and Neurotoxicity Research
Authors: Mehmet Şükrü Adin | Hamit Adın
Source: Polymers (article, 2024-11-27)
Field: Materials Science — Materials Chemistry

Machining Eco-Friendly Jute Fiber-Reinforced Epoxy Composites Using Specially Produced Cryo-Treated and Untreated Cutting Tools In recent years, consumers have become increasingly interested in natural, biodegradable and eco-friendly composites. Eco-friendly composites manufactured using natural reinforcing filling materials stand out with properties such as cost effectiveness and easy accessibility. For these reasons, in this research, a composite workpiece was specially manufactured using eco-friendly jute fibers. Two cost-effective cutting tools were specially produced to ensure high-quality machining of this composite workpiece. One of these specially manufactured cutting tools was subjected to DC&T (deep cryogenic treatment and tempering) processes to improve its performance. At the end of the research, when the lowest and highest Fd (delamination factor) values obtained with DC&T-T1 and T1 cutting tools were compared, it was observed that 5.49% and 6.23% better results were obtained with the DC&T-T1 cutting tool, respectively. From the analysis of the S/N (signal-to-noise) ratios obtained using Fd values, it was found that the most appropriate machining parameters for the composite workpiece used in this investigation were the DC&T-T1 cutting tool, a 2000 rev/min spindle speed and a 100 mm/min feed rate. Through ANOVAs (analyses of variance), it was discovered that the most significant parameter having an impact on the Fd values was the spindle speed, with a rate of 53.01%. Considering the lowest and highest Ra (average surface roughness) values obtained using DC&T-T1 and T1 cutting tools, it was seen that 19.42% and 16.91% better results were obtained using the DC&T-T1 cutting tool, respectively. In the S/N ratio analysis results obtained using Ra values, it was revealed that the most appropriate machining parameters for the composite workpiece used in this investigation were the DC&T-T1 cutting tool, a 2000 rev/min spindle speed and a 100 mm/min feed rate. In the ANOVAs, it was revealed that the most significant parameter having an effect on the Ra values was the feed rate at 37.86%. Epoxy ; Composite material ; Materials science ; Environmentally friendly ; Machining ; Fiber ; Fiber-reinforced composite ; Metallurgy Metal Alloys Wear and Properties ; Advanced machining processes and optimization ; Tribology and Wear Analysis
Authors: Juan Zhang | Zhihua Wang | Xingen Lin | Xiaoping Gao | Qiuping Wang | Rui Huang | Yaner Ruan | Haonan Xu | Lin Tian | Ling Chen | Ran Shi | Suowen Xu | Kong Chen | Yuen Wu
Source: Angewandte Chemie International Edition (article, 2024-09-27)
Field: Materials Science — Materials Chemistry

Mn−Ce Symbiosis: Nanozymes with Multiple Active Sites Facilitate Scavenging of Reactive Oxygen Species (ROS) Based on Electron Transfer and Confinement Anchoring Regulating appropriate valence states of metal active centers, such as Ce<sup>3+</sup>/Ce<sup>4+</sup> and Mn<sup>3+</sup>/Mn<sup>2+</sup>, as well as surface vacancy defects, is crucial for enhancing the catalytic activity of cerium-based and manganese-based nanozymes. Drawing inspiration from the efficient substance exchange in rhizobia-colonized root cells of legumes, we developed a symbiosis nanozyme system with rhizobia-like CeO<sub>x</sub> nanoclusters robustly anchored onto root-like Mn<sub>3</sub>O<sub>4</sub> nanosupports (CeO<sub>x</sub>/Mn<sub>3</sub>O<sub>4</sub>). The process of "substance exchange" between Ce and Mn atoms-reminiscent of electron transfer-not only fine-tunes the metal active sites to achieve optimal Ce<sup>3+</sup>/Ce<sup>4+</sup> and Mn<sup>3+</sup>/Mn<sup>2+</sup> ratios but also enhances the vacancy ratio through interface defect engineering. Additionally, the confinement anchoring of CeO<sub>x</sub> on Mn<sub>3</sub>O<sub>4</sub> ensures efficient electron transfer in catalytic reactions. The final CeO<sub>x</sub>/Mn<sub>3</sub>O<sub>4</sub> nanozyme demonstrates potent catalase-like (CAT-like) and superoxide dismutase-like (SOD-like) activities, excelling in both chemical settings and cellular environments with high reactive oxygen species (ROS) levels. This research not only unveils a novel material adept at effectively eliminating ROS but also presents an innovative approach for amplifying the efficacy of nanozymes. Reactive oxygen species ; Electron transfer ; Cerium ; Catalysis ; Chemistry ; Rhizobia ; Oxygen ; Catalase ; Nanotechnology ; Photochemistry ; Biophysics ; Materials science ; Antioxidant ; Inorganic chemistry ; Biochemistry ; Nitrogen fixation Advanced Nanomaterials in Catalysis ; Nanoparticles: synthesis and applications ; Nanocluster Synthesis and Applications
Authors: Ziting Zhu | Hsinhan Tsai | Surya T. Parker | Jung‐Hoon Lee | Yuto Yabuuchi | Henry Z. H. Jiang | Yang Wang | Shuoyan Xiong | Alexander C. Forse | Bhavish Dinakar | Adrian Huang | Chaochao Dun | Phillip J. Milner | Alex Smith | Pedro Guimarães Martins | Katie R. Meihaus | Jeffrey J. Urban | Jeffrey A. Reimer | Jeffrey B. Neaton | Jeffrey R. Long
Source: Journal of the American Chemical Society (article, 2024-02-24)
Field: Chemistry — Inorganic Chemistry

High-Capacity, Cooperative CO<sub>2</sub> Capture in a Diamine-Appended Metal–Organic Framework through a Combined Chemisorptive and Physisorptive Mechanism Diamine-appended Mg<sub>2</sub>(dobpdc) (dobpdc<sup>4-</sup> = 4,4'-dioxidobiphenyl-3,3'-dicarboxylate) metal-organic frameworks are promising candidates for carbon capture that exhibit exceptional selectivities and high capacities for CO<sub>2</sub>. To date, CO<sub>2</sub> uptake in these materials has been shown to occur predominantly via a chemisorption mechanism involving CO<sub>2</sub> insertion at the amine-appended metal sites, a mechanism that limits the capacity of the material to ∼1 equiv of CO<sub>2</sub> per diamine. Herein, we report a new framework, pip2-Mg<sub>2</sub>(dobpdc) (pip2 = 1-(2-aminoethyl)piperidine), that exhibits two-step CO<sub>2</sub> uptake and achieves an unusually high CO<sub>2</sub> capacity approaching 1.5 CO<sub>2</sub> per diamine at saturation. Analysis of variable-pressure CO<sub>2</sub> uptake in the material using solid-state nuclear magnetic resonance (NMR) spectroscopy and <i>in situ</i> diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) reveals that pip2-Mg<sub>2</sub>(dobpdc) captures CO<sub>2</sub> via an unprecedented mechanism involving the initial insertion of CO<sub>2</sub> to form ammonium carbamate chains at half of the sites in the material, followed by tandem cooperative chemisorption and physisorption. Powder X-ray diffraction analysis, supported by van der Waals-corrected density functional theory, reveals that physisorbed CO<sub>2</sub> occupies a pocket formed by adjacent ammonium carbamate chains and the linker. Based on breakthrough and extended cycling experiments, pip2-Mg<sub>2</sub>(dobpdc) exhibits exceptional performance for CO<sub>2</sub> capture under conditions relevant to the separation of CO<sub>2</sub> from landfill gas. More broadly, these results highlight new opportunities for the fundamental design of diamine-Mg<sub>2</sub>(dobpdc) materials with even higher capacities than those predicted based on CO<sub>2</sub> chemisorption alone. Chemistry ; Physisorption ; Chemisorption ; Diamine ; Carbamic acid ; Ethylamine ; van der Waals force ; Metal-organic framework ; Piperidine ; Fourier transform infrared spectroscopy ; Physical chemistry ; Chemical engineering ; Organic chemistry ; Molecule ; Adsorption Metal-Organic Frameworks: Synthesis and Applications ; Carbon Dioxide Capture Technologies ; Covalent Organic Framework Applications
Authors: Pengfei Dong | Xinyu Xu | Taikang Wu | Rengan Luo | Weisu Kong | Zhiyuan Xu | Shuai Yuan | Jun Zhou | Jianping Lei
Source: Angewandte Chemie International Edition (article, 2024-05-13)
Field: Materials Science — Materials Chemistry

Stepwise Protonation of Three‐Dimensional Covalent Organic Frameworks for Enhancing Hydrogen Peroxide Photosynthesis Three-dimensional covalent organic frameworks (3D COFs), recognized for their tailorable structures and accessible active sites, offer a promising platform for developing advanced photocatalysts. However, the difficulty in the synthesis and functionalization of 3D COFs hinders their further development. In this study, we present a series of 3D-bcu-COFs with 8 connected porphyrin units linked by linear linkers through imine bonds as a versatile platform for photocatalyst design. The photoresponse of 3D-bcu-COFs was initially modulated by functionalizing linear linkers with benzo-thiadiazole or benzo-selenadiazole groups. Furthermore, taking advantage of the well-exposed porphyrin and imine sites in 3D-bcu-COFs, their photocatalytic activity was optimized by stepwise protonation of imine bonds and porphyrin centers. The dual protonated COF with benzo-selenadiazole groups exhibited enhanced charge separation, leading to an increased photocatalytic H<sub>2</sub>O<sub>2</sub> production under visible light. This enhancement demonstrates the combined benefits of linker functionalization and stepwise protonation on photocatalytic efficiency. Protonation ; Hydrogen peroxide ; Photosynthesis ; Chemistry ; Covalent bond ; Photochemistry ; Organic chemistry ; Biochemistry Covalent Organic Framework Applications ; Advanced Photocatalysis Techniques ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Jikai Sun | Rui Tu | Yuchun Xu | Hongyan Yang | Tie Yu | Dong Zhai | Xiuqin Ci | Wei Deng
Source: Nature Communications (article, 2024-07-17)
Field: Materials Science — Materials Chemistry

Machine learning aided design of single-atom alloy catalysts for methane cracking The process of CH<sub>4</sub> cracking into H<sub>2</sub> and carbon has gained wide attention for hydrogen production. However, traditional catalysis methods suffer rapid deactivation due to severe carbon deposition. In this study, we discover that effective CH<sub>4</sub> cracking can be achieved at 450 °C over a Re/Ni single-atom alloy via ball milling. To explore single-atom alloy catalysis, we construct a library of 10,950 transition metal single-atom alloy surfaces and screen candidates based on C-H dissociation energy barriers predicted by a machine learning model. Experimental validation identifies Ir/Ni and Re/Ni as top performers. Notably, the non-noble metal Re/Ni achieves a hydrogen yield of 10.7 gH<sub>2</sub> gcat<sup>-1</sup> h<sup>-1</sup> with 99.9% selectivity and 7.75% CH<sub>4</sub> conversion at 450 °C, 1 atm. Here, we show the mechanical energy boosts CH<sub>4</sub> conversion clearly and sustained CH<sub>4</sub> cracking over 240 h is achieved, significantly surpassing other approaches in the literature. Cracking ; Alloy ; Catalysis ; Materials science ; Dissociation (chemistry) ; Hydrogen ; Selectivity ; Methane ; Chemical engineering ; Atom (system on chip) ; Fluid catalytic cracking ; Nanotechnology ; Metallurgy ; Chemistry ; Physical chemistry ; Composite material ; Computer science ; Organic chemistry Catalytic Processes in Materials Science ; Electrocatalysts for Energy Conversion ; Machine Learning in Materials Science
Authors: Duo Zhang | Hangrui Bi | Fu‐Zhi Dai | Wanrun Jiang | Xinzijian Liu | Linfeng Zhang | Handong Wang
Source: npj Computational Materials (article, 2024-05-07)
Field: Materials Science — Materials Chemistry

Pretraining of attention-based deep learning potential model for molecular simulation Abstract Machine learning-assisted modeling of the inter-atomic potential energy surface (PES) is revolutionizing the field of molecular simulation. With the accumulation of high-quality electronic structure data, a model that can be pretrained on all available data and finetuned on downstream tasks with a small additional effort would bring the field to a new stage. Here we propose DPA-1, a Deep Potential model with a gated attention mechanism, which is highly effective for representing the conformation and chemical spaces of atomic systems and learning the PES. We tested DPA-1 on a number of systems and observed superior performance compared with existing benchmarks. When pretrained on large-scale datasets containing 56 elements, DPA-1 can be successfully applied to various downstream tasks with a great improvement of sample efficiency. Surprisingly, for different elements, the learned type embedding parameters form a s p i r a l in the latent space and have a natural correspondence with their positions on the periodic table, showing interesting interpretability of the pretrained DPA-1 model. Computer science ; Deep learning ; Psychology ; Artificial intelligence ; Cognitive psychology Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: Dongdong Xu | Yang Li | Shouchun Yin | Feihe Huang
Source: Chemical Society Reviews (review, 2024-01-01)
Field: Materials Science — Biomaterials

Strategies to address key challenges of metallacycle/metallacage-based supramolecular coordination complexes in biomedical applications Owing to their capacity for dynamically linking two or more functional molecules, supramolecular coordination complexes (SCCs), exemplified by two-dimensional (2D) metallacycles and three-dimensional (3D) metallacages, have gained increasing significance in biomedical applications. However, their inherent hydrophobicity and self-assembly driven by heavy metal ions present common challenges in their applications. These challenges can be overcome by enhancing the aqueous solubility and <i>in vivo</i> circulation stability of SCCs, alongside minimizing their side effects during treatment. Addressing these challenges is crucial for advancing the fundamental research of SCCs and their subsequent clinical translation. In this review, drawing on extensive contemporary research, we offer a thorough and systematic analysis of the strategies employed by SCCs to surmount these prevalent yet pivotal obstacles. Additionally, we explore further potential challenges and prospects for the broader application of SCCs in the biomedical field. Metallacycle ; Supramolecular chemistry ; Key (lock) ; Nanotechnology ; Solubility ; Coordination complex ; Chemistry ; Combinatorial chemistry ; Computer science ; Metal ; Materials science ; Physics ; Molecule ; Organic chemistry Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Jie Xue | Dan Liŭ | Da Li | Tianzeng Hong | Chuanbing Li | Zifu Zhu | Yuxuan Sun | Xiaobo Gao | Lei Guo | Xi Shen | Peng‐Cheng Ma | Qingbin Zheng
Source: Advanced Materials (review, 2024-03-16)
Field: Materials Science — Electronic, Optical and Magnetic Materials

New Carbon Materials for Multifunctional Soft Electronics Soft electronics are garnering significant attention due to their wide-ranging applications in artificial skin, health monitoring, human-machine interaction, artificial intelligence, and the Internet of Things. Various soft physical sensors such as mechanical sensors, temperature sensors, and humidity sensors are the fundamental building blocks for soft electronics. While the fast growth and widespread utilization of electronic devices have elevated life quality, the consequential electromagnetic interference (EMI) and radiation pose potential threats to device precision and human health. Another substantial concern pertains to overheating issues that occur during prolonged operation. Therefore, the design of multifunctional soft electronics exhibiting excellent capabilities in sensing, EMI shielding, and thermal management is of paramount importance. Because of the prominent advantages in chemical stability, electrical and thermal conductivity, and easy functionalization, new carbon materials including carbon nanotubes, graphene and its derivatives, graphdiyne, and sustainable natural-biomass-derived carbon are particularly promising candidates for multifunctional soft electronics. This review summarizes the latest advancements in multifunctional soft electronics based on new carbon materials across a range of performance aspects, mainly focusing on the structure or composite design, and fabrication method on the physical signals monitoring, EMI shielding, and thermal management. Furthermore, the device integration strategies and corresponding intriguing applications are highlighted. Finally, this review presents prospects aimed at overcoming current barriers and advancing the development of state-of-the-art multifunctional soft electronics. Electronics ; Materials science ; Nanotechnology ; Graphene ; Flexible electronics ; Carbon nanotube ; Electrical engineering ; Engineering Electromagnetic wave absorption materials ; Supercapacitor Materials and Fabrication ; Advanced Sensor and Energy Harvesting Materials
Authors: Bruno Focassio | Luis Paulo Mezzina Freitas | Gabriel R. Schleder
Source: ACS Applied Materials & Interfaces (review, 2024-07-11)
Field: Materials Science — Materials Chemistry

Performance Assessment of Universal Machine Learning Interatomic Potentials: Challenges and Directions for Materials’ Surfaces Machine learning interatomic potentials (MLIPs) are one of the main techniques in the materials science toolbox, able to bridge <i>ab initio</i> accuracy with the computational efficiency of classical force fields. This allows simulations ranging from atoms, molecules, and biosystems, to solid and bulk materials, surfaces, nanomaterials, and their interfaces and complex interactions. A recent class of advanced MLIPs, which use equivariant representations and deep graph neural networks, is known as universal models. These models are proposed as foundation models suitable for any system, covering most elements from the periodic table. Current universal MLIPs (UIPs) have been trained with the largest consistent data set available nowadays. However, these are composed mostly of bulk materials' DFT calculations. In this article, we assess the universality of all openly available UIPs, namely MACE, CHGNet, and M3GNet, in a representative task of generalization: calculation of surface energies. We find that the out-of-the-box foundation models have significant shortcomings in this task, with errors correlated to the total energy of surface simulations, having an out-of-domain distance from the training data set. Our results show that while UIPs are an efficient starting point for fine-tuning specialized models, we envision the potential of increasing the coverage of the materials space toward universal training data sets for MLIPs. Materials science ; Nanotechnology ; Engineering physics ; Chemical physics ; Engineering ; Physics Machine Learning in Materials Science ; Electronic and Structural Properties of Oxides ; Electron and X-Ray Spectroscopy Techniques
Authors: Zhangyu Wu | Hao Pan | Peng Huang | Jinhui Tang | Wei She
Source: Advanced Materials (article, 2024-07-07)
Field: Materials Science — Biomaterials

Biomimetic Mechanical Robust Cement‐Resin Composites with Machine Learning‐Assisted Gradient Hierarchical Structures Abstract Biological materials relying on hierarchically ordered architectures inspire the emergence of advanced composites with mutually exclusive mechanical properties, but the efficient topology optimization and large‐scale manufacturing remain challenging. Herein, this work proposes a scalable bottom‐up approach to fabricate a novel nacre‐like cement‐resin composite with gradient brick‐and‐mortar (BM) structure, and demonstrates a machine learning‐assisted method to optimize the gradient structure. The fabricated gradient composite exhibits an extraordinary combination of high flexural strength, toughness, and impact resistance. Particularly, the toughness and impact resistance of such composite attractively surpass the cement counterparts by factors of approximately 700 and 600 times, and even outperform natural rocks, fiber‐reinforced cement‐based materials and even some alloys. The strengthening and toughening mechanisms are clarified as the regional‐matrix densifying and crack‐tip shielding effects caused by the gradient BM structure. The developed gradient composite not only endows a promising structural material for protective applications in harsh scenarios, but also paves a new way for biomimetic metamaterials designing. Materials science ; Composite material ; Toughness ; Composite number ; Flexural strength ; Electromagnetic shielding ; Fracture toughness ; Cement Calcium Carbonate Crystallization and Inhibition ; Bone Tissue Engineering Materials ; Polymer composites and self-healing