jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Akira Miura | Muratahan Aykol | S Kozaki | Chikako Moriyoshi | Shintaro Kobayashi | Shogo Kawaguchi | Chul‐Ho Lee | Yongming Wang | Amil Merchant | Simon Batzner | Hiroshi Kageyama | Kiyoharu Tadanaga | Pushmeet Kohli | Ekin D. Cubuk
Source: Journal of the American Chemical Society (article, 2024-10-16)
Field: Materials Science — Materials Chemistry

Efficient Exploratory Synthesis of Quaternary Cesium Chlorides Guided by In Silico Predictions Exploratory synthesis of solids is essential for the advancement of materials science but is also highly time- and resource-intensive. Here, we demonstrate an efficient strategy to explore solid-state synthesis of quaternary cesium chlorides in the search space of Cs<sub><i>n</i></sub>A<sup>I</sup>BCl<sub>6</sub> (<i>n</i> = 2 or 3, A = Li, Na or K, and B = <i>d</i> or <i>p</i>-block metal), where the target compositions are selected from a pool of candidates based on computationally predicted stabilities and availability of viable precursor powders. Synthesizability of the targets is assessed by observing the evolution of starting phases upon heating under in situ synchrotron X-ray diffraction. Laboratory synthesis is attempted for promising targets, and resulting materials are characterized by powder X-ray and neutron diffraction and subsequent Rietveld refinement. We focus on how computational predictions can be bridged to experimental characterizations in exploratory synthesis and report on successful and failed synthesis attempts for compounds of type Cs<sub>2</sub>A<sup>I</sup>B<sup>III</sup>Cl<sub>6</sub>, revealing underexplored variants including new polymorphs of Cs<sub>2</sub>LiCrCl<sub>6</sub> and Cs<sub>2</sub>LiRuCl<sub>6</sub>, and a new compound Cs<sub>2</sub>LiIrCl<sub>6</sub>. Chemistry ; Quaternary ; Caesium ; In silico ; Combinatorial chemistry ; Organic chemistry ; Biochemistry Machine Learning in Materials Science ; Zeolite Catalysis and Synthesis ; Chemical Synthesis and Characterization
Authors: G. M. Shweta | Lohit Naik | Sushant Kakati | Rangappa Pujar | Shridhar N. Mathad | Deepak B. Shirgaonkar
Source: Characterization and Application of Nanomaterials (review, 2024-11-22)
Field: Materials Science — Materials Chemistry

A review on antimicrobial properties of nano-ferrites: Biomedical applications This review focuses on ferrites, which are gaining popularity with their unique properties like high electrical resistivity, thermal stability, and chemical stability, making them suitable for versatile applications both in industry and in biomedicine. This review is highly indicative of the importance of synthesis technique in order to control ferrite properties and, consequently, their specific applications. While synthesizing the materials with consideration of certain properties that help in certain methods of preparation using polyol route, green synthesis, sol-gel combustion, or other wise to tailor make certain properties shown by ferrites, this study also covers biomedical applications of ferrites, including magnetic resonance imaging (MRI), drug delivery systems, cancer hyperthermia therapy, and antimicrobial agents. This was able to inhibit the growth of all tested Gram-negative and positive bacteria as compared with pure ferrite nanoparticles without Co, Mn or Zn doping. In addition, ferrites possess the ability to be used in environmental remediation; such as treatment of wastewater which makes them useful for high-surface-area and adsorption capacity due heavy metals and organic pollutants. A critical analysis of functionalization strategies and possible applications are presented in this work to emphasize the capability of nanoferrites as an aid for the advancement both biomedical technology and environmental sustainability due to their versatile properties combined with a simple, cost effective synthetic methodology. Nano- ; Antimicrobial ; Nanotechnology ; Materials science ; Microbiology ; Composite material ; Biology Magnetic Properties and Synthesis of Ferrites
Authors: Seonghwan Kim | Byung Do Lee | Min Young Cho | Myoungho Pyo | Young‐Kook Lee | Woon Bae Park | Kee‐Sun Sohn
Source: npj Computational Materials (article, 2024-09-09)
Field: Materials Science — Materials Chemistry

Deep learning for symmetry classification using sparse 3D electron density data for inorganic compounds We report a novel deep learning (DL) method for classifying inorganic compounds using 3D electron density data. We transform Density Functional Theory (DFT)-derived CHGCAR files from the Materials Project (MP) and experimental data from the Inorganic Crystal Structure Database (ICSD) into point clouds and sparse tensors, optimized for use in DL models such as PointNet and Sparse 3D CNN. This approach effectively overcomes the limitations of handling the dense 3D data, a common challenge in DL. Contrasting with traditional 1D or 2D X-ray diffraction (XRD) patterns that necessitate complex reciprocal space analysis, our method utilizes 3D density data for direct interpretation in real lattice space. This shift significantly enhances classification accuracy, outperforming traditional XRD-driven DL methods. We achieve accuracies of 97.28%, 90.77%, and 90.10% for crystal system, extinction group, and space group classifications, respectively. Our 3D electron density-based DL approach not only showcases improved accuracy but also contributes a more intuitive and effective framework for materials discovery. Symmetry (geometry) ; Computer science ; Pattern recognition (psychology) ; Artificial intelligence ; Chemistry ; Materials science ; Mathematics ; Geometry Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Electron and X-Ray Spectroscopy Techniques
Authors: Esra Öztürk | Nilgün Kalaycıoğlu Özpozan | Volkan Kalem
Source: Luminescence (article, 2024-10-01)
Field: Materials Science — Materials Chemistry

The Investigation of the Effect of La <sup>3+</sup> , Eu <sup>3+</sup> , and Sm <sup>3+</sup> Ions on Photoluminescence and Piezoelectric Behavior of RE <sub>1.90</sub> Y <sub>0.10</sub> Zr <sub>2</sub> O <sub>7</sub> (RE: Eu, Sm and Y: La, Sm, Eu) Pyrochlore‐Based Multifunctional Smart Advanced Materials A series of compounds with the general formula RE<sub>1.90</sub>Y<sub>0.10</sub>Zr<sub>2</sub>O<sub>7</sub> (where RE includes Eu, Sm and Y includes La, Sm, Eu) were synthesized using a solid-state reaction method. These compounds were analyzed through differential thermal analysis (DTA), thermogravimetric analysis (TG), X-ray powder diffraction (XRD), and scanning electron microscopy (SEM). Additionally, their dielectric constant, loss tangent, piezoelectric charge constant, and Curie temperature were measured using an LCR meter, d<sub>33</sub> meter, and TG/DTA. X-ray diffraction results indicated that all samples crystallize in a cubic pyrochlore structure. Photoluminescence studies revealed that Eu<sup>3+</sup> ions predominantly contribute to the emission, whether as activators or co-activators. Among the phosphors, Eu<sub>1.90</sub>La<sub>0.10</sub>Zr<sub>2</sub>O<sub>7</sub> exhibited a significantly longer afterglow compared to Sm<sub>1.90</sub>Eu<sub>0.10</sub>Zr<sub>2</sub>O<sub>7</sub> and Eu<sub>1.90</sub>Sm<sub>0.10</sub>Zr<sub>2</sub>O<sub>7</sub>. Conversely, Sm<sub>1.90</sub>Eu<sub>0.10</sub>Zr<sub>2</sub>O<sub>7</sub> demonstrated luminescence intensity that was 20 times greater than that of Eu<sub>1.90</sub>La<sub>0.10</sub>Zr<sub>2</sub>O<sub>7</sub> and Eu<sub>1.90</sub>Sm<sub>0.10</sub>Zr<sub>2</sub>O<sub>7</sub>. Furthermore, all samples with characteristic Eu<sup>3+</sup> emissions also exhibited piezoelectric properties. Curie temperature (T<sub>c</sub>) of Eu<sub>1.90</sub>La<sub>0.10</sub>Zr<sub>2</sub>O<sub>7</sub>, Sm<sub>1.90</sub>Eu<sub>0.10</sub>Zr<sub>2</sub>O<sub>7</sub>, and Eu<sub>1.90</sub>Sm<sub>0.10</sub>Zr<sub>2</sub>O<sub>7</sub> are 770°C, 830°C, and 845°C, respectively. Therefore, Sm<sup>3+</sup> ion improves piezoelectric properties and Curie temperature when doping into the Eu<sub>2</sub>Zr<sub>2</sub>O<sub>7</sub> host crystal. Analytical Chemistry (journal) ; Photoluminescence ; Luminescence ; Materials science ; Phosphor ; Pyrochlore ; Europium ; Powder diffraction ; Differential thermal analysis ; Ion ; Crystallography ; Chemistry ; Diffraction ; Physics ; Phase (matter) Nuclear materials and radiation effects ; Microwave Dielectric Ceramics Synthesis ; Ferroelectric and Piezoelectric Materials
Authors: Elena García Trelles | Christoph Schweizer | Akhil Thomas | Philipp von Hartrott | Marina Janka-Ramm
Source: Applied Sciences (article, 2024-12-14)
Field: Materials Science — Materials Chemistry

Digitalizing Material Knowledge: A Practical Framework for Ontology-Driven Knowledge Graphs in Process Chains This paper proposes a robust methodology for integrating process-specific data and domain expert knowledge into linked knowledge graphs. These graphs utilize an ontology that provides a standardized vocabulary for material science and facilitates the creation of semantic models for various processes along the digital process chain. A generic template for structuring processes is proposed, simplifying subsequent data retrieval. The templates of specific processes are designed collaboratively by domain and ontology experts, aided by a proposed interview template that bridges the knowledge gap. Following the digitalization of material data through semantic modeling, machine-readable data with contextual metadata is stored in a graph database, which can be efficiently queried using the SPARQL language, enabling seamless integration into data pipelines. To demonstrate this approach, a knowledge graph is developed to represent the process chain of AlSi10Mg objects manufactured via permanent mold casting, capturing their complete history from the initial manufacturing step to final non-destructive testing and mechanical characterization. This methodology enhances data interoperability and accessibility while providing context-rich data for training AI models, potentially accelerating new knowledge discovery in material science. Computer science ; Knowledge graph ; Process (computing) ; Ontology ; Information retrieval ; Knowledge management ; Epistemology ; Programming language ; Philosophy Machine Learning in Materials Science ; Semantic Web and Ontologies
Authors: Sayma Khandaker | Nurulain Shaipuzaman | Md Mahmudul Hasan | Mohd Amir Shahlan Mohd Aspar | Hadi Manap
Source: Pertanika journal of science & technology (review, 2024-10-23)
Field: Chemistry — Spectroscopy

A Comprehensive Review of State-of-the-art Optical Methods for Methane Gas Detection Methane (CH&lt;sub&gt;₄&lt;/sub&gt;), a potent greenhouse gas, significantly contributes to climate change and global warming. Its impact over 100 years surpasses carbon dioxide (CO&lt;sub&gt;₂&lt;/sub&gt;) by 28 times. Addressing methane emissions, particularly from oil and gas production activities such as transmission pipelines, is imperative. One promising avenue is the development of reliable sensors to detect and mitigate methane leaks and prevent hazardous issues. Optical-based methods present notable advantages, including versatility and remote operation, making them pivotal in this endeavor. This review article provides a concise overview of optical-based methane identification technologies, encompassing sensing materials, absorption spectra, operational mechanisms, and recent advancements. Potential perspectives are explored, and inferences from this assessment are also derived. Emphasizing the significance of optical fiber-based methane detection methods, the authors advocate for further research to support ongoing efforts and foster innovation in this critical area. Methane ; State (computer science) ; Methane gas ; Environmental science ; Computer science ; Chemistry ; Organic chemistry ; Algorithm Spectroscopy and Laser Applications ; Gas Sensing Nanomaterials and Sensors ; Atmospheric and Environmental Gas Dynamics
Authors: Agnieszka Gola | Rafał Pietrańczyk | Witold Musiał
Source: Polymers (article, 2024-07-05)
Field: Materials Science — Polymers and Plastics

Synthesis and Physicochemical Properties of Thermally Sensitive Polymeric Derivatives of N-vinylcaprolactam Six derivatives of poly-<i>N</i>-vinylcaprolactam (PNVCL) P1-P6 were synthesized via surfactant-free precipitation polymerization (SFPP) at 70 °C, with potassium persulfate (KPS) as the initiator. P5 and P6 were synthesized using the cross-linker <i>N</i>,<i>N</i>'-Methylenebisacrylamide (MBA). The conductivity was measured to monitor the polymerization process. The hydrodynamic diameters (HDs) and polydispersity indexes (PDIs) of aqueous dispersions of P1-P6 were determined using dynamic light scattering (DLS) and zeta potential (ZP) using electrophoretic mobilities. At 18 °C for P1-P6, the HDs (nm) were 428.32 ± 81.30 and PDI 0.31 ± 0.19, 528.60 ± 84.70 (PDI 0.42 ± 0,04), 425.96 ± 115.42 (PDI 0.56 ± 0.08), 440.34 ± 106.40 (PDI 0.52 ± 0.09), 198.39 ± 225.35 (PDI 0.40 ± 0.19), and 1201.52 ± 1318.05 (PDI 0.71 ± 0.30), the and ZPs were (mV) 0.90 ± 3.23, -4.46 ± 1.22, -6.44 ± 1.82, 0.22 ± 0.48, 0.18 ± 0.79, and -0.02 ± 0.39 for P1-P6, respectively. The lower critical solution temperature ranged from 27 to 29 °C. The polymers were characterized using the ATR-FTIR method. The study concluded that the physicochemical properties of the product were significantly affected by the initial reaction parameters. Polymers P1-P4 and P6 have potential for use as drug carriers for skin applications. Materials science ; Chemical engineering ; Polymer science ; Polymer chemistry ; Chemistry ; Engineering Synthesis and properties of polymers ; Analytical Chemistry and Chromatography ; Advanced Polymer Synthesis and Characterization
Authors: Ruibin Yuan | Hanfeng Lin | Y. F. Wang | Zeyue Tian | Shangda Wu | Tianhao Shen | Ge Zhang | Yuhang Wu | Cong Liu | Ziya Zhou | Ziyang Ma | Liumeng Xue | Ziyu Wang | Qin Liu | Tianyu Zheng | Yi‐Zhi Li | Yinghao Ma | Yiming Liang | Xiaowei Chi | Ruibo Liu | Zili Wang | Peng‐Fei Li | Jingcheng Wu | Chenghua Lin | Qifeng Liu | Tao Jiang | Wenhao Huang | Wenhu Chen | Emmanouil Benetos | Jie Fu | Gus Xia | Roger B. Dannenberg | Wei Xue | Shiyin Kang | Yike Guo
Source: arXiv (Cornell University) (preprint, 2024-02-25)
Field: Materials Science — Materials Chemistry

ChatMusician: Understanding and Generating Music Intrinsically with LLM While Large Language Models (LLMs) demonstrate impressive capabilities in text generation, we find that their ability has yet to be generalized to music, humanity's creative language. We introduce ChatMusician, an open-source LLM that integrates intrinsic musical abilities. It is based on continual pre-training and finetuning LLaMA2 on a text-compatible music representation, ABC notation, and the music is treated as a second language. ChatMusician can understand and generate music with a pure text tokenizer without any external multi-modal neural structures or tokenizers. Interestingly, endowing musical abilities does not harm language abilities, even achieving a slightly higher MMLU score. Our model is capable of composing well-structured, full-length music, conditioned on texts, chords, melodies, motifs, musical forms, etc, surpassing GPT-4 baseline. On our meticulously curated college-level music understanding benchmark, MusicTheoryBench, ChatMusician surpasses LLaMA2 and GPT-3.5 on zero-shot setting by a noticeable margin. Our work reveals that LLMs can be an excellent compressor for music, but there remains significant territory to be conquered. We release our 4B token music-language corpora MusicPile, the collected MusicTheoryBench, code, model and demo in GitHub. Psychology ; Computer science Machine Learning in Materials Science ; Scientific Computing and Data Management ; Topic Modeling
Authors: Manjit Singh Jadon | Sandeep Kumar
Source: International Journal of Online and Biomedical Engineering (iJOE) (article, 2024-07-16)
Field: Materials Science — Polymers and Plastics

Fabrication of TiO2 Nanoparticle Coating on Stainless Steel 316L and Its Assessment for Orthopaedic Applications The study aims to investigate the efficacy of titanium dioxide (TiO2) nanoparticle coating on stainless steel 316L (SS 316L) orthopaedic implants to enhance their biocompatibility, osseointegration, and durability. The TiO2 nanoparticles were synthesized via the hydrothermal method and extensively characterized for composition, crystallinity, and morphology using techniques such as X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM) with energy dispersive X-ray analysis (EDX), corroborated by elemental mapping. SEM and XRD analyses revealed the synthesized nanoparticles have a spherical shape and an average size of approximately 23 nanometres. The synthesized TiO2 nanoparticles were uniformly coated on SS 316L substrates using the spin coating technique, as confirmed by SEM images. Cell viability of the synthesized TiO2 nanoparticles, as well as uncoated and TiO2 nanoparticle-coated SS 316L substrates, was evaluated using the MTT (3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide) assay against the NIH-3T3 mouse embryonic fibroblast cell line. The results demonstrated that the TiO2 nanoparticle-coated SS 316L substrate showed a significant increase of 22.87% in cell viability as compared to the uncoated SS 316L substrate. A ball-on-disc tribometer was employed to assess wear and friction resistance at various speeds, viz., 150 rpm, 300 rpm, and 450 rpm, under 30N load conditions for five minutes. The results collectively indicate a substantial improvement in the performance of TiO2 nanoparticle-coated SS 316L substrates for orthopaedic applications. Fabrication ; Coating ; Materials science ; Nanoparticle ; Nanotechnology ; Composite material ; Metallurgy ; Medicine Polymer Nanocomposite Synthesis and Irradiation ; Bone Tissue Engineering Materials
Authors: Shengchao Liu | Weitao Du | Hannan Xu | Yanjing Li | Zhuoxinran Li | Vignesh C. Bhethanabotla | Divin Yan | Christian Borgs | Anima Anandkumar | Hai-Feng Guo | Jennifer Chayes
Source: Research Square (preprint, 2024-12-11)
Field: Materials Science — Materials Chemistry

A Multi-Grained Symmetric Differential Equation Model for Learning Protein-Ligand Binding Dynamics Computer science ; Trajectory ; Molecular dynamics ; Speedup ; Solver ; Algorithm ; Physics ; Computational chemistry ; Chemistry ; Parallel computing Machine Learning in Materials Science ; Protein Structure and Dynamics ; Computational Drug Discovery Methods
Authors: Seyedeh Maryam Mortazavi | Seyyed Ali Mohammadi Vadoud | Hamid Reza Moghimi
Source: Bioimpacts (review, 2024-04-28)
Field: Materials Science — Biomaterials

Topically applied GHK as an anti-wrinkle peptide: Advantages, problems and prospective Although GHK-Cu and Pal-GHK are effective and relatively skin permeable, their permeability could be successfully increased using permeation enhancement methodologies. Wrinkle ; Peptide ; Medicine ; Chemistry ; Biochemistry ; Gerontology Silk-based biomaterials and applications ; Skin Protection and Aging ; Photochromic and Fluorescence Chemistry
Authors: José M. M. M. de Almeida | P. Santos | J. Caldinhas Vaz | Ricardo A. Marques Lameirinhas | Catarina P. Correia V. Bernardo | João Paulo N. Torres
Source: Energies (article, 2024-10-24)
Field: Materials Science — Materials Chemistry

Step-Up DC-DC Converter Supplied by a Thermoelectric Generator for IoT Applications This research work aims to design and prototype a DC-DC converter to step up the low voltage of a small, low-power thermoelectric generator (TEG). The system is based on an inductive boost converter and attains a regulated output voltage of 1.2 V. The design’s optimisation was based on simulation and experimental validation and it was implemented with only ten low-cost commercial off-the-shelf (COTS) components. To reduce complexity, the low-side switch MOSFET of the boost converter is directly driven by an LC oscillator, switching at 1.25 MHz. For loads above 20 kΩ, the converter ensures voltages higher than 1.2 V, supplied by the TEG voltage of 0.5 V, while registering identical efficiency values to those of more complex and expensive CMOS-integrated solutions. These designed features suggest applications in remote IoT nodes and portable devices, delivering sufficient power to backup the supply of corresponding sensing and communication low-power circuits, reducing the necessity of battery replacements or increasing their lifetime. Thermoelectric generator ; Electrical engineering ; Generator (circuit theory) ; Thermoelectric effect ; Flyback converter ; Engineering ; Computer science ; Boost converter ; Physics ; Voltage ; Power (physics) Advanced Thermoelectric Materials and Devices ; Energy Harvesting in Wireless Networks ; Innovative Energy Harvesting Technologies
Authors: S. Elashry | Usama Rashed | Mostafa A. WAHBA | Hend M. Ahmed | N.M. El-Siragy
Source: Plasma Science and Technology (article, 2024-03-22)
Field: Materials Science — Surfaces, Coatings and Films

Surface activation of viscose textiles via air, argon, and oxygen dielectric barrier discharge plasma: influence of peak voltage Abstract This paper discusses the use of atmospheric pressure dielectric barrier discharge (DBD) plasma treatment to enhance the surface qualities of viscose fabrics. The study explores the effects of different plasma gases, discharge voltages, and exposure times on the treated fabrics. The findings emphasize the importance of optimizing the plasma’s peak voltage to achieve the desired surface treatment outcomes. The document also presents data on colour strength, wettability, colour fastness, and tensile strength of the treated fabrics, as well as scanning electron microscopy (SEM) analysis of surface morphology and chemical analysis using fourier- transition infrared spectroscopy (FTIR) and energy dispersive X-ray (EDX). The results show that treatment at a peak voltage of 11.83 kV is more efficient, except for the tensile strength which is enhanced at a peak voltage of 8.92 kV. The oxygen plasma treatment significantly improves the colour strength, which exhibits an increase from 11 to 18. The intensified colour was attributed to the significant influence of electrostatic interactions between the charged hydroxyl groups of the oxygen plasma treated viscose textiles and the dye molecules, which enhance the printability. The oxygen DBD plasma exhibits a higher ability to enhance the properties of textiles when compared to air and argon plasmas. This study presents a sustainable, economical, secure, and ecologically friendly approach to explore new fabrics for specific uses. Viscose ; Dielectric barrier discharge ; Materials science ; Argon ; Oxygen ; Plasma cleaning ; Plasma ; Partial discharge ; Dielectric ; Composite material ; Voltage ; Chemistry ; Electrical engineering ; Optoelectronics ; Organic chemistry Surface Modification and Superhydrophobicity ; Plasma Applications and Diagnostics ; Nanomaterials and Printing Technologies