jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Basita Das | Kangyu Ji | Fang Sheng | Kyle M. McCall | Tonio Buonassisi
Source: Faraday Discussions (article, 2024-07-15)
Field: Materials Science — Materials Chemistry

Embedding human knowledge in material screening pipeline as filters to identify novel synthesizable inorganic materials How might one embed a chemist's knowledge into an automated materials-discovery pipeline? In generative design for inorganic crystalline materials, generating candidate compounds is no longer a bottleneck - there are now synthetic datasets of millions of compounds. However, weeding out unsynthesizable or difficult to synthesize compounds remains an outstanding challenge. Post-generation "filters" have been proposed as a means of embedding human domain knowledge, either in the form of scientific laws or rules of thumb. Examples include charge neutrality, electronegativity balance, and energy above hull. Some filters are "hard" and some are "soft" - for example, it is difficult to envision creating a stable compound while violating the rule of charge neutrality; however, several compounds break the Hume-Rothery rules. It is therefore natural to wonder: can one compile a comprehensive list of "filters" that embed domain knowledge, adopt a principled approach to classifying them as either non-conditional or conditional "filters," and envision a software environment to implement combinations of these in a systematic manner? In this commentary we explore such questions, "filters" for screening of novel inorganic compounds for synthesizability. Pipeline (software) ; Embedding ; Computer science ; Nanotechnology ; Computer architecture ; Chemistry ; Process engineering ; Materials science ; Engineering ; Artificial intelligence ; Programming language Material Selection and Properties ; Machine Learning in Materials Science ; Geochemistry and Geologic Mapping
Authors: Sabrina Antonella Maccio | Rubén Darío Alaniz | Gastón Darío Pierini | Marı́a Alicia Zón | Fernando Javier Arévalo | Héctor Fernández | Héctor C. Goicoechea | Sebastián Noel Robledo | Mirta R. Alcaráz
Source: Chemosensors (article, 2024-09-23)
Field: Chemistry — Electrochemistry

A Straightforward Electrochemical Approach for the Simultaneous Determination of Thymol and Carvacrol in Essential Oils A novel, simple, rapid, and non-expensive analytical method based on square wave voltammogram at Pt-microelectrode coupled with partial least square multivariate calibration was used for the simultaneous quantitation of thymol (THY) and carvacrol (CAR) in thyme and oregano essential oils. Results demonstrated that the multivariate calibration method successfully exploited the first-order advantage, rendering highly satisfactory quantitative figures (average recoveries not statistically different than 100%). Moreover, the results agree well with those obtained from the official analytical method. Last, the method’s environmental sustainability was asserted using the AGREE metric, highlighting its eco-friendly nature. More importantly, the proposed analytical procedure does not require previous sample preparation or electrode surface modification. The results underscore the suitability of the method for determining THY and CAR in essential oils at low concentrations (LOD ~ 7.6 µM) with REP% below 5.6%, meeting the requirements of the green analytical chemistry. Thymol ; Carvacrol ; Essential oil ; Chemistry ; Chromatography ; Analytical Chemistry (journal) Electrochemical Analysis and Applications ; Pesticide Residue Analysis and Safety ; Analytical Chemistry and Sensors
Authors: Jürgen Bajorath
Source: Future Science OA (article, 2024-02-07)
Field: Materials Science — Materials Chemistry

Chemical and biological language models in molecular design: opportunities, risks and scientific reasoning Computer science ; Artificial intelligence ; Context (archaeology) ; Language model ; Popularity ; Scientific terminology ; Cognitive science ; Data science ; Psychology ; Biology Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: Sanaz Zarei
Source: Research Square (preprint, 2024-02-15)
Field: Materials Science — Materials Chemistry

On-chip programmable optical routing using nonvolatile Sb2Se3 phase-change metasurfaces Chip ; Routing (electronic design automation) ; Phase (matter) ; Materials science ; Phase change ; Optoelectronics ; Computer science ; Electronic engineering ; Embedded system ; Telecommunications ; Physics ; Engineering ; Engineering physics Phase-change materials and chalcogenides ; Metamaterials and Metasurfaces Applications ; Chalcogenide Semiconductor Thin Films
Authors: Manh‐Ha Doan | Peter Bøggild
Source: 2D Materials (article, 2024-12-17)
Field: Materials Science — Materials Chemistry

Interface engineering of van der Waals heterostructures towards energy-efficient quantum devices operating at high temperatures Abstract Quantum devices, which rely on quantum mechanical effects for their operation, may offer advantages, such as reduced dimensions, increased speed, and energy efficiency, compared to conventional devices. However, quantum phenomena are typically observed only at cryogenic temperatures, which limits their practical applications. Two-dimensional materials and their van der Waals (vdW) heterostructures provide a promising platform for high-temperature quantum devices owing to their strong Coulomb interactions and/or spin–orbit coupling. In this review, we summarise recent research on emergent quantum phenomena in vdW heterostructures based on interlayer tunnelling and the coupling of charged particles and spins, including negative differential resistance, Josephson tunnelling, exciton condensation, and topological superconductivity. These are the underlying mechanisms of energy-efficient devices, including tunnel field-effect transistors, topological/superconducting transistors, and quantum computers. The natural homojunction within vdW layered materials offers clean interfaces and perfectly aligned structures for enhanced interlayer coupling. Twisted bilayers with small angles may also give rise to novel quantum effects. In addition, we highlight several proposed structures for achieving high-temperature Majorana zero modes, which are critical elements of topological quantum computing. This review is helpful for researchers working on interface engineering of vdW heterostructures towards energy-efficient quantum devices operating above liquid nitrogen temperature. Heterojunction ; Interface (matter) ; van der Waals force ; Quantum ; Materials science ; Engineering physics ; Physics ; Optoelectronics ; Quantum mechanics ; Molecule Boron and Carbon Nanomaterials Research ; Electronic and Structural Properties of Oxides ; 2D Materials and Applications
Authors: Amit Kumar Choudhary | Dominic Hohs | Andreas Jansche | Timo Bernthaler | D. Goll | Gerhard Schneider
Source: AIP Advances (article, 2024-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A data-driven approach to predict the saturation magnetization for magnetic 14:2:1 phases from chemical composition 14:2:1 phases enable permanent magnets with excellent magnetic properties. From an application viewpoint, saturation polarization, Curie temperature, and anisotropy constant are important parameters for the magnetic 14:2:1 phases. Novel chemical compositions that represent new 14:2:1 phases require especially maximum saturation magnetization values at application-specific operating temperatures to provide maximum values for the remanence and the maximum energy density in permanent magnets. Therefore, accurate knowledge of the saturation magnetization Ms is important. Ms gets affected by chemical composition in a twofold way, with chemical composition significantly influencing both magnetic moments and crystal structure parameters. Therefore, for magnetic 14:2:1 phases, we have developed a regression model with the aim to predict the saturation magnetization in [µB/f.u.] at room temperature directly from the chemical composition as input features. The dataset for the training and testing of the model is very diverse, with literature data of 143 unique phases and 55 entries of repeated phases belonging to the ternary, quaternary, quinary, and senary alloy systems. Substitutionally dissolved elements are heavy and light rare earth elements, transition metals, and additional elements. The trained model is a voting regressor model with different weights assigned to four base regressors and has generalized well, resulting in a low mean absolute error of 0.8 [µB/f.u.] on the unseen test set of 52 phases. This paper could serve as the basis for developing novel magnetic 14:2:1 phases from chemical composition. Remanence ; Magnetization ; Saturation (graph theory) ; Quinary ; Chemical composition ; Curie temperature ; Magnet ; Magnetic anisotropy ; Anisotropy ; Condensed matter physics ; Materials science ; Ternary operation ; Chemistry ; Nuclear magnetic resonance ; Thermodynamics ; Alloy ; Magnetic field ; Ferromagnetism ; Metallurgy ; Physics ; Computer science ; Mathematics ; Optics Magnetic Properties of Alloys ; Magnetic Properties and Applications ; Magnetic and transport properties of perovskites and related materials
Authors: Luonan Chen | Xianle Ruan | Xinyi Li | Hongtuo Fu
Source: Computational Molecular Biology (article, 2024-01-01)
Field: Chemistry — Physical and Theoretical Chemistry

Molecular Interactions in Biological Systems: Technological Applications and Innovations This study reviews the complex interactions between proteins, DNA, RNA, lipids, and small molecules in biological systems, emphasizing the critical role of the &quot;interactome&quot; concept in understanding organismal functions. These interactions, including protein-protein and protein-RNA interactions, play significant roles in cellular processes such as recognition, regulation, and signaling, and have great potential in drug discovery. The research methods encompass various biophysical techniques, such as mass spectrometry (MS), nuclear magnetic resonance (NMR) spectroscopy, and surface plasmon resonance (SPR), which are used to elucidate the structure and dynamics of molecular interactions. The results demonstrate that molecular interactions are key to developmental innovation, environmental adaptation, and disease mechanisms, particularly in revealing the interactions between biological membranes and small molecules, protein complex formation, and drug target discovery. The study highlights the importance of future improvements in research methods, especially through the integration of computational and experimental approaches, to better understand the dynamic molecular interactions in biological systems. Computational biology ; Computer science ; Nanotechnology ; Biology ; Materials science Various Chemistry Research Topics
Authors: Shreya Talreja | Shashank Tiwari
Source: Asian Journal of Pharmaceutical Research and Development (article, 2024-10-15)
Field: Chemistry — Organic Chemistry

Current Trends in Alkaloid Research: From Natural Sources to Synthetic Pathways Alkaloid is a large family of the diverse natural compounds that are provided with nitrogen atoms. Primarily derived from vegetation, these substances have a great many actions, opening up their applications in medicine, agriculture, and industry. This review is a complete description of alkaloids; starting from the sorting, the biosynthesis, and pharmacological activities, it covers all the aspects. The epitome of their therapeutic uses, such as pain relievers, heart rate stimulants, antimalarial drugs, anticancer drugs, and antibiotics, will be made. The authors present recent frontiers on Biotechnological approaches, the new discovery of alkaloids and the development of environmentally friendly production techniques. This publication is ended with the statement that in the places of personalized medicine, nanotechnology, and synthetic biology, especially alkaloids are key players in creating more effective drugs to different diseases. Natural (archaeology) ; Alkaloid ; Chemistry ; Geography ; Stereochemistry ; Archaeology Chemical synthesis and alkaloids ; Plant-based Medicinal Research
Authors: Samira Shokri | Nabi Shariatifar | Ebrahim Molaee-Aghaee | Gholamreza Jahed Khaniki | Parisa Sadighara | Somaye Vali Zade | Shahram Shoeibi
Source: Food Chemistry X (article, 2024-09-25)
Field: Chemistry — Analytical Chemistry

Ponceau 4R elimination from fruit juice: An integrated optimization strategy utilizing artificial neural networks, least squares, and chitosan-nickel ferrite Nano Sorbent The goal of present work is to examine the efficiency of aminated-chitosan/NiFe<sub>2</sub>O<sub>4</sub> nanoparticles (AmCs/NiFe<sub>2</sub>O<sub>4</sub> NPs) produced for removing Ponceau 4R (P4R) from fruit juice through an adsorption process. The resulting nanoparticles were characterized using various techniques. The modeling of results was done using least squares (LS) and <i>Radial basis function-</i>artificial neural network (RBF-ANN). The optimum removal of P4R (91.43 %) was obtained at the following optimum conditions: pH 4.47, adsorbent dosage 0.047 g/L, contact time approximately 57.78 min, and initial concentration P4R 26.89 mg/L. The highest adsorption capacity (qm) was found to be 208.33 mg g<sup>-1</sup>. The P4R adsorption mostly followed the Freundlich and pseudo-second-order isotherm kinetic models. Both LS-based models and RBF-ANN provided good predictions for independent variables. The dye elimination efficacy for juice samples were approximately 90.34 %. Therefore, based on the obtained results, it can be claimed that the prepared AmCs/NiFe<sub>2</sub>O<sub>4</sub> NPs can be used to remove P4R. Sorbent ; Chitosan ; Artificial neural network ; Nano- ; Nickel ; Materials science ; Ferrite (magnet) ; Chemical engineering ; Process engineering ; Composite material ; Chemistry ; Metallurgy ; Computer science ; Engineering ; Artificial intelligence ; Organic chemistry ; Adsorption Dye analysis and toxicity ; Biochemical Analysis and Sensing Techniques ; Spectroscopy and Chemometric Analyses
Authors: Sagar Dhoble | Tzu‐Hsien Wu | Kenry Kenry
Source: Angewandte Chemie (article, 2024-01-25)
Field: Materials Science — Materials Chemistry

Decoding Nanomaterial‐Biosystem Interactions through Machine Learning Abstract The interactions between biosystems and nanomaterials regulate most of their theranostic and nanomedicine applications. These nanomaterial‐biosystem interactions are highly complex and influenced by a number of entangled factors, including but not limited to the physicochemical features of nanomaterials, the types and characteristics of the interacting biosystems, and the properties of the surrounding microenvironments. Over the years, different experimental approaches coupled with computational modeling have revealed important insights into these interactions, although many outstanding questions remain unanswered. The emergence of machine learning has provided a timely and unique opportunity to revisit nanomaterial‐biosystem interactions and to further push the boundary of this field. This minireview highlights the development and use of machine learning to decode nanomaterial‐biosystem interactions and provides our perspectives on the current challenges and potential opportunities in this field. Nanomedicine ; Nanomaterials ; Nanotechnology ; Computer science ; Field (mathematics) ; Materials science ; Nanoparticle Machine Learning in Materials Science ; Gold and Silver Nanoparticles Synthesis and Applications ; Advanced biosensing and bioanalysis techniques
Authors: Zouheyr Belouadah | K. Nasri | Lotfi Toubal
Source: Preprints.org (preprint, 2024-03-20)
Field: Materials Science — Polymers and Plastics

Effects of Lignin on the Thermal and Morphological Properties and Damages Mechanisms after UV Irradiation of Polypropylene Biocomposites Reinforced with Flax and Pine Fibres: Acoustic Emission Analysis Various wood fibres, including pine and flax, are used in wood–plastic composites (WPCs). This paper studies the effect of the lignin content on the morphological and thermal degradation and damage due to the ultraviolet (UV) aging of polypropylene/flax (PP-flax) and polypropylene/pine (PP-pine) fibres composites. Flax and pine fibres exhibited distinct densities of 1.51 and 1.47 g/cm³, respectively, potentially influenced by growth factors and varying compositions of light substances, such as hemicellulose, lignin, and impurities. The thermal decomposition mass loss increased proportionally with the percentage of lignin in the fibre. From 238°C to 390°C, the pine fibre exhibited a 72% mass loss compared to flax fibre, which showed a 54% mass loss, owing to the higher lignin content in pine fibres. Based on differential scanning calorimetry (DSC), the fibre composition affected the material melting temperature. Moreover, DSC curves revealed a higher degree of crystallinity in the case of the PP-flax biocomposite (12%) compared to pure polypropylene (9%) and PP-pine (6%). This result can be attributed to the high content of crystalline components in flax fibres, such as cellulose. Acoustic emissions analysis confirmed that the high lignin content delays degradation and mitigates the appearance of microcracks on the surface of the PP-pine biocomposite. Overall, the study provides valuable data for understanding the UV degradation phenomenon in biocomposites and highlights the influence of fibre composition on material performance. Polypropylene ; Composite material ; Materials science ; Lignin ; Irradiation ; Damages ; Chemistry ; Organic chemistry Natural Fiber Reinforced Composites ; Nanocomposite Films for Food Packaging
Authors: Kara A. Zielinski | Cole Dolamore | H. Wang | Robert Henning | Mark A. Wilson | Lois Pollack | V. Šrajer | Doeke R. Hekstra | Kevin M. Dalton
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2024-07-31)
Field: Materials Science — Materials Chemistry

Scaling and Merging Time-Resolved Laue Data with Variational Inference Time-resolved X-ray crystallography (TR-X) at synchrotrons and free electron lasers is a promising technique for recording dynamics of molecules at atomic resolution. While experimental methods for TR-X have proliferated and matured, data analysis is often difficult. Extracting small, time-dependent changes in signal is frequently a bottleneck for practitioners. Recent work demonstrated this challenge can be addressed when merging redundant observations by a statistical technique known as variational inference (VI). However, the variational approach to time-resolved data analysis requires identification of successful hyperparameters in order to optimally extract signal. In this case study, we present a successful application of VI to time-resolved changes in an enzyme, DJ-1, upon mixing with a substrate molecule, methylglyoxal. We present a strategy to extract high signal-to-noise changes in electron density from these data. Furthermore, we conduct an ablation study, in which we systematically remove one hyperparameter at a time to demonstrate the impact of each hyperparameter choice on the success of our model. We expect this case study will serve as a practical example for how others may deploy VI in order to analyze their time-resolved diffraction data. Hyperparameter ; Bottleneck ; Inference ; Computer science ; Algorithm ; SIGNAL (programming language) ; Scaling ; Noise (video) ; Physics ; Statistical physics ; Data mining ; Artificial intelligence ; Image (mathematics) ; Mathematics Enzyme Structure and Function ; Advanced Electron Microscopy Techniques and Applications ; Advanced X-ray Imaging Techniques
Authors: Xu Sun | Haixia Cheng | Songqi Cheng | Yikun Fang | Minggang Zhu | Hang Su | Wei Li
Source: Metals (article, 2024-11-27)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Revisiting the Structural and Magnetic Properties of SmCo5/Sm2Co17 Interface from First-Principles Investigations The formation and evolution of SmCo5/Sm2Co17 (1:5H/2:17R/H) cellular structures play an essential role in understanding the coercivity of Sm-Co magnets. Herein, the pristine and different elemental-doped 1:5/2:17R and 1:5/2:17H interfaces are investigated to evaluate the elemental site preferences, interface configurations, and magnetic properties in Sm2Co17-type magnets with general alloy elements M (M = Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Al, Si, and Ga). Comparing the calculated results of 1:5/2:17H with those of the 1:5/2:17R interface, we found that Cu and Mn always segregate at the 1:5 phase, and Ga elements first appear at the 1:5 phase in 1:5/2:17H and then change to the 2:17 phase in 1:5/2:17R. While Ti, V, Fe, Zn, Al, and Si elements always tend to segregate at the 2:17 phase, Ni first segregates at the 2:17 phase in 1:5/2:17H and then occupies the 1:5 phase of 1:5/2:17R. The 1:5/2:17H interface along the c-axis expands about 1.98~3.28%, while the 1:5/2:17R interface slightly shrinks about 0.04~0.87% after element doping. This suggests that different interface stress behaviors exist for high-temperature and room-temperature phase Sm2Co17-type magnets. Furthermore, Mn, Fe, and Ga doping improved the saturation magnetization strength. Our results provide new insights into understanding the effect of elemental doping at the interfaces of 1:5H/2:17R cellular structures. Interface (matter) ; Materials science ; Composite material Magnetic Properties of Alloys ; Rare-earth and actinide compounds ; Magnetic and transport properties of perovskites and related materials
Authors: Universiti Pertahanan Nasional Malaysia | Nur Arina Mat Rusni | Azuraida Amat | Wan Yusmawati Wan Yusoff | Nor Azlian Abdul Manaf | Nurazlin Ahmad
Source: International Journal of Integrated Engineering (article, 2024-10-08)
Field: Materials Science — Materials Chemistry

Mechanical Properties of Thulium-doped Bismuth Borotellurite Glass via Nanoindentation for Lead-Free Radiation Shielding Application Commercially, lead-based glasses are used in industry as transparent radiation shielding material due to their durability.However, lead toxicity could cause detrimental health issues to humans.Thus, in this study, a new composition of thulium-doped bismuth borotellurite glass was fabricated via melt-and-quench technique.The effect of bismuth oxide (Bi2O3) on the physical, structural, and mechanical properties of the glass was investigated.Glass with 0.25 mol% of Bi2O3 has the highest density.However, the oxygen packing density (OPD) of glass with 0.15 mol% of Bi2O3 is higher than 0.25 mol% of Bi2O3.This is due to a high number of non-bridging oxygen (NBOs) in 0.25 mol% of Bi2O3 glass structure.The bonds that are present in the glass structure were verified by Fourier Transform Infrared Spectroscopy (FTIR) analysis.Then, the mechanical properties were investigated by nanoindentation test with Berkovich indenter.Comparing the mechanical properties of indented glass samples, 0.15Bi glass projected the best mechanical durability since it provides the highest hardness and reduced elastic modulus value.Also, the low plastic work and optimal elastic work make 0.15Bi glass resilient to stress.Thus, the 0.15Bi glass is deemed as the best glass sample for high mechanical strength radiation shielding glass.This lead-free radiation shielding glass does not pose harmful effects to humans. Nanoindentation ; Materials science ; Bismuth ; Thulium ; Radiation shielding ; Electromagnetic shielding ; Doping ; Lead (geology) ; Composite material ; Metallurgy ; Optoelectronics ; Geology Radiation Shielding Materials Analysis ; Polymer Nanocomposite Synthesis and Irradiation ; Glass properties and applications