jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Taqmeem Hussain | Rahila Kousar | Kanwal Younas | Khurram Saleem | Aamir Shahzad | Tariq Munir | M. Fakhar-e-Alam | Arsalan Mehmood | Muhammad Asif | Kholood A. Dahlous | Mohamed F. Shibl | Noora Al‐Qahtani
Source: Radiochimica Acta (article, 2024-09-19)
Field: Materials Science — Materials Chemistry

Thermoluminescence response of Ce doped CaTiO<sub>3</sub> nanophosphor synthesized by hydrothermal method for gamma dosimetry Abstract Nanocrystalline calcium titanate (CaTiO 3 ) doped with cerium ions (0.02 mol%) was synthesized via hydrothermal method and its luminescent properties were studied for gamma dosimetry. For the synthesized samples, the best luminescent response was achieved after annealing at 700 °C for 8 h. The synthesis was confirmed via XRD technique yielding the cyrstallite size of 22 nm for the most intense peak (121). The surface morphology was studied via scanning electron microscopy (SEM) yielding the grain size of 12 µm. The strong IR absorptions appeared at 700 cm−1 and 712 cm −1 attributed to bending mode of vibrations changing angle between Ti–O–Ti for CaTiO 3 and CaTiO 3 :Ce respectively, as confirmed via Fourier-Transform Infrared (FTIR) Spectroscopy. Thermoluminescent (TL) response of undoped and doped samples was studied by Mikrolab RA94 TLD Reader-Analyzer having heating rate 10 °C/s, for absorbed doses 0–20 mGy from 137 Cs γ-source having a dose rate 100 mSv/h. The found values at 662 keV for the photon-sensing parameters, i.e., mass attenuation coefficients ( μ / ρ ), mass-energy attenuation coefficient ( μ en / ρ ), effective atomic number for photon interaction ( Z eff,PI ) and effective atomic number for total photon energy absorption ( Z eff,PEA ) were 0.07030882 cm 2 /g, 0.0280245 cm 2 /g, 13.9 and 13.4 respectively. Thus, synthesized nanophosphor has shown excellent thermoluminescent dosimetric response for gamma radiation sensing in the selected dose range. Thermoluminescence ; Hydrothermal circulation ; Chemistry ; Dosimetry ; Doping ; Radiochemistry ; Nuclear chemistry ; Chemical engineering ; Luminescence ; Materials science ; Optoelectronics ; Nuclear medicine Luminescence Properties of Advanced Materials ; Radiation Detection and Scintillator Technologies ; Nuclear materials and radiation effects
Authors: Shahrbano Rahimi | S. Jalali-Asadabadi | Peter Blaha | Farhad Jalali-Asadabadi
Source: Scientific Reports (article, 2024-01-05)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Nonzero spontaneous electric polarization in metals: novel predictive methods and applications Ferroelectricity in metals has advanced since the initial discovery of nonmagnetic ferroelectric-like metal LiOsO[Formula: see text], anchored in the Anderson and Blount prediction. However, evaluating the spontaneous electric polarization (SEP) of this metal has been hindered by experimental and theoretical obstacles. The experimental challenge arises from difficulties in switching polarization using an external electric field, while the theoretical limitation lies in existing methods applicable only to nonmetals. Zabalo and Stengel (Phys Rev Lett 126:127601, 2021, https://doi.org/10.1103/PhysRevLett.126.127601 ) addressed the experimental obstacle by proposing flexoelectricity as an alternative for practical polarization switching in LiOsO[Formula: see text], which requires a critical bending radius similar to BaTiO[Formula: see text]. In this study, we focus on resolving the theoretical obstacle by modifying the Berry phase and Wannier functions approaches within density functional theory plus modern theory of polarization. By employing these modifications, we calculate the SEP of LiOsO[Formula: see text], comparable to the polarization of BaTiO[Formula: see text]. We validate our predictions using various ways. This study confirms the coexistence of ferroelectricity and metallicity in this new class of ferroelectric-like metals. Moreover, by addressing the theoretical limitation and providing new insights into polarization properties, our study complements the experimental flexoelectricity proposal and opens avenues for further exploration and manipulation of polarization characteristics. The developed approaches, incorporating modified Berry phase and Wannier function techniques, offer promising opportunities for studying and designing novel materials, including bio- and nano-ferroelectric-like metals. This study contributes to the advancement of ferroelectricity in metals and provides a foundation for future research in this exciting field. Algorithm ; Ferroelectricity ; Polarization (electrochemistry) ; Computer science ; Machine learning ; Materials science ; Physics ; Chemistry ; Quantum mechanics ; Physical chemistry ; Dielectric Multiferroics and related materials ; Ferroelectric and Piezoelectric Materials ; Dielectric properties of ceramics
Authors: Yi Wei | Menglin Song | Lihua Li | Yingjin Ma | Xinyue Lao | Yuan Liu | Guogang Li | Jianhua Hao
Source: Science China Materials (article, 2024-11-12)
Field: Materials Science — Materials Chemistry

Enhanced long-lasting luminescence nanorods for ultrasensitive detection of SARS-CoV-2 N protein Abstract Persistent luminescence nanomaterials can remain luminescence when the light source is turned off, which exhibits promise in biosensor and bioimaging fields since they have the ability to completely eradicate tissue autofluorescence. Although significant progress has been made in the persistent luminescence biosensing, there is still a dearth of long-afterglow detection platform with low limit of detection (LOD) and high sensitivity. Herein, Zn 2 GeO 4 :Mn, Cr persistently luminescent nanorods (PLNRs) with superior persistent luminescence and long afterglow time were developed. The addition of Cr 3+ manifestly improves persistent luminescence intensity and afterglow duration through creating a deep defect trap. Then the biosensors were constructed by combining the Zn 2 GeO 4 :Mn,Cr PLNRs-antibody and Fe 3 O 4 magnetic nanoparticles (MNPs)-antibody for nucleocapsid protein detection based on electrostatic attraction. The LOD value for nucleocapsid protein realizes as low as 39.82 ag/mL, which is much lower than the previously reported persistent luminescent-based biosensors. Accordingly, the low detection sensitivity is attributed to fluorescence resonance energy transfer. In addition, high specificity is also achieved. Therefore, the as-prepared Zn 2 GeO 4 :Mn,Cr persistently luminescent materials can act as the promising candidate in biosensors applications. This strategy provides effective guidance for the development of biosensing platforms with high sensitivity and specificity. Luminescence ; Afterglow ; Biosensor ; Persistent luminescence ; Materials science ; Nanorod ; Detection limit ; Nanotechnology ; Fluorescence ; Nanomaterials ; Nanoparticle ; Optoelectronics ; Chemistry ; Thermoluminescence ; Optics ; Chromatography ; Physics Luminescence Properties of Advanced Materials ; Luminescence and Fluorescent Materials ; Nanoplatforms for cancer theranostics
Authors: Akhil Varghese | Miguel Arana‐Catania | Stefano Mori | Adriana Encinas‐Oropesa | Joy Sumner
Source: Materials and Corrosion (article, 2024-02-12)
Field: Materials Science — Metals and Alloys

Causal discovery to understand hot corrosion Abstract Gas turbine superalloys experience hot corrosion, driven by factors including corrosive deposit flux, temperature, gas composition, and component material. The full mechanism still needs clarification and research often focuses on laboratory work. As such, there is interest in causal discovery to confirm the significance of factors and identify potential missing causal relationships or codependencies between these factors. The causal discovery algorithm fast causal inference (FCI) has been trialled on a small set of laboratory data, with the outputs evaluated for their significance to corrosion propagation, and compared to existing mechanistic understanding. FCI identified salt deposition flux as the most influential corrosion variable for this limited data set. However, HCl was the second most influential for pitting regions, compared to temperature for more uniformly corroding regions. Thus, FCI generated causal links aligned with literature from a randomised corrosion data set, while also identifying the presence of two different degradation modes in operation. Corrosion ; Materials science ; Metallurgy Hydrogen embrittlement and corrosion behaviors in metals ; Corrosion Behavior and Inhibition ; Petroleum Processing and Analysis
Authors: Chao Hu | Xingyan Zhao | Yang Qiu | Shaonan Zheng | Qize Zhong | Yuan Dong | Ting Hu
Source: IEEE photonics journal (article, 2024-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A Computational Microspectrometer Based on Binary-Image-Generated Freeform Metasurfaces for Spectral Sensing In the trend of spectrometer miniaturization, the design of combining computational imaging with the metasurfaces has been proved to be an efficient and feasible solution. Nevertheless, determining the optimal filter array design remains a compelling subject for ongoing research. A computational microspectrometer consisting of a planar array of broadband optical filters is proposed, which are formed by low-loss freeform dielectric metasurfaces. Diverse metasurface designs are obtained by using binary graph generation technology, and rich spectral responses are obtained. The final performance of microspectrometer depends on the trade-offs between reconstruction time, relative error, footprint, and resolution. To optimize these trade-offs, we have improved the existing freeform metasurface design scheme and optimized the filter array design. Simulation results show the proposed microspectrometer can successfully reconstruct the spectra over the 380 to 680 nm spectral range with a resolution of 1 nm. In summary, we propose an integrated design including meta-pixel design, filter combinations and simulation test flow, which leads to an impressive performance microspectrometer. Computer science ; Binary number ; Image (mathematics) ; Computer vision ; Artificial intelligence ; Optics ; Physics ; Mathematics Metamaterials and Metasurfaces Applications ; Optical Wireless Communication Technologies ; Optical and Acousto-Optic Technologies
Authors: Kyle A. Vanderschoot | K. Bender | Christopher M. De | Kelli A. Steineman | Elizabeth K. Neumann
Source: Seminars in Nephrology (review, 2024-11-01)
Field: Chemistry — Spectroscopy

Multimodal Mass Spectrometry Imaging in Atlas Building: A Review Mass spectrometry imaging ; Atlas (anatomy) ; Mass spectrometry ; Chemistry ; Chromatography ; Medicine ; Anatomy Mass Spectrometry Techniques and Applications ; Spectroscopy Techniques in Biomedical and Chemical Research ; Metabolomics and Mass Spectrometry Studies
Authors: Shimeng Kang | Penghui Yao | Zehua Pan | Yuhang Jing | Siyu Liu | Yexin Zhou | Jingyi Wang | Yan Gao | Yi Sun | Yongdan Li | Zheng Zhong
Source: Materials (article, 2024-09-24)
Field: Materials Science — Materials Chemistry

High-Temperature Mechanical–Conductive Behaviors of Proton-Conducting Ceramic Electrolytes in Solid Oxide Fuel Cells Proton-conducting solid oxide fuel cells (P-SOFCs) are widely studied for their lower working temperatures than oxygen-ion-conducting SOFCs (O-SOFCs). Due to the elevated preparation and operation temperatures varying from 500 °C to 1500 °C, high mechanical stresses can be developed in the electrolytes of SOFCs. The stresses will in turn impact the electrical conductivities, which is often omitted in current studies. In this work, the mechanical-conductive behaviors of Y-doped BaZrO<sub>3</sub> (BZY) electrolytes for P-SOFCs under high temperatures are studied through molecular dynamics modeling. The Young's moduli of BZY in fully hydrated and non-hydrated states are calculated with different Y-doping concentrations and at different temperatures. It is shown that Y doping, oxygen vacancies, and protonic point defects all lead to a decrease in the Young's moduli of BZY at 773 K. The variations in the conductivities of BZY are then investigated by calculating the diffusion rates of protons in BZY at different triaxial, biaxial, and uniaxial strains from 673 K to 873 K. In all cases, the diffusion rate present a trend of first increasing and then decreasing from compression state to tension state. The variations in elementary affecting factors of proton diffusion, including hydroxide rotation, proton transfer, proton trapping, and proton distribution, are then analyzed in detail under different strains. It is concluded that the influences of strains on these factors collectively determine the changes in proton conductivity. Materials science ; Electrolyte ; Oxide ; Ceramic ; Proton ; Diffusion ; Conductivity ; Doping ; Electrical conductor ; Chemical physics ; Thermodynamics ; Chemical engineering ; Composite material ; Physical chemistry ; Chemistry ; Electrode ; Metallurgy Advancements in Solid Oxide Fuel Cells ; Chemical Looping and Thermochemical Processes ; Fuel Cells and Related Materials
Authors: Mattew A. Olawumi | Bankole I. Oladapo | Temitope Olumide Olugbade | Francis T. Omigbodun | David B. Olawade
Source: Biomimetics (review, 2024-08-14)
Field: Materials Science — Polymers and Plastics

AI-Driven Data Analysis of Quantifying Environmental Impact and Efficiency of Shape Memory Polymers This research investigates the environmental sustainability and biomedical applications of shape memory polymers (SMPs), focusing on their integration into 4D printing technologies. The objectives include comparing the carbon footprint, embodied energy, and water consumption of SMPs with traditional materials such as metals and conventional polymers and evaluating their potential in medical implants, drug delivery systems, and tissue engineering. The methodology involves a comprehensive literature review and AI-driven data analysis to provide robust, scalable insights into the environmental and functional performance of SMPs. Thermomechanical modeling, phase transformation kinetics, and heat transfer analyses are employed to understand the behavior of SMPs under various conditions. Significant findings reveal that SMPs exhibit considerably lower environmental impacts than traditional materials, reducing greenhouse gas emissions by approximately 40%, water consumption by 30%, and embodied energy by 25%. These polymers also demonstrate superior functionality and adaptability in biomedical applications due to their ability to change shape in response to external stimuli. The study concludes that SMPs are promising sustainable alternatives for biomedical applications, offering enhanced patient outcomes and reduced environmental footprints. Integrating SMPs into 4D printing technologies is poised to revolutionize healthcare manufacturing processes and product life cycles, promoting sustainable and efficient medical practices. Carbon footprint ; Sustainability ; Greenhouse gas ; Embodied energy ; Energy consumption ; Adaptability ; Shape-memory polymer ; Efficient energy use ; Process engineering ; Computer science ; Biochemical engineering ; Materials science ; Nanotechnology ; Environmental science ; Manufacturing engineering ; Engineering ; Shape-memory alloy ; Artificial intelligence Polymer composites and self-healing ; Advanced Materials and Mechanics ; Dielectric materials and actuators
Authors: Sankar V. Harilal | Matilda I. Duffy | Eva Brayfindley | Tatiana G. Levitskaia | Elisabeth Moore | Gregg J. Lumetta | Brienne N. Seiner | Towfiq Ahmed
Source: ACS Omega (article, 2024-12-10)
Field: Chemistry — Inorganic Chemistry

Machine Learning Prediction of Nitric Acid Extraction Behavior in PUREX Process Plutonium uranium reduction extraction (PUREX) is a liquid-liquid extraction process used to recover plutonium (Pu) and uranium (U) from irradiated uranium fuel for various nuclear-related applications. Despite extensive efforts, quantitative prediction of liquid-liquid extraction parameters, i.e., distribution ratios and separation factors, of the process remains challenging. Existing thermodynamic models are difficult to develop and often have limited utility due to the complexity of the aqueous feed. Nitric acid is a critical component of the PUREX system, both as a driving force for dissolving irradiated fuels in preprocessing stages, as well as being efficiently extracted by tributyl phosphate (TBP). Models to understand nitric acid's distribution behavior is therefore a prerequisite to predict actinide extraction. In this work, we compiled a wealth of solvent extraction literature data and built machine learning (ML) models capable of predicting the organic phase nitric acid equilibrium concentration from initial acid and TBP concentrations across a variety of diluents. Our results demonstrate that ML is highly capable of predicting nitric acid extraction behavior in PUREX systems, and the resultant ML-aided response surfaces demonstrate promising progress as an <i>in silico</i> aid for optimizing the design of experiments for future work with the PUREX process. PUREX ; Nitric acid ; Plutonium ; Extraction (chemistry) ; Tributyl phosphate ; Uranium ; Chemistry ; Spent nuclear fuel ; Diluent ; Actinide ; Dissolution ; Nuclear fuel ; Materials science ; Chromatography ; Radiochemistry ; Solvent extraction ; Nuclear chemistry ; Inorganic chemistry ; Organic chemistry ; Metallurgy Radioactive element chemistry and processing ; Nuclear Materials and Properties ; Nuclear reactor physics and engineering
Authors: Samira Zeroual | Saliha Belhouchat | Saad Bouchekioua | Rafik Menacer | Oussama Khaoua | Noura Benbellat | Henry Chermette
Source: ChemistrySelect (article, 2024-10-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Prediction by DFT and Docking Calculations of a Series of Hypothetical 3d Transition Element Isostructural Complexes [M(hfac) <sub>2</sub> (TTF) <sub>2</sub> ]: A Comparative Study Abstract The study aims to predict and compare the structural, electronic, conductivity, and biological properties of a series of 3d transition element complexes with those of the previously studied isostructural copper complex [Cu(hfac) 2 (TTF) 2 ][PF6] 2 (TTF: tetrathiafulvalene, hfac: hexafluoroacetylacetonate). Because transition metals hold open electronic shells, all possible spin states for all divalent compounds have to be considered in order to determine the most stable configurations. These configurations are those corresponding to the highest spin state (5 for Mn, 4 for Fe, 3 for Co, 2 for Ni, 1 for Cu, and 0 for Zn). However, the configurations with the smallest gap are Mn(3) and Co(1), suggesting that these are the most conductive complexes. A significant metal–ligand charge transfer is observed for both Mn and Co complexes. Antifungal (CYP121 (PDB: 2IJ7) and CYP51 (PDB: 1EA1)) and antibacterial ( Escherichia coli (PDB: 1KZN)) properties of the compounds studied were evaluated by molecular docking; the results obtained reveal that the following complexes show significant activity: Zn(hfac) 2 (TTF) 2 ] [PF6] 2 (−8.9 kcal/mol), Ni(hfac) 2 (TTF)2] [PF6] 2 (−7.8 kcal/mol), and Cu(hfac) 2 (TTF) 2 ] [PF6] 2 (−8.2 kcal/mol). Isostructural ; Chemistry ; Crystallography ; Transition metal ; Protein Data Bank (RCSB PDB) ; Divalent ; Electronic structure ; Copper ; Computational chemistry ; Stereochemistry ; Crystal structure ; Organic chemistry Organic and Molecular Conductors Research ; Magnetism in coordination complexes ; Metal complexes synthesis and properties
Authors: Yi-fan Tu | Mei-ying Kwan | Kit‐Lun Yick
Source: Preprints.org (review, 2024-09-19)
Field: Materials Science — Polymers and Plastics

A Systematic Review of AI-Driven Prediction of Fabric Properties and Handfeel Artificial intelligence (AI) is revolutionizing the textile industry by improving the prediction of fabric properties and handfeel, which are essential for assessing textile quality and performance. However, the practical application and translation of AI-predicted results into real-world textile production remain unclear, posing challenges for widespread adoption. This paper systematically reviews AI-driven techniques for predicting these characteristics by focusing on model mechanisms, dataset diversity, and prediction accuracy. Among 811 papers initially identified, 26 were selected for in-depth analysis through both bibliometric and content analysis. The review categorizes and evaluates various AI approaches, including machine learning, deep learning, and hybrid models, across different types of fabric. Despite significant advances, challenges remain, such as ensuring model generalization and managing complex fabric behavior. Future research should focus on developing more robust models, integrating sustainability, and refining feature extraction techniques. This review highlights the critical gaps in the literature and provides practical insights to enhance AI-driven prediction of fabric properties, thus guiding future textile innovations. Artificial intelligence ; Computer science Textile materials and evaluations ; Industrial Vision Systems and Defect Detection ; Color perception and design
Authors: William Trey Harris | Isabelle Altieri | Isabella Gieck | R. Jeremy Johnson
Source: Proteins Structure Function and Bioinformatics (article, 2024-01-05)
Field: Materials Science — Materials Chemistry

A conserved but structurally divergent loop in acyl protein thioesterase 1 regulates its catalytic activity, ligand binding, and folded stability Human acyl protein thioesterases (APTs) catalyze the depalmitoylation of S-acylated proteins attached to the plasma membrane, facilitating reversible cycles of membrane anchoring and detachment. We previously showed that a bacterial APT homologue, FTT258 from the gram-negative pathogen Francisella tularensis, exists in equilibrium between a closed and open state based on the structural dynamics of a flexible loop overlapping its active site. Although the structural dynamics of this loop are not conserved in human APTs, the amino acid sequence of this loop is highly conserved, indicating essential but divergent functions for this loop in human APTs. Herein, we investigated the role of this loop in regulating the catalytic activity, ligand binding, and protein folding of human APT1, a depalmitoylase connected with cancer, immune, and neurological signaling. Using a combination of substitutional analysis with kinetic, structural, and biophysical characterization, we show that even in its divergent structural location in human APT1 that this loop still regulates the catalytic activity of APT1 through contributions to ligand binding and substrate positioning. We confirmed previously known roles for multiple residues (Phe72 and Ile74) in substrate binding and catalysis while adding new roles in substrate selectivity (Pro69), in catalytic stabilization (Asp73 and Ile75), and in transitioning between the membrane binding β-tongue and substrate-binding loops (Trp71). Even conservative substitution of this tryptophan (Trp71) fulcrum led to complete loss of catalytic activity, a 13°C decrease in total protein stability, and drastic drops in ligand affinity, indicating that the combination of the size, shape, and aromaticity of Trp71 are essential to the proper structure of APT1. Mixing buried hydrophobic surface area with contributions to an exposed secondary surface pocket, Trp71 represents a previously unidentified class of essential tryptophans within α/β hydrolase structure and a potential allosteric binding site within human APTs. Ligand (biochemistry) ; Active site ; Chemistry ; Biochemistry ; Protein structure ; Biophysics ; Binding site ; Tryptophan ; Amino acid ; Stereochemistry ; Biology ; Catalysis ; Receptor Enzyme Structure and Function ; Protein Kinase Regulation and GTPase Signaling ; Cellular transport and secretion