jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Xuyang Zhou | Prince Mathews | Benjamin Berkels | Wassilios J. Delis | Saba Ahmad | Amel Shamseldeen Ali Alhassan | Philipp Keuter | Jochen M. Schneider | Sandra Korte‐Kerzel | Stefanie Sandlöbes | Dierk Raabe | Jörg Neugebauer | Gerhard Dehm | Tilmann Hickel | Christina Scheu | Siyuan Zhang
Source: Advanced Materials (article, 2024-11-17)
Field: Materials Science — Biomaterials

Materials Design by Constructing Phase Diagrams for Defects Phase transformations and crystallographic defects are two essential tools to drive innovations in materials. Bulk materials design via tuning chemical compositions is systematized using phase diagrams. It is shown here that the same thermodynamic concept can be applied to manipulate the chemistry at defects. Grain boundaries in Mg-Ga system are chosen as a model system, because Ga segregates to the boundaries, while simultaneously improving the strength and ductility of Mg alloys. To reveal the role of grain boundaries, correlated atomic-scale characterization and simulation to scope and build phase diagrams for defects are presented. The discovery is enabled by triggering phase transformations of individual grain boundaries through local alloying, and sequentially imaging the structural and chemical changes using atomic-resolution scanning transmission electron microscopy. Ab initio simulations determined the thermodynamic stability of grain boundary phases, and found out that increasing Ga content enhances grain boundary cohesion, relating to improved ductility. The methodology to trigger, trace, and simulate defect transformation at atomic resolution enables a systematic development of defect phase diagrams, providing a valuable tool to utilize chemical complexity and phase transformations at defects. Materials science ; Grain boundary ; Atomic units ; Phase diagram ; Ductility (Earth science) ; CALPHAD ; Phase (matter) ; Nanoscopic scale ; Chemical physics ; Nanotechnology ; Metallurgy ; Microstructure ; Chemistry Magnesium Alloys: Properties and Applications ; Microstructure and mechanical properties ; Aluminum Alloy Microstructure Properties
Authors: Anton M. Kuzmin | Alireza Ashori | P. V. Pantyukhov | Yonghui Zhou | Litao Guan | Chuanshuang Hu
Source: Scientific Reports (article, 2024-10-24)
Field: Materials Science — Polymers and Plastics

Mechanical, thermal, and water absorption properties of HDPE/barley straw composites incorporating waste rubber This study investigates the mechanical, thermal, and water absorption properties of high-density polyethylene (HDPE) composites filled with barley straw and varying amounts of waste rubber. The research aims to develop sustainable materials that repurpose agricultural and industrial waste while addressing resource scarcity and waste management challenges. Composites were prepared using a twin-rotor mixer and hydraulic press, with waste rubber content varying from 0 to 20 wt%. Mechanical properties were evaluated through tensile testing, thermal behavior was analyzed using TGA, DTG, and DSC, and long-term water absorption was measured. Results show that increasing waste rubber content from 0 to 20% led to a decrease in tensile strength (11.3 to 8.9 MPa) and tensile modulus (1760 to 790 MPa), while relative extension increased (2.4-5.9%). Thermal analysis revealed a slight reduction in onset degradation temperature (270 °C to 240 °C) and increased char residue (8-18%) with higher rubber content. Water absorption decreased significantly, from 12 to 13% to 6-7% after 600 h of immersion, as waste rubber content increased. These findings demonstrate that incorporating waste rubber into HDPE/barley straw composites results in materials with enhanced flexibility and water resistance at the cost of some strength and stiffness. In conclusion, the results of this study offer a clear pathway for the development of sustainable polymer composites that have broad potential applications across industries like construction, marine infrastructure, automotive, and packaging. By replacing traditional, resource-intensive materials with eco-friendly alternatives, these composites not only provide functional benefits but also support global efforts toward sustainable development and environmental conservation. Absorption of water ; Straw ; Composite material ; Natural rubber ; Materials science ; High-density polyethylene ; Thermal ; Absorption (acoustics) ; Polyethylene ; Agronomy ; Biology Natural Fiber Reinforced Composites ; biodegradable polymer synthesis and properties ; Fiber-reinforced polymer composites
Authors: Peng Huang | Jinfu Yuan | Pan Yang | Futong Xiao | Yongpeng Zhao
Source: Foods (article, 2024-04-25)
Field: Chemistry — Analytical Chemistry

Nondestructive Detection of Sunflower Seed Vigor and Moisture Content Based on Hyperspectral Imaging and Chemometrics Sunflower is an important crop, and the vitality and moisture content of sunflower seeds have an important influence on the sunflower's planting and yield. By employing hyperspectral technology, the spectral characteristics of sunflower seeds within the wavelength range of 384-1034 nm were carefully analyzed with the aim of achieving effective prediction of seed vitality and moisture content. Firstly, the original hyperspectral data were subjected to preprocessing techniques such as Savitzky-Golay smoothing, standard normal variable correction (SNV), and multiplicative scatter correction (MSC) to effectively reduce noise interference, ensuring the accuracy and reliability of the data. Subsequently, principal component analysis (PCA), extreme gradient boosting (XGBoost), and stacked autoencoders (SAE) were utilized to extract key feature bands, enhancing the interpretability and predictive performance of the data. During the modeling phase, random forests (RFs) and LightGBM algorithms were separately employed to construct classification models for seed vitality and prediction models for moisture content. The experimental results demonstrated that the SG-SAE-LightGBM model exhibited outstanding performance in the classification task of sunflower seed vitality, achieving an accuracy rate of 98.65%. Meanwhile, the SNV-XGBoost-LightGBM model showed remarkable achievement in moisture content prediction, with a coefficient of determination (R2) of 0.9715 and root mean square error (RMSE) of 0.8349. In conclusion, this study confirms that the fusion of hyperspectral technology and multivariate data analysis algorithms enables the accurate and rapid assessment of sunflower seed vitality and moisture content, providing robust tools and theoretical support for seed quality evaluation and agricultural production practices. Furthermore, this research not only expands the application of hyperspectral technology in unraveling the intrinsic vitality characteristics of sunflower seeds but also possesses significant theoretical and practical value. Hyperspectral imaging ; Sunflower ; Mathematics ; Principal component analysis ; Mean squared error ; Sunflower seed ; Sowing ; Artificial intelligence ; Water content ; Remote sensing ; Pattern recognition (psychology) ; Machine learning ; Computer science ; Statistics ; Agronomy ; Engineering ; Geography Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Water Quality Monitoring and Analysis
Authors: Russell R. Kibbe | David C. Muddiman
Source: Journal of Mass Spectrometry (article, 2024-03-15)
Field: Chemistry — Spectroscopy

Quantitative mass spectrometry imaging (qMSI): A tutorial Mass spectrometry imaging (MSI) is an analytical technique that enables the simultaneous detection of hundreds to thousands of chemical species while retaining their spatial information; usually, MSI is applied to biological tissues. Combining these elements can create ion images, which allows for the identification and localization of multiple chemical species within the sample. Being able to produce molecular images of biological tissues has already impacted the study of health and disease; however, the next logical step is being able to combine MSI with quantitative mass spectrometry methods to both quantify and determine the localization of disease progression or drug action. In this tutorial, we will detail the main factors to consider when designing a qMSI experiment and highlight the methods that have been developed to overcome these added complexities, specifically for those newer to the field of MSI. Chemistry ; Mass spectrometry imaging ; Mass spectrometry ; Identification (biology) ; Computational biology ; Field (mathematics) ; Biological system ; Biochemical engineering ; Chromatography Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Analytical Chemistry and Chromatography
Authors: Maria Lucimar da Silva Medeiros | Leila Moreira de Carvalho | Marta Suely Madruga | Francisco J. Rodríguez‐Pulido | Francisco J. Heredia | Douglas Fernandes Barbin
Source: Food Research International (article, 2024-03-15)
Field: Chemistry — Analytical Chemistry

Comparison of hyperspectral imaging and spectrometers for prediction of cheeses composition Partial least squares regression ; Hyperspectral imaging ; Principal component analysis ; Chemometrics ; Near-infrared spectroscopy ; Linear discriminant analysis ; Spectrometer ; Chemistry ; Chemical composition ; Composition (language) ; Pattern recognition (psychology) ; Food science ; Mathematics ; Artificial intelligence ; Statistics ; Computer science ; Chromatography ; Optics Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Advanced Chemical Sensor Technologies
Authors: Yanan Lu | Dabao Xie | Congmin Zhang | Dan Cao | Xiaoshuang Chen | Haibo Shu
Source: Advanced Electronic Materials (article, 2024-06-16)
Field: Materials Science — Materials Chemistry

Band Alignment Engineering in 2D Ferroelectric Van der Waals Heterostructures for All‐In‐One Optoelectronic Architecture Abstract 2D van der Waals (vdW) heterostructures consisting of vertically stacking atomically thin semiconductors with different band structures provide a flexible platform to design integrated electronic and optoelectronic devices with multi‐functionalities. However, the realization of device multifunctionality requires the heterostructures with tunable band alignments. Here an efficient strategy is proposed by constructing 2D vdW ferroelectric semiconductor heterostructures composed of atomically thin ferroelectrics and semiconductors to achieve this goal. These calculated results indicate that the local built‐in electric field derived from the ferroelectric polarization can effectively modulate the band alignment of the heterostructures, leading to 36 potential band‐alignment transition pathways. Using SnS/In 2 Se 3 vdW heterostructure as a prototype example, a reversible switching from high‐resistance to low‐resistance state is demonstrated by the band‐alignment transition from type‐II to type‐III driven by ferroelecric polarization switching, consequently leading to giant tunneling electroresistance (TER) ratio as high as 10 12 %. Moreover, the heterostructure with the momentum‐space matching band structure and in‐plane anisotropy exhibits broadband photoresponse from near‐infrared to ultraviolet regions and excellent polarization sensitivity with the dichroic ratio up to 10.3. The ferroelectric polarization‐dependent conductance state and photoresponse in the heterostructures make them large potential for the realization of all‐in‐one optoelectronic architecture in artificial vision system. Materials science ; Heterojunction ; van der Waals force ; Optoelectronics ; Ferroelectricity ; Nanotechnology ; Dielectric ; Molecule ; Physics ; Quantum mechanics 2D Materials and Applications ; Perovskite Materials and Applications ; Nanowire Synthesis and Applications
Authors: Jin Wang | Xiangrong Song | Meidan Wei | Lexin Qin | Qingyun Zhu | Shujie Wang | Tingting Liang | Wentao Hu | Xinyu Zhu | Jianxiang Li
Source: International Journal of Molecular Sciences (article, 2024-06-18)
Field: Chemistry — Spectroscopy

PCAS: An Integrated Tool for Multi-Dimensional Cancer Research Utilizing Clinical Proteomic Tumor Analysis Consortium Data Proteomics offers a robust method for quantifying proteins and elucidating their roles in cellular functions, surpassing the insights provided by transcriptomics. The Clinical Proteomic Tumor Analysis Consortium database, enriched with comprehensive cancer proteomics data including phosphorylation and ubiquitination profiles, alongside transcriptomics data from the Genomic Data Commons, allow for integrative molecular studies of cancer. The ProteoCancer Analysis Suite (PCAS), our newly developed R package and Shinyapp, leverages these resources to facilitate in-depth analyses of proteomics, phosphoproteomics, and transcriptomics, enhancing our understanding of the tumor microenvironment through features like immune infiltration and drug sensitivity analysis. This tool aids in identifying critical signaling pathways and therapeutic targets, particularly through its detailed phosphoproteomic analysis. To demonstrate the functionality of the PCAS, we conducted an analysis of GAPDH across multiple cancer types, revealing a significant upregulation of protein levels, which is consistent with its important biological and clinical significance in tumors, as indicated in our prior research. Further experiments were used to validate the findings performed using the tool. In conclusion, the PCAS is a powerful and valuable tool for conducting comprehensive proteomic analyses, significantly enhancing our ability to uncover oncogenic mechanisms and identify potential therapeutic targets in cancer research. Phosphoproteomics ; Proteomics ; Computational biology ; Biology ; Cancer biomarkers ; Proteome ; Transcriptome ; Quantitative proteomics ; Cancer ; Bioinformatics ; Protein phosphorylation ; Phosphorylation ; Gene ; Gene expression ; Protein kinase A ; Genetics Advanced Proteomics Techniques and Applications ; Ubiquitin and proteasome pathways ; Ferroptosis and cancer prognosis
Authors: Qiqi Liu | Chunyu Wang | Mingsheng Zhu | Jinming Liu | Qiannan Duan | Adam C. Midgley | Ruming Liu | Bing Jiang | Deling Kong | Quan Chen | Jie Zhuang | Xinglu Huang
Source: Advanced Science (article, 2024-02-17)
Field: Materials Science — Biomaterials

Self‐Assembly of Heterogeneous Ferritin Nanocages for Tumor Uptake and Penetration Well-defined nanostructures are crucial for precisely understanding nano-bio interactions. However, nanoparticles (NPs) fabricated through conventional synthesis approaches often lack poor controllability and reproducibility. Herein, a synthetic biology-based strategy is introduced to fabricate uniformly reproducible protein-based NPs, achieving precise control over heterogeneous components of the NPs. Specifically, a ferritin assembly toolbox system is developed that enables intracellular assembly of ferritin subunits/variants in Escherichia coli. Using this strategy, a proof-of-concept study is provided to explore the interplay between ligand density of NPs and their tumor targets/penetration. Various ferritin hybrid nanocages (FHn) containing human ferritin heavy chains (FH) and light chains are accurately assembled, leveraging their intrinsic binding with tumor cells and prolonged circulation time in blood, respectively. Further studies reveal that tumor cell uptake is FH density-dependent through active binding with transferrin receptor 1, whereas in vivo tumor accumulation and tissue penetration are found to be correlated to heterogeneous assembly of FHn and vascular permeability of tumors. Densities of 3.7 FH/100 nm<sup>2</sup> on the nanoparticle surface exhibit the highest degree of tumor accumulation and penetration, particularly in tumors with high permeability compared to those with low permeability. This study underscores the significance of nanoparticle heterogeneity in determining particle fate in biological systems. Nanocages ; Ferritin ; Penetration (warfare) ; Nanotechnology ; Materials science ; Chemistry ; Biochemistry ; Engineering Nanoparticle-Based Drug Delivery ; Advanced biosensing and bioanalysis techniques ; RNA Interference and Gene Delivery
Authors: Hang Xue | Xiping Xu | Yang Yang | Dongmei Hu | Guocheng Niu
Source: Sensors (article, 2024-03-14)
Field: Chemistry — Analytical Chemistry

Rapid and Non-Destructive Prediction of Moisture Content in Maize Seeds Using Hyperspectral Imaging The moisture content of corn seeds is a crucial indicator for evaluating seed quality and is also a fundamental aspect of grain testing. In this experiment, 80 corn samples of various varieties were selected and their moisture content was determined using the direct drying method. The hyperspectral imaging system was employed to capture the spectral images of corn seeds within the wavelength range of 1100-2498 nm. By utilizing seven preprocessing techniques, including moving average, S-G smoothing, baseline, normalization, SNV, MSC, and detrending, we preprocessed the spectral data and then established a PLSR model for comparison. The results show that the model established using the normalization preprocessing method has the best prediction performance. To remove spectral redundancy and simplify the prediction model, we utilized SPA, CASR, and UVE algorithms to extract feature wavelengths. Based on three algorithms (PLSR, PCR, and SVM), we constructed 12 predictive models. Upon evaluating these models, it was determined that the normalization-SPA-PLSR algorithm produced the most accurate prediction. This model boasts high RC2 and RP2 values of 0.9917 and 0.9914, respectively, along with low RMSEP and RMSECV values of 0.0343 and 0.0257, respectively, indicating its exceptional stability and predictive capabilities. This suggests that the model can precisely estimate the moisture content of maize seeds. The results showed that hyperspectral imaging technology provides technical support for rapid and non-destructive prediction of corn seed moisture content and new methods in seed quality evaluation. Hyperspectral imaging ; Normalization (sociology) ; Water content ; Preprocessor ; Partial least squares regression ; Smoothing ; Mathematics ; Cross-validation ; Pattern recognition (psychology) ; Biological system ; Artificial intelligence ; Remote sensing ; Computer science ; Statistics ; Engineering Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Remote Sensing in Agriculture
Authors: Ying Li | Yong Shi | Ding Luo | Xuehui Wang | Yuying Yan
Source: Applied Thermal Engineering (article, 2024-03-05)
Field: Materials Science — Materials Chemistry

Impacts of distributed thermal and electric contact resistance on performance and geometric optimization of thermoelectric generators Thermal and electric contact resistance (TCR/ECR) critically impact performance and geometric optimization of thermoelectric generators (TEGs). However, conventional treatments usually ignored or simplified them as lumped variables, neglecting their actual distributions across the TEG system. In this study, we proposed a multi-physical model to characterize TEG performance with explicitly specifying TCRs/ECRs at different TEG interfaces (locations). The numerical results show that conventional treatment led to maximal overestimations of 16.9 % and 24.5 % in the TEG output power and efficiency, respectively, compared to the results with distributed TCR in this article. Importantly, it also reveals that the TEG performance was susceptible to the TCR location—the interfaces on the cold side exerted more negative impacts than those on the hot side. Furthermore, reducing both TCR and ECR could improve TEG performance and reducing TCR is more effective. It is shown that an 80 % reduction in TCR increased the maximum TEG output power by 35.6 %, while the same reduction percentage in ECR only improved it by 8.8 %. As to geometric optimization, an optimal TE leg height equal to 0.6 mm was obtained for the maximum output power. This contrasts with previous studies without considering TCR and ECR, which always favoured shorter heights. As for copper electrodes, their optimal heights were in the range of 0.2–0.4 mm corresponding to the maximum efficiency, far smaller than those (0.7–1.2 mm) obtained when TCR/ECR were neglected. The latter even further resulted in a reduction in the maximum efficiency by more than 1 % compared to its true peak. In this study, all these numerical results clearly elucidate the important impacts of distributed TCR and ECR on TEG performance, and provide a comprehensive and balanced guideline for TEG design. Thermoelectric effect ; Thermoelectric generator ; Materials science ; T-cell receptor ; Thermal ; Reduction (mathematics) ; Power (physics) ; Electrode ; Range (aeronautics) ; Mathematics ; Automotive engineering ; Mechanics ; Electrical engineering ; Physics ; Thermodynamics ; Geometry ; Composite material ; Engineering ; T cell Advanced Thermoelectric Materials and Devices ; Thermal properties of materials ; Thermal Radiation and Cooling Technologies
Authors: Weichen Li | Ole Sigmund | Xiaojia Shelly Zhang
Source: Nature Communications (article, 2024-07-15)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Analytical realization of complex thermal meta-devices Fourier's law dictates that heat flows from warm to cold. Nevertheless, devices can be tailored to cloak obstacles or even reverse the heat flow. Mathematical transformation yields closed-form equations for graded, highly anisotropic thermal metamaterial distributions needed for obtaining such functionalities. For simple geometries, devices can be realized by regular conductor distributions; however, for complex geometries, physical realizations have so far been challenging, and sub-optimal solutions have been obtained by expensive numerical approaches. Here we suggest a straightforward and highly efficient analytical de-homogenization approach that uses optimal multi-rank laminates to provide closed-form solutions for any imaginable thermal manipulation device. We create thermal cloaks, rotators, and concentrators in complex domains with close-to-optimal performance and esthetic elegance. The devices are fabricated using metal 3D printing, and their omnidirectional thermal functionalities are investigated numerically and validated experimentally. The analytical approach enables next-generation free-form thermal meta-devices with efficient synthesis, near-optimal performance, and concise patterns. Metamaterial ; Cloak ; Homogenization (climate) ; Thermal ; Computer science ; Realization (probability) ; Cloaking ; Transformation optics ; Microscale chemistry ; Thermal insulation ; Thermal conduction ; Mechanical engineering ; Materials science ; Optoelectronics ; Physics ; Nanotechnology ; Mathematics Metamaterials and Metasurfaces Applications ; Thermal Radiation and Cooling Technologies ; Advanced Materials and Mechanics