jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Carmen Ballester | Dorin Copaci | Janeth Arias Guadalupe | Luís Moreno | Dolores Blanco
Source: Actuators (article, 2023-04-04)
Field: Materials Science — Materials Chemistry

Hoist-Based Shape Memory Alloy Actuator with Multiple Wires for High-Displacement Applications Shape memory alloys (SMAs) are smart materials that change their crystalline structures when subjected to heat or tension, resulting in a macroscopic deformation. When applied to actuators, SMAs present a remarkable load–weight ratio and flexibility, making them suitable for diverse applications. However, challenges such as their energy consumption, nonlinear control, and low displacement must be considered. This paper presents a new strategy for improving the total displacement while adding neither supplementary SMA wires nor complex external devices. In addition, a novel control strategy is proposed to improve the nonlinearity of SMAs’ behavior. A hoist system was developed to linearly increase the displacement with the number of pulleys and wire turns used. The design also used parallel actuation to increase the load capacity. The actuator presented a high load capacity with reduced weight, lifting more than 100 times its own mass, with a low-cost and robust external system. The simplicity of the actuator’s control and production and its lightness make it a suitable option for a wide range of applications, including wearable exoskeletons. Actuator ; Shape-memory alloy ; Pulley ; Displacement (psychology) ; SMA* ; Mechanical engineering ; Nonlinear system ; Materials science ; Computer science ; Structural engineering ; Control theory (sociology) ; Engineering ; Composite material ; Physics ; Control (management) Shape Memory Alloy Transformations ; Structural Engineering and Vibration Analysis
Authors: Olayemi Joshua Ibidoja | Fam Pei Shan | Mukhtar Mukhtar | Jumat Sulaiman | Majid Khan Majahar Ali
Source: Journal of the Nigerian Society of Physical Sciences (article, 2023-02-04)
Field: Chemistry — Analytical Chemistry

Robust M-estimators and Machine Learning Algorithms for Improving the Predictive Accuracy of Seaweed Contaminated Big Data A common problem in regression analysis using ordinary least squares (OLS) is the effect of outliers or contaminated data on the estimates of the parameters. A robust method that is not sensitive to outliers and can handle contaminated data is needed. In this study, the objective is to determine the significant parameters that determine the moisture content of the seaweed after drying and develop a hybrid model to reduce the outliers. The data were collected with sensors from the v-Groove Hybrid Solar Drier (v-GHSD) at Semporna, South-Eastern Coast of Sabah, Malaysia. After the second order interaction, we have 435 drying parameters, each parameter has 1914 observations. First, we used four machine learning algorithms, such as random forest, support vector machine, bagging and boosting to determine the significant parameters by selecting 15, 25, 35 and 45 parameters. Second, we developed the hybrid model using robust methods such as M. Bi-Square, M. Hampel and M. Huber. The results show that there is a significant improvement in the reduction of the number of outliers and better prediction using hybrid model for the contaminated seaweed big data. For the highest variable importance of 45 significant drying parameters of seaweed, the hybrid model bagging M Bi-square performs better because it has the lowest percentage of outliers of 4.08 %. Outlier ; Support vector machine ; Algorithm ; Random forest ; Boosting (machine learning) ; Statistics ; Machine learning ; Ordinary least squares ; Mathematics ; Mean squared error ; Computer science ; Artificial intelligence Spectroscopy and Chemometric Analyses ; Advanced Statistical Methods and Models ; Fault Detection and Control Systems
Authors: Mu’ayyad M. Al-Shrida | Mohammed T. Hayajneh | Faris M. AL‐Oqla
Source: Materials Research (article, 2023-01-01)
Field: Materials Science — Polymers and Plastics

Modeling and Investigation of the Influential Reinforcement Parameters on the Strength of Polypropylene Lignocellulosic Fiber Composites Using Analysis of Variances and Box-Cox Transformation Technique Green materials have received great interest in wide industrial applications due to their desired properties. However, the reinforcing conditions have a significant impact on how they perform in their final use. The current study intends to statistically examine the effects of three key parameters on the average tensile strength of polypropylene composites. These factors included the type of fiber, the chemical treatment, and the fiber's weight percentage. The fibers were hemp and sisal, and the weight percentages were 10, 20, and 30. While some of them received sodium hydroxide (NaOH) treatment, the rest were left untreated. The main effect and the interaction effect were both examined using the analysis of variance (ANOVA). The findings demonstrated that, on average, the weight percentage had no tangible effect on the tensile strength of polypropylene (PP) composites. Additionally, the performance of sisal and hemp composites was unaffected by treatment. The strength, however, is significantly influenced by the type of fiber. The investigation also showed that there was little difference between untreated hemp and untreated sisal in terms of tensile strength. SISAL ; Ultimate tensile strength ; Composite material ; Polypropylene ; Materials science ; Fiber ; Sodium hydroxide ; Izod impact strength test ; Chemistry Natural Fiber Reinforced Composites ; Nanocomposite Films for Food Packaging ; Advanced Cellulose Research Studies
Authors: Hao‐Cheng Weng | Jorge Monroy-Ruz | Jonathan C. F. Matthews | John Rarity | Krishna C. Balram | Joe A. Smith
Source: ACS Photonics (article, 2023-08-31)
Field: Materials Science — Materials Chemistry

Heterogeneous Integration of Solid-State Quantum Systems with a Foundry Photonics Platform Diamond color centers are promising optically addressable solid-state spins that can be matter-qubits, mediate deterministic interaction between photons, and act as single photon emitters. Useful quantum computers will comprise millions of logical qubits. To become useful in constructing quantum computers, spin-photon interfaces must, therefore, become scalable and be compatible with mass-manufacturable photonics and electronics. Here, we demonstrate the heterogeneous integration of NV centers in nanodiamond with low-fluorescence silicon nitride photonics from a standard 180 nm CMOS foundry process. Nanodiamonds are positioned over predefined sites in a regular array on a waveguide in a single postprocessing step. Using an array of optical fibers, we excite NV centers selectively from an array of six integrated nanodiamond sites and collect the photoluminescence (PL) in each case into waveguide circuitry on-chip. We verify single photon emission by an on-chip Hanbury Brown and Twiss cross-correlation measurement, which is a key characterization experiment otherwise typically performed routinely with discrete optics. Our work opens up a simple and effective route to simultaneously address large arrays of individual optically active spins at scale, without requiring discrete bulk optical setups. This is enabled by the heterogeneous integration of NV center nanodiamonds with CMOS photonics. Photonics ; Qubit ; Photon ; Nanodiamond ; Optoelectronics ; Physics ; Waveguide ; Spins ; Silicon photonics ; Quantum optics ; Quantum dot ; Nanotechnology ; Quantum ; Materials science ; Optics ; Diamond ; Quantum mechanics Diamond and Carbon-based Materials Research ; Advanced Fiber Laser Technologies ; Force Microscopy Techniques and Applications
Authors: Marek Hawryluk | Marzena Lachowicz | A. Łukaszek-Sołek | Łukasz Lisiecki | Grzegorz Ficak | Piotr Cygan
Source: Materials (article, 2023-06-07)
Field: Materials Science — Materials Chemistry

Structural Features of Fatigue Crack Propagation of a Forging Die Made of Chromium–Molybdenum–Vanadium Tool Steel on Its Durability The paper presents the results of tests on a die insert made of non-standardised chrome-molybdenum–vanadium tool steel used during pre-forging, the life of which was 6000 forgings, while the average life for such tools is 8000 forgings. It was withdrawn from production due to intensive wear and premature breakage. In order to determine the causes of increased tool wear, a comprehensive analysis was carried out, including 3D scanning of the working surface; numerical simulations, with particular emphasis on cracking (according to the C-L criterion); and fractographic and microstructural tests. The results of numerical modelling in conjunction with the obtained results of structural tests allowed us to determine the causes of cracks in the working area of the die, which were caused by high cyclical thermal and mechanical loads and abrasive wear due to intensive flow of the forging material. It was found that the resulting fracture initiated as a multi-centric fatigue fracture continued to develop as a multifaceted brittle fracture with numerous secondary faults. Microscopic examinations allowed us to evaluate the wear mechanisms of the insert, which included plastic deformation and abrasive wear, as well as thermo-mechanical fatigue. As part of the work carried out, directions for further research were also proposed to improve the durability of the tested tool. In addition, the observed high tendency to cracking of the tool material used, based on impact tests and determination of the K1C fracture toughness factor, led to the proposal of an alternative material characterised by higher impact strength. Forging ; Durability ; Materials science ; Abrasive ; Metallurgy ; Fracture toughness ; Brittleness ; Die (integrated circuit) ; Vanadium ; Fracture (geology) ; Hot work ; Composite material ; Tool steel Metal Alloys Wear and Properties ; Metallurgy and Material Forming ; Microstructure and Mechanical Properties of Steels
Authors: Benjamin Ducharne | Yves Armand Tene Deffo | Shurui Zhang | Gaël Sebald | Mickaël Lallart | Tetsuya Uchimoto | Christophe Gallais | Olivier Ghibaudo
Source: NDT & E International (article, 2023-04-26)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Carburization depth evaluation from magnetic nondestructive testing Materials science ; Amplitude ; Nondestructive testing ; Excitation ; Permeability (electromagnetism) ; Coercivity ; Penetration depth ; Destructive testing ; Magnetization ; Rod ; Magnetic field ; Composite material ; Nuclear magnetic resonance ; Condensed matter physics ; Engineering ; Optics ; Physics ; Electrical engineering ; Materials testing ; Chemistry Magnetic Properties and Applications ; Microstructure and Mechanical Properties of Steels ; Non-Destructive Testing Techniques
Authors: Andreas Møller Slavensky | Mads-Peter Verner Christiansen | Bjørk Hammer
Source: The Journal of Chemical Physics (article, 2023-07-11)
Field: Materials Science — Materials Chemistry

Generating candidates in global optimization algorithms using complementary energy landscapes Global optimization of atomistic structure relies on the generation of new candidate structures in order to drive the exploration of the potential energy surface (PES) in search of the global minimum energy structure. In this work, we discuss a type of structure generation, which locally optimizes structures in complementary energy (CE) landscapes. These landscapes are formulated temporarily during the searches as machine learned potentials (MLPs) using local atomistic environments sampled from collected data. The CE landscapes are deliberately incomplete MLPs that rather than mimicking every aspect of the true PES are sought to become much smoother, having only a few local minima. This means that local optimization in the CE landscapes may facilitate the identification of new funnels in the true PES. We discuss how to construct the CE landscapes and we test their influence on the global optimization of a reduced rutile SnO2(110)-(4 × 1) surface and an olivine (Mg2SiO4)4 cluster for which we report a new global minimum energy structure. Maxima and minima ; Global optimization ; Energy landscape ; Potential energy surface ; Computer science ; Energy minimization ; Energy (signal processing) ; Identification (biology) ; Algorithm ; Construct (python library) ; Mathematical optimization ; Surface (topology) ; Optimization problem ; Work (physics) ; Mathematics ; Physics ; Geometry ; Chemistry ; Computational chemistry ; Biology Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Crystallography and molecular interactions
Authors: Marvin P. Bernhardt | Martin Hanke | Nico F. A. van der Vegt
Source: Journal of Chemical Theory and Computation (article, 2023-01-11)
Field: Materials Science — Materials Chemistry

Stability, Speed, and Constraints for Structural Coarse-Graining in VOTCA Structural coarse-graining involves the inverse problem of deriving pair potentials that reproduce target radial distribution functions. Despite its clear mathematical formulation, there are open questions about the existing methods concerning speed, stability, and physical representability of the resulting potentials. In this work, we make progress on several aspects of iterative methods used to solve the inverse problem. Based on integral equation theory, we derive fast Gauss–Newton schemes applicable to very general systems, including molecules with bonds and mixtures. Our methods are similar to inverse Monte Carlo in terms of convergence speed and have a similar cost per iteration as iterative Boltzmann inversion. We investigate stability problems in our schemes and in the inverse Monte Carlo method and propose modifications to fix them. Furthermore, we establish how the pair potential can be constrained at each iteration to reproduce the pressure, Kirkwood–Buff integral, or the enthalpy of vaporization. We demonstrate the potential of our approach in deriving coarse-grained force fields for nine different solvents and their mixtures. All methods described are implemented in the free and open VOTCA software framework for systematic coarse-graining. Granularity ; Computer science ; Monte Carlo method ; Stability (learning theory) ; Inverse ; Convergence (economics) ; Inverse problem ; Applied mathematics ; Statistical physics ; Mathematical optimization ; Iterative method ; Work (physics) ; Mathematics ; Algorithm ; Physics ; Mathematical analysis ; Thermodynamics Machine Learning in Materials Science ; Phase Equilibria and Thermodynamics ; Block Copolymer Self-Assembly
Authors: Qianfan Liu | Yu Zhang | Jing Chen | Chengxu Sun | Mengxing Huang | Mingwei Che | Chun Li | Shenghuang Lin
Source: Frontiers in Plant Science (article, 2023-12-08)
Field: Chemistry — Inorganic Chemistry

An improved Deeplab V3+ network based coconut CT image segmentation method Due to the unique structure of coconuts, their cultivation heavily relies on manual experience, making it difficult to accurately and timely observe their internal characteristics. This limitation severely hinders the optimization of coconut breeding. To address this issue, we propose a new model based on the improved architecture of Deeplab V3+. We replace the original ASPP(Atrous Spatial Pyramid Pooling) structure with a dense atrous spatial pyramid pooling module and introduce CBAM(Convolutional Block Attention Module). This approach resolves the issue of information loss due to sparse sampling and effectively captures global features. Additionally, we embed a RRM(residual refinement module) after the output level of the decoder to optimize boundary information between organs. Multiple model comparisons and ablation experiments are conducted, demonstrating that the improved segmentation algorithm achieves higher accuracy when dealing with diverse coconut organ CT(Computed Tomography) images. Our work provides a new solution for accurately segmenting internal coconut organs, which facilitates scientific decision-making for coconut researchers at different stages of growth. Pooling ; Pyramid (geometry) ; Computer science ; Segmentation ; Block (permutation group theory) ; Artificial intelligence ; Residual ; Pattern recognition (psychology) ; Algorithm ; Mathematics Coconut Research and Applications ; Advanced Neural Network Applications
Authors: Nikola Đorđević | Clemens Dierks | Essi Hantikainen | Vadim Farztdinov | Fatma Amari | Vinicius Verri Hernandes | Alessandro De Grandi | Francisco S. Domingues | Michael Mülleder | Peter P. Pramstaller | Johannes Rainer | Markus Ralser
Source: medRxiv (preprint, 2023-10-15)
Field: Chemistry — Spectroscopy

Pervasive Influence of Hormonal Contraceptives on the Human Plasma Proteome in a Broad Population Study Abstract Background Plasma proteomics offers new avenues to explore non-genetic associations, such as biomarkers for lifestyle and environmental exposure in population studies. To date, most proteomic investigations in population studies have utilized affinity-reagent based technologies, which are ideal to quantify the low abundant fraction of the circulating proteome but may omit several of the abundant proteins that function in plasma. Methods Utilizing high throughput mass spectrometry, we quantified 148 highly abundant protein groups including immunoglobulins, coagulation factors, metabolic proteins, and components of the innate immune system, in the plasma of 3,632 participants from the Cooperative Health Research in South Tyrol (CHRIS) study. Using multiple regression analyses we then investigated associations with various factors including common medications. Results Beyond age and sex, the high abundant plasma proteome is predominantly influenced by hormonal contraceptives. For instance, Angiotensinogen (AGT) levels exhibit significant alteration with this treatment, suggesting that AGT levels could be a potential biomarker for contraceptive use. The effect of this drug class is more pronounced than other common medications or covariates. Furthermore, our analysis does not reveal any enduring signature associated with the use of these contraceptives. Conclusion In contrast to most used drugs, hormonal contraceptives exert a pronounced effect on the high abundant plasma proteome. Given its high prevalence among young female participants, the impact of hormonal contraceptives might be misconstrued as sex-or age-related effects on the plasma proteome. One should thus account for their use in any epidemiological or clinical plasma proteome study to prevent misleading results. Proteome ; Hormone ; Biomarker ; Proteomics ; Population ; Blood proteins ; Biology ; Medicine ; Physiology ; Computational biology ; Bioinformatics ; Immunology ; Endocrinology ; Genetics Advanced Proteomics Techniques and Applications ; Iron Metabolism and Disorders ; Mass Spectrometry Techniques and Applications
Authors: Pelayo Álvarez Penanes | Vladimir Gorshkov | Mark V. Ivanov | Mikhail V. Gorshkov | Frank Kjeldsen
Source: Journal of Proteome Research (article, 2023-07-03)
Field: Chemistry — Spectroscopy

Potential of Negative-Ion-Mode Proteomics: An MS1-Only Approach Current proteomics approaches rely almost exclusively on using the positive ionization mode, resulting in inefficient ionization of many acidic peptides. This study investigates protein identification efficiency in the negative ionization mode using the DirectMS1 method. DirectMS1 is an ultrafast data acquisition method based on accurate peptide mass measurements and predicted retention times. Our method achieves the highest rate of protein identification in the negative ion mode to date, identifying over 1000 proteins in a human cell line at a 1% false discovery rate. This is accomplished using a single-shot 10 min separation gradient, comparable to lengthy MS/MS-based analyses. Optimizing separation and experimental conditions was achieved by utilizing mobile buffers containing 2.5 mM imidazole and 3% isopropanol. The study emphasized the complementary nature of data obtained in positive and negative ion modes. Combining the results from all replicates in both polarities increased the number of identified proteins to 1774. Additionally, we analyzed the method's efficiency using different proteases for protein digestion. Among the four studied proteases (LysC, GluC, AspN, and trypsin), trypsin and LysC demonstrated the highest protein identification yield. This suggests that digestion procedures utilized in positive-mode proteomics can be effectively applied in the negative ion mode. Data are deposited to ProteomeXchange: PXD040583. Proteomics ; Chemistry ; Bottom-up proteomics ; Proteases ; Trypsin ; Chromatography ; Mass spectrometry ; Electrospray ionization ; Ion ; Ionization ; Analytical Chemistry (journal) ; Biochemistry ; Protein mass spectrometry ; Enzyme Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Ammar Armghan | Meshari Alsharari | Khaled Aliqab
Source: Micromachines (article, 2023-05-17)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Broadband and Efficient Metamaterial Absorber Design Based on Gold–MgF2–Tungsten Hybrid Structure for Solar Thermal Application We have presented a solar absorber design with gold-MgF<sub>2</sub>-tungsten materials. The solar absorber design is optimized with nonlinear optimization mathematical method to find and optimize geometrical parameters. The wideband absorber is made of a three-layer structure composed of tungsten, magnesium fluoride, and gold. This study analyzed the absorber's performance using numerical methods over the sun wavelength range of 0.25 μm to 3 μm. The solar AM 1.5 absorption spectrum is a benchmark against which the proposed structure's absorbing characteristics are evaluated and discussed. It is necessary to analyze the behavior of the absorber under a variety of various physical parameter conditions in order to determine the results and structural dimensions that are optimal. The nonlinear parametric optimization algorithm is applied to obtain the optimized solution. This structure can absorb more than 98% of light across the near-infrared and visible light spectrums. In addition, the structure has a high absorption efficiency for the far range of the infrared spectrum and the THz range. The absorber that has been presented is versatile enough to be used in a variety of solar applications, both narrowband and broadband. The design of the solar cell that has been presented will be of assistance in designing a solar cell that has high efficiency. The proposed optimized design with optimized parameters will help design solar thermal absorbers. Broadband ; Materials science ; Tungsten ; Metamaterial ; Thermal ; Metamaterial absorber ; Optoelectronics ; Optics ; Tunable metamaterials ; Physics ; Metallurgy Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis