jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Xin Zhou | Tobias Dierke | Mingjian Wu | Shu‐Li You | Klaus Götz | Tobias Unruh | Philipp Pelz | Johannes Will | Janina Maultzsch | Erdmann Spiecker
Source: npj 2D Materials and Applications (article, 2025-07-05)
Field: Materials Science — Materials Chemistry

Identification of polytypism and their dislocations in bilayer MoS2 using correlative transmission electron microscopy and Raman spectroscopy Abstract Stacking orders and topological defects substantially influence the physical properties of 2D van der Waals (vdW) materials. However, the inherent features of 2D materials challenge the effectiveness of single characterization techniques in identifying stacking sequences, necessitating correlative approaches. Using bilayer MoS 2 as a benchmark, we differentiate its polytypism and specific dislocations through transmission electron microscopy (TEM) and Raman spectroscopy. Perfect and partial dislocations were revealed in TEM, which are closely linked to the stacking sequences, thus indirectly indicating the 2H and 3R polytypes. Quantitative analysis of reciprocal lattice from 3D electron diffraction and low-frequency Raman spectroscopy further validated these polytypes owing to their reliance on crystal symmetry. Surprisingly, we unexpectedly resolved both polytypes despite starting with 2H bulk crystal, pointing to a possible phase transition during mechanical exfoliation. The correlative TEM-Raman approach can be extended to other 2D materials, paving the way for property alteration via stacking and defect engineering. Raman spectroscopy ; Correlative ; Transmission electron microscopy ; Materials science ; Bilayer ; Electron microscope ; Crystallography ; Nanotechnology ; Chemistry ; Optics ; Physics ; Membrane 2D Materials and Applications ; MXene and MAX Phase Materials ; Perovskite Materials and Applications
Authors: Piyanart Chotikawanid | Pattanapong Saeleung | Yutthapong Pianroj | Saysunee Jumrat | Teerasak Punvichai | Jirapond Muangprathub
Source: Applied Computational Intelligence and Soft Computing (article, 2025-01-01)
Field: Chemistry — Inorganic Chemistry

Optimizing an Object Detection Algorithm for Detecting Oil Palm Fruit Bunches and Their Ripeness The detection and classification of oil palm fruit bunches are critical for optimizing palm oil yield and quality. Traditional methods relying on human visual inspection are prone to errors and inconsistencies. To address these challenges, this study proposes an optimized You Only Look Once Version 7 (YOLOv7) algorithm for real‐time detection and classification of oil palm fruit bunches. By leveraging a comprehensive dataset and implementing strategic fine‐tuning techniques, we significantly improved the model’s performance. The optimized model achieved a classification accuracy of 92.55% and a mean average precision (mAP) of 95.08%, demonstrating its effectiveness in real‐world applications. The model was integrated into web application, allowing farmers and processing facilities to assess the ripeness of palm fruit in real time, thereby improving decision‐making and operational efficiency. This research highlights the potential of advanced deep learning models in agricultural applications, promising a transformative impact on the palm oil industry by ensuring consistent quality assessments and optimizing production processes. Ripeness ; Computer science ; Bunches ; Palm oil ; Object (grammar) ; Object detection ; Artificial intelligence ; Computer vision ; Computer graphics (images) ; Real-time computing ; Pattern recognition (psychology) ; Horticulture ; Environmental science ; Ripening ; Optics Coconut Research and Applications ; Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI
Authors: 陈思阳 Chen Siyang | 黄泽骁 Huang Zexiao | 王月 Wang Yue | 孟庆涛 Meng Qingtao | 张志强 Zhang Zhiqiang
Source: Acta Optica Sinica (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

一种钴（Ⅲ）配合物用于生物体内连二亚硫酸钠的磁共振/荧光双模态成像 以Co3+为磁共振单元，采用7-（二乙氨基）香豆素-3-甲酸作为荧光单元，设计开发了基于钴（Ⅲ）配合物的荧光/磁共振双模态分子探针H2。该探针将具有高灵敏度和高选择性的光学成像技术和组织穿透能力强、空间分辨率高的磁共振成像技术结合，弥补了单一模态成像的缺点。连二亚硫酸钠（Na2S2O4）与钴离子进行氧化还原反应，使得抗磁性Co3+转变为顺磁性Co2+，进而实现了磁共振信号和荧光信号的同步激活。探针H2具有良好的稳定性，对Na2S2O4具有专一的识别能力，适用于生理条件的pH，检测限为23 μmol/L。最后，通过磁共振/荧光双模态成像将探针H2成功应用于生物体内外源性Na2S2O4的检测。 Geology Lanthanide and Transition Metal Complexes ; Nanoplatforms for cancer theranostics ; Luminescence Properties of Advanced Materials
Authors: Maira Khafagy | Sherief Fathi | Ahmed Magdy
Source: Scientific Reports (article, 2025-07-08)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A low-complexity M-shaped reconfigurable intelligent meta-surface for mitigating pathloss in wireless systems Future 6G wireless communication systems require innovative solutions to overcome severe path loss, particularly in the millimeter-wave (mmWave) frequency bands. This study presents a novel Low-Complexity M-shaped Reconfigurable Intelligent Metasurface (LCM-RIM) designed to mitigate path loss in indoor environments. The proposed LCM-RIM features a compact, single-layer unit cell based on a low-loss Rogers substrate, offering a lightweight and cost-effective design suitable for seamless integration into wall-mounted installations in office and conference room settings. Each unit cell incorporates an AlGaAs PIN diode, enabling control at high frequencies and facilitating 1-bit phase modulation with discrete phase shifts of [Formula: see text] and [Formula: see text], operating at 24.12 GHz. This configuration supports passive beamforming with low hardware complexity and minimal power consumption. A [Formula: see text] array configuration (1024 elements) with [Formula: see text] element spacing is used to enhance the gain. The LCM-RIM is employed to enable effective wavefront manipulation and ensure scalability for large-area coverage. To evaluate system-level performance, a numerical path loss model is developed by characterizing the angular gain profile of the LCM-RIM, which follows a Gaussian distribution across reflection angles. The model is validated using MATLAB simulations under various transmitter-receiver distances and angles of incidence. Results indicate that the LCM-RIM structure can enhance received signal strength by up to 15 dB in typical mmWave indoor scenarios. These findings underscore the potential of the proposed LCM-RIM design for practical deployment in future 6G networks, offering an efficient and scalable solution to address mmWave path loss in enclosed environments. Path loss ; Computer science ; Beamforming ; Transmitter ; Scalability ; Physical layer ; Wireless ; Extremely high frequency ; Electronic engineering ; Telecommunications ; Engineering ; Channel (broadcasting) Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Carlos Alcantara | Luísa Jorge | Clara B. Vaz
Source:  (article, 2025-03-19)
Field: Chemistry — Organic Chemistry

Sustainably enhancing olive oil production: intelligent system architecture Olive oil production is a noteworthy economic activity in multiple places worldwide. Due to environmental degradation and lack of resources with population growth, there is a global tendency for more sustainable and efficient practices, driving the implementation of more responsible agricultural and industrial systems. This paper aims to develop an intelligent system architecture focused on optimizing the production of olive oil, improving product quality, reducing operational waste, and maximizing the efficient use of natural resources. Through the use of Industrial Internet of Things (IIoT) technologies, the proposed solution aims to monitor and control the parameters of olive oil production automatically. In addition, the study addresses sensors already used in the market and existing systems to compare and seek improvements. The proposed architecture contains three layers: device, edge, and cloud computing layer, which are integrated and enable the implementation of a scalable and complete solution that allows real-time visualization and control of the production process. Sustainability ; Olive oil ; Production (economics) ; Architecture ; Oil production ; Computer science ; Business ; Engineering ; Food science ; Petroleum engineering ; Art ; Chemistry ; Economics Edible Oils Quality and Analysis
Authors: Weizhao Gu | Simone Lamon | Haoyi Yu | Qiming Zhang | Miṅ Gu
Source: Light Science & Applications (article, 2025-12-04)
Field: Materials Science — Materials Chemistry

Topology-driven energy transfer networks for upconversion stimulated emission depletion microscopy Lanthanide-doped upconversion nanoparticles enable upconversion stimulated emission depletion microscopy with high photostability and low-intensity near-infrared continuous-wave lasers. Controlling energy transfer dynamics in these nanoparticles is crucial for super-resolution microscopy with minimal laser intensities and high photon budgets. However, traditional methods neglect the spatial distribution of lanthanide ions and its effect on energy transfer dynamics. Here, we introduce topology-driven energy transfer networks in lanthanide-doped upconversion nanoparticles for upconversion stimulated emission depletion microscopy with reduced laser intensities, maintaining a high photon budget. Spatial separation of Yb<sup>3+</sup> sensitizers and Tm<sup>3+</sup> emitters in 50-nm core-shell nanoparticles enhance energy transfer dynamics for super-resolution microscopy. Topology-dependent energy migration produces strong 450-nm upconversion luminescence under low-power 980-nm excitation. Enhanced cross-relaxation improves optical switching efficiency, achieving a saturation intensity of 0.06 MW cm<sup>-2</sup> under excitation at 980 nm and depletion at 808 nm. Super-resolution imaging with a 65-nm lateral resolution is achieved using intensities of 0.03 MW cm<sup>-2</sup> for a Gaussian-shaped excitation laser at 980 nm and 1 MW cm<sup>-2</sup> for a donut-shaped depletion laser at 808 nm, representing a 10-fold reduction in excitation intensity and a 3-fold reduction in depletion intensity compared to conventional methods. These findings demonstrate the potential of harnessing topology-dependent energy transfer dynamics in upconversion nanoparticles for advancing low-power super-resolution applications. Photon upconversion ; Laser ; Excitation ; Microscopy ; Nanoparticle ; Luminescence ; Emission intensity ; Ion Luminescence Properties of Advanced Materials ; Luminescence and Fluorescent Materials ; Photorefractive and Nonlinear Optics
Authors: Annabelle Dietrich | Luca Heim | Jürgen Hubbuch
Source: Frontiers in Bioengineering and Biotechnology (article, 2025-08-21)
Field: Chemistry — Analytical Chemistry

Raman-based PAT for multi-attribute monitoring during VLP recovery by dual-stage CFF: attribute-specific spectral preprocessing for model transfer Spectroscopic soft sensors are developed by combining spectral data with chemometric modeling, and offer as Process Analytical Technology (PAT) tools powerful insights into biopharmaceutical processing. In this study, soft sensors based on Raman spectroscopy and linear or partial least squares (PLS) regression were developed and successfully transferred to a filtration-based recovery step of precipitated virus-like particles (VLPs). For near real-time monitoring of product accumulation and precipitant depletion, the dual-stage cross-flow filtration (CFF) set-up was equipped with an on-line loop in the second membrane stage. With this set-up, spectral data from three CFF runs were collected, differing in initial product concentration and process parameters. Under the scope of multi-attribute monitoring, a comprehensive investigation of the sensor sensitivity towards protein and precipitant and their Raman spectral features was carried out. This study reveals much higher sensitivity towards the precipitant ammonium sulfate (AMS) than the VLPs and the need for attribute-specific spectral preprocessing. To enhance the detector's sensitivity towards proteins, a higher exposure time was applied during CFF processing than during model building from pure-component stock solutions. As a result of this increased exposure time, the predominant sulfate band exhibited oversaturation effects, which otherwise could have been used for AMS quantification via linear regression. Nevertheless, AMS prediction using purpose-driven preprocessing operations and PLS models was achieved with normalization and a data-driven variable selection technique, next to baseline correction and signal smoothing. For VLP monitoring, a novel pre-cropping approach improved spectral appearance after further preprocessing in protein-associated wavenumber regions. However, fluctuations in prediction were much higher for VLPs than for AMS, and prediction accuracy was especially limited in low protein concentration ranges. These results highlight the potential of Raman-based PAT sensors for real-time monitoring of biopharmaceutical processes, while underscoring the general importance of attribute-specific selections of sensors, preprocessing operations, and models for PAT tool development. Preprocessor ; Dual (grammatical number) ; Stage (stratigraphy) ; Computer science ; Artificial intelligence ; Biology Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Viral Infectious Diseases and Gene Expression in Insects
Authors: А. Г. Погорелов | Larisa Ipatova | В. Н. Погорелова | A. I. Panait | A.A. Stankevich | O. A. Suvorov
Source: chemistry of plant raw material (article, 2025-03-03)
Field: Chemistry — Analytical Chemistry

ULTRASONIC EXTRACTION OF PIGMENTS FROM VEGETABLE RAW MATERIALS. REVIEW This review summarizes and analyzes methods for isolating plant pigments (anthocyanins, betalains, carotenoids) by ultrasonic extraction from secondary plant resources in the food industry. Extracting dyes from plant waste makes it possible to simultaneously improve the depth of processing of raw materials, reduce the burden on the environment and increase the production volumes of natural dyes. In addition, plant pigments are low-molecular substances that have the functions of physiologically active compounds. The review presents materials from the Scopus (scopus.com), Google Scholar (scholar.google.ru) and RSCI (elibrary.ru) databases, published mainly for the period 2019-2023. Articles devoted to the extraction of coloring substances from waste processing of food plant raw materials and the advantages of ultrasonic extraction were analyzed. 134 articles were analyzed, of which 41% of publications were published in the last two years.The advantages of ultrasonic extraction are shown, including the ability to eliminate the use or significantly reduce the volume of organic solvents, allowing this method to be defined as a “green” technology. The emphasis is on secondary raw materials, common in our country, which accumulate after processing cranberries, onions, carrots, and beets. Works devoted to the study of the influence of ultrasound on the extraction of plant pigments confirm the relevance of the research topic. A number of promising areas include: improvement of the ultrasonic extraction method, including optimization of processing methods and modes, as well as the search for effective combinations of ultrasound with other gentle extraction methods. Ultrasonic sensor ; Raw material ; Extraction (chemistry) ; Environmental science ; Pulp and paper industry ; Engineering ; Acoustics ; Chromatography ; Chemistry ; Physics ; Organic chemistry Dye analysis and toxicity
Authors: Birger Dittrich | Rok Breznikar | Gianluca Santarossa | Pamela S. Whitfield | Henrik Moebitz
Source: IUCrJ (article, 2025-06-17)
Field: Materials Science — Materials Chemistry

Benchmarking quantum chemical methods with X-ray structures via structure-specific restraints There is a need for fast, efficient and accurate solid-state structure optimization for imprecise crystal structures (`augmentation') for subsequent property prediction in the pharmaceutical industry. Crystal structures from single-crystal X-ray, 3D electron or powder diffraction are widely available but require augmentation to the same quality level for comparative studies. Properties can be best calculated when the level of theory is alike and the accuracy, as well as the precision, are high. Moreover, the size of molecules and the complexity of structures encountered in pharmaceutical research are increasing. Efficient procedures are thus required that can also treat structures with disorder and several molecules in the asymmetric unit of the unit cell. Hence, we investigated whether `molecule-in-cluster' (MIC) computations [Dittrich et al. (2020). CrystEngComm 22, 7420-7431] can reach the accuracy of full-periodic (FP) computations. Selected quantum mechanical methods are assessed. The evaluation criterion is how well the structures of 22 very low temperature high-quality structures are reproduced. Computational efficiency is also considered. A novel approach to evaluating the accuracy of quantum mechanical predictions is enforcing computed structure-specific restraints in crystallographic least-squares refinements. To complement this approach, root mean square Cartesian displacements of computed and experimental structures were also compared. Analysis shows that (a) MIC DFT-D computations in a quantum mechanics/molecular mechanics (QM:MM) framework provide improved restraints and coordinates over earlier MIC GFN2-xTB computations, (b) increasing QM basis-set size in MIC QM:MM does not systematically improve computations, and (c) the choice of DFT functional is less important than the choice of the basis set. Overall, MIC computations are an accurate and computationally efficient tool for solid-state structure optimization that can match FP computations to augment experimental structures. Computation ; Computer science ; Cartesian coordinate system ; Quantum ; Algorithm ; Crystal structure ; Statistical physics ; Chemistry ; Physics ; Mathematics ; Crystallography ; Quantum mechanics ; Geometry X-ray Diffraction in Crystallography ; Machine Learning in Materials Science ; Crystallography and molecular interactions
Authors: Linda Nelles-Ziegler | Christoph Plett | Stefan Grimme
Source: Chemistry - A European Journal (article, 2025-06-03)
Field: Chemistry — Spectroscopy

Quantum Chemistry Based Simulation of Enantioseparation on Cyclodextrin‐ and Polysaccharide‐Based Chiral Stationary Phases We assess the capability of modern quantum chemical methods to simulate enantioseparation on chiral stationary phases (CSPs) in high-performance liquid chromatography (HPLC) by comparing calculated and experimental elution orders (EEOs). Compared to previous studies, this work utilizes more accurate state-of-the-art density functional theory (DFT) methods combined with automated computational workflows. The proposed approach employs molecular docking, conformer sampling, and DFT refinement for final ensemble-based association free energy calculations of two diastereomeric complexes. Ten drug-type molecules were considered on two common CSPs for which various molecular models were investigated. Although the association free energies of the strongest binding motifs were rather system-dependen t ranging from about -9 to 29 kcal/mol, the differences between the two enantiomers were always only a few kcal/mol, sometimes even below 1 kcal/mol. Despite these small differences, correct determination of EEOs for all tested cyclodextrin-based CSP systems was achieved. Even for more flexible polysaccharide-based CSPs, the workflow yielded correct EEO results in 90 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:semantics><mml:mo>%</mml:mo> <mml:annotation>$\%$</mml:annotation></mml:semantics> </mml:math> of the tested cases, provided that a sufficiently large cut-out of the CSP material consisting of about 150 atoms was considered as a model. Due to the latter constraint, the method remains computationally expensive, requiring further research for improving practical application in, e.g., screening studies. Cyclodextrin ; Chemistry ; Quantum chemistry ; Polysaccharide ; Computational chemistry ; Organic chemistry ; Molecule ; Supramolecular chemistry Analytical Chemistry and Chromatography ; Crystallization and Solubility Studies ; Crystallography and molecular interactions
Authors: P. Maestro | A. Gil | Andrés Bustillo
Source: The International Journal of Advanced Manufacturing Technology (article, 2025-09-19)
Field: Materials Science — Materials Chemistry

Semi-supervised tapping wear detection in nodular cast iron workpieces under real industrial conditions Abstract The tapping of metal components is a manufacturing task with great potential for automation, because the conditions affecting the industrial components are of limited variability. However, automation encounters two main problems: both the human- and the time-related costs associated with the manual classification of threads are excessive, and thread quality can vary greatly, due to tapping tool wear. In this study, the use of semi-supervised algorithms is proposed to improve the performance of machine learning–based models trained on real industrial datasets. The strategy was validated on a dataset of more than 7000 threads produced with 36 different tapping tools under the same working conditions involving nodular cast iron workpieces. Several algorithms were trained using datasets with different features and data processing. The best results were obtained with datasets using linear regression in which sinusoidal fluctuations in the raw signals were replaced by linear regressions and the slope of an 11-element rolling window was applied to extend the raw dataset. Algorithms were trained with different percentages of labeled datasets. The co-training-based algorithms almost systematically obtained the best results, yielding better results than the reference algorithms using a 100% labeled dataset. Besides, the proposed solution also achieved higher performance with 50% of labeled instances in the training dataset, drastically reducing the costs of manual labeling for that sort of industrial dataset. Tapping ; Cast iron ; Thread (computing) ; Blast furnace ; Automation ; Embedding ; Linear regression ; Task (project management) Metal Alloys Wear and Properties ; Non-Destructive Testing Techniques ; Metal and Thin Film Mechanics