jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Christian Carbogno | Nikita Rybin | Sara Panahian Jand | Alaa Akkoush | Carlos Mera Acosta | Zhen‐Kun Yuan | Mariana Rossi
Source: arXiv (Cornell University) (preprint, 2025-01-05)
Field: Chemistry — Physical and Theoretical Chemistry

Polarisation, Born Effective Charges, and Topological Invariants via a Berry-Phase Approach This paper represents one contribution to a larger Roadmap article reviewing the current status of the FHI-aims code. In this contribution, the implementation of polarization, Born-effective charges and topological invariants using a Berry-phase approach in a all-electron, numeric atom-centered orbitals framework is summarized. Guidelines on usage and links to tutorials are provided. Geometric phase ; Topology (electrical circuits) ; Phase (matter) ; Berry ; Physics ; Theoretical physics ; Mathematics ; Quantum mechanics ; Combinatorics History and advancements in chemistry ; Topological Materials and Phenomena
Authors: Roger Moens | Nathan Heath Patterson | Lukasz G. Migas | Allison B. Esselman | Felipe Moser | Jeffrey M. Spraggins | Raf Van de Plas
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-10-30)
Field: Chemistry — Spectroscopy

Unmixing of Imaging Mass Spectrometry Measurements Using Microscopy-Informed Constraints Imaging mass spectrometry (IMS) provides spatially resolved molecular information of organic tissue but can be limited by pixel signals mixing contributions from adjacent biological structures, <i>e.g.</i> of single cells and multicellular functional tissue units (FTUs). This paper proposes computational methods to predict mass spectral profiles of biological structures on the basis of IMS data by "unmixing" pixel-level signals, leveraging microscopy-based boundary information of these structures. By modeling each biological structure as having a unique mass spectrum, we formulate a linear mixing model and solve the corresponding inverse problem that unmixes blended signals. In particular, we cover both overdetermined and underdetermined linear system scenarios and compare ordinary least squares, non-negative least squares, and singular value thresholding to a custom algorithm, coined Tissue-informed Unmixing of Labeled regions by Inverse Problem (TULIP), specifically tailored to IMS data. Validation on a synthetic <i>in-situ</i> single cell dataset and demonstration on a large-scale kidney FTU dataset illustrate the potential of these methods for enhanced <i>in-situ</i> tissue structure analysis, e.g. in cellular and tissue studies. Overdetermined system ; Underdetermined system ; Thresholding ; Inverse problem ; Mixing (physics) ; Basis (linear algebra) ; Inverse ; Multispectral image Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Ion-surface interactions and analysis
Authors: Qichao Zhao | B.L. Wang | Jinwu KANG
Source: Scientific Reports (article, 2025-12-30)
Field: Materials Science — Materials Chemistry

A PIKAN-based model for the prediction of the temperature fields of castings In the casting process, solving various physical quantities centered on the temperature field through numerical simulation is very helpful for optimizing the process. The rapid development of deep learning technology offers potential for industrial applications and can represent a new simulation methodology. This study proposes a PIKAN model that groups spatiotemporal parameters and inputs them through an MLP model. During the training process, this study used a loss function that combines physical loss and data loss, and identified the optimal weight parameters through Bayesian optimization. Pre-training with multiple casting geometries as labels has improved the efficiency of model prediction. With an absolute error of 10 K as the critical value, the average temperature error of this study is 5.62 K, and the average accuracy reaches 88.74%. This study predicts the evolution of the two-dimensional temperature field during the casting solidification process using deep learning, supporting the application of new technologies in engineering. Casting ; Field (mathematics) ; Process (computing) ; Approximation error ; Function (biology) ; Bayesian probability ; Mean absolute error ; Temperature measurement Machine Learning in Materials Science ; Aluminum Alloy Microstructure Properties ; Metallurgical Processes and Thermodynamics
Authors: Xudong Zhu | Sulin He
Source: Journal of Education and Educational Policy Studies (article, 2025-03-07)
Field: Chemistry — Physical and Theoretical Chemistry

Citizen science projects: an effective approach for cultivating the core chemistry literacy of middle school students In recent years, citizen science has become an important way for the public to engage in scientific inquiry in Europe and North America. It has gradually evolved into school-based citizen science projects that integrate with school education. Currently, citizen science projects in China are still in their early stages, mainly focused on fields such as ecology and astronomy, with very few citizen science projects in the field of chemistry. In the existing citizen science projects in China, public participation is still at the early stage of simple data collection, with little integration with school education. This paper explores the important role of citizen science in enhancing middle school students' core chemistry literacy and aims to provide a platform for students to participate in scientific inquiry through citizen science projects, with the goal of offering a new approach to cultivating core chemistry literacy in middle school students. Mathematics education ; Scientific literacy ; Core (optical fiber) ; Literacy ; Science education ; Pedagogy ; Sociology ; Chemistry ; Engineering ethics ; Engineering ; Psychology Various Chemistry Research Topics ; Science Education and Pedagogy ; Mobile Learning in Education
Authors: Jeff Z. Y. Chen
Source: Soft Matter (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Phase-field model for quantitative analysis of droplet wetting A general phase-field formalism is presented, aimed at capturing the excess surface energies and geometric profiles of three-dimensional, asymmetric liquid droplets on solid surfaces. To ensure strict volume conservation of the droplet, a nonlinear definition is employed for the internal volume. To facilitate modeling in systems where the interface widths approach zero, an extrapolation method is proposed to interpret data obtained at finite interface widths. The numerically tractable algorithm yields accurate predictions for the excess surface energies and state diagrams of known wetting configurations on both the external and internal surfaces of cylinders, demonstrating quantitative agreement with established results from other models and computational techniques. Wetting ; Field (mathematics) ; Phase (matter) ; Materials science ; Chemistry ; Physics ; Thermodynamics ; Mathematics ; Organic chemistry Solidification and crystal growth phenomena ; nanoparticles nucleation surface interactions ; Fluid Dynamics and Thin Films
Authors: José Espinoza | Laio Ariel Leite de Paiva | Lucas Ramos da Costa | Gustavo Lopes Muniz | Jackson Silva Nóbrega | Stefeson Bezerra de Melo | Paulo César Moura da Silva | Bruno Caio Chaves Fernandes | Luiz Fernando de Sousa Antunes | Antônio Gustavo de Luna Souto | Norlan Leonel Ramos Cruz | Eulene Francisco da Silva | Phâmella Kalliny Pereira Farias | Rafael Oliveira Batista
Source: AgriEngineering (article, 2025-09-15)
Field: Chemistry — Physical and Theoretical Chemistry

Integration of Fractal Metrics and Scanning Electron Microscopy for Advanced and Innovative Diagnosis of Biofouling in Drippers Applying Brackish Water Traditional methods of analyzing biofouling in emitters fail to capture the complexity and heterogeneity of their components. Therefore, the objective of this work was to develop and validate an innovative approach that integrates fractal metrics and scanning electron microscopy (SEM) to accurately characterize, quantify, and diagnose biofouling in drippers used with brackish water. For this purpose, tests were conducted on benches that applied brackish water and fresh water through drippers with a flow exponent (x) of 0.46 (NJ), 0.45 (SL), and 0.48 (ST) over 160 h. Biofouling was mapped using advanced diagnostics using SEM and factual metrics, and the results were analyzed using multivariate statistics. The results obtained present important findings for the study, detection, mapping, and proposal of mitigation measures for biofouling in drippers, presenting factual metrics that may be new indicators of clogging. Biofouling is a phenomenon resulting from the interaction between the spatial evolution of the obstructing material, emitter geometry, and irrigation water quality. The combination of SEM and fractal metrics has proven to be an advanced and innovative diagnostic tool for detecting the presence and distribution of biofouling, enabling clogging monitoring and creating more realistic scenarios in hydrodynamic studies to improve or develop emitter designs. Biofouling ; Brackish water ; Fractal ; Clogging ; Scanning electron microscope ; Water flow Electrostatics and Colloid Interactions
Authors: Jiawen Sun | Jiashun Niu | Lichao Xu | Jianping Sun | Linhong Zhao
Source: Forests (article, 2025-06-21)
Field: Chemistry — Organic Chemistry

Multi-Algorithm Feature Extraction from Dual Sections for the Recognition of Three African Redwoods To address the persistent challenge of low recognition accuracy in precious wood species classification, this study proposes a novel methodology for identifying Pterocarpus santalinus, Pterocarpus tinctorius (PTD), and Pterocarpus tinctorius (Zambia). This approach synergistically integrates artificial neural networks (ANNs) with advanced image feature extraction techniques, specifically Fast Fourier Transform, Gabor Transform, Wavelet Transform, and Gray-Level Co-occurrence Matrix. Features were extracted from both transverse and longitudinal wood sections. Fifteen distinct ANN models were subsequently developed: hybrid-section models combined features from different sections using a single algorithm, while multi-algorithm models aggregated features from the same section across all four algorithms. The dual-section hybrid wavelet model (LC4) demonstrated superior performance, achieving a perfect 100% recognition accuracy. High accuracies were also observed in the four-parameter combination models for longitudinal (L5) and transverse (C5) sections, yielding 97.62% and 91.67%, respectively. Notably, 92.31% of the LC4 model’s test samples exhibited an absolute error of ≤1%, highlighting its high reliability and precision. These findings confirm the efficacy of integrating image processing with neural networks for fine-grained wood identification and underscore the exceptional discriminative power of wavelet-based features in cross-sectional data fusion. Dual (grammatical number) ; Computer science ; Extraction (chemistry) ; Pattern recognition (psychology) ; Feature (linguistics) ; Feature extraction ; Artificial intelligence ; Algorithm ; Chromatography ; Chemistry ; Art Wood and Agarwood Research ; Remote Sensing and LiDAR Applications ; African Botany and Ecology Studies
Authors: Manish Kumar | V. G. Krishna
Source: International Journal of Agriculture and Food Science (review, 2025-01-01)
Field: Chemistry — Analytical Chemistry

A review on advanced sensing technologies for real-time monitoring of grain loss Grain loss during combine harvesting is a critical issue influenced by various factors. Since the 1960s, researchers have developed automated detection systems using piezoelectric sensors to monitor grain wastage. However, existing sensors struggle with saturation at high impact rates. To improve detection accuracy in rice harvesting, laboratory experiments were conducted to refine the structure and placement of the instrumented plate. The optimal plate (150×40×1 mm) successfully measured grain loss with an error margin of less than 3.83%. From 2017 to 2020, field experiments in Northeast China analyzed grain dry Matter Loss (GDML) and Mechanical Losses (ML), Including Header Loss (HL), Cleaning Loss (CL), Entrainment Loss (EL), and Un-Threshed Loss (UTL). The results showed that harvesting at 52-53 days after heading (DAH) for long-grain rice and 53-54 DAH for short-grain rice significantly reduced losses. In addition, smart farming technologies, such as the Internet of Things (IoT) and machine learning, enhance precision agriculture by improving yield prediction, pest monitoring, and harvest scheduling. Furthermore, smartphone-based imaging provided a quick, non-invasive method for assessing Grain Moisture Content (GMC). In Malaysia, studies recorded grain losses ranging from 1.08% to 1.21%, negatively impacting farm profits. By optimizing harvesting schedules, fine-tuning machine parameters, and integrating intelligent farming techniques, grain loss can be significantly minimized, operational efficiency can be improved, and economic returns for farmers can be maximized. Computer science ; Environmental science ; Remote sensing ; Geology Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI
Authors: Xuejin Zhao | Zhenzong Li | Xiaoyu Zhao | Feihong Xu | Chengxin Zhao
Source: Research Square (preprint, 2025-10-06)
Field: Materials Science — Materials Chemistry

Design and mechanical properties analysis of multi hybrid orthotic insole based on FG-TPMS structures Plantar pressure ; Finite element method ; Stereolithography ; Compression (physics) ; Homogeneous ; Biomechanics ; Load bearing Silicone and Siloxane Chemistry ; Structural Engineering and Vibration Analysis ; Structural Analysis and Optimization
Authors: Melissa Klingeberg | Christoph Krisp | Sonja Fritzsche | Simon Schallenberg | Daniel Hornburg | Fabian Coscia
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-06-05)
Field: Chemistry — Spectroscopy

An ultrasensitive spatial tissue proteomics workflow exceeding 100 proteomes per day Abstract Achieving high-resolution spatial tissue proteomes requires careful balancing and integration of optimized sample processing, chromatography, and MS acquisition. Here, we present an advanced cellenONE protocol for loss-reduced tissue processing and compare all Evosep ONE Whisper Zoom gradients (20, 40, 80, and 120 samples per day), along with three common DIA acquisition schemes on a timsUltra AIP mass spectrometer. We found that tissue type was as important as gradient length and sample amount in determining proteome coverage. Moreover, the benefit of increased tissue sampling was gradient- and dynamic range-dependent. Analyzing mouse liver, a high dynamic range tissue, over tenfold more tissue sampling led to only ~30% gain in protein identification for short gradients (120 SPD and 80 SPD). However, even the lowest tested tissue amount (0.04 nL, 40,000 µm 3 ) yielded 3,200 reproducibly quantified proteins for the 120 SPD method. Longer gradients (40 SPD and 20 SPD) instead significantly benefited from more tissue sampling, quantifying over 7,500 proteins from 0.5 nL of tonsil T-cell niches. Finally, we applied our workflow to a rare squamous cell carcinoma of the oral cavity, uncovering disease-associated pathways and region-specific protein level changes. Our study demonstrates that more than 100 high-quality spatial tissue proteomes can be prepared and acquired daily, laying a strong foundation for cohort-size spatial tissue proteomics in translational research. Workflow ; Proteome ; Proteomics ; Computational biology ; Computer science ; Biology ; Bioinformatics ; Biochemistry ; Database Advanced Proteomics Techniques and Applications
Authors: Sanjyot Vinayak Shenoy | Deeptarup Biswas | Arthur O. Zalevsky | Audrey Kishishita | Ayushi Verma | Ishan Upadhay | Yi He | Andrej Săli | Rosa Viner | Kamal Mandal | Sanjeeva Srivastava | Arun P. Wiita
Source: Molecular & Cellular Proteomics (article, 2025-08-19)
Field: Chemistry — Spectroscopy

AlphaCross-XL: A Seamless Tool for Automated and Proteome-Scale Mapping of Cross-Linked Peptides Onto 3D Protein Structures Crosslinking mass spectrometry (XL-MS) is an exciting proteomics technology to capture native protein conformations in real time within biological systems. Historically, however, implementation of this technology has typically been limited to single purified recombinant proteins or in vitro-assembled protein complexes. These limitations are associated with inherent challenges in XL-MS analysis, including extremely low abundance of crosslinked (XL) peptides and complex deconvolution of XL peptide-derived spectral data. However, impressive recent developments in computation and instrumentation have now made it feasible to address biological questions using proteome-wide XL-MS analysis. Although some XL mapping software tools exist, these require manual input of specific Protein Data Bank structures at the single protein level and do not function at the high-throughput scale required to analyze datasets derived from thousands of proteins. To address this need, we therefore sought to develop a strategy enabling automated mapping of XL peptides onto the 3D structures of proteins, at a proteome-wide scale. Herein, we describe AlphaCross-XL, a first-in-class seamless computational tool for automated mapping of XL peptides onto the protein structures for intraprotein crosslinks and loop links. The AlphaCross-XL software first retrieves protein structures from the AlphaFold Protein Structure Database and maps all the identified crosslinks onto the 3D structure. It also calculates the Euclidian distance between the crosslinked residues and reports the violated and satisfied crosslink distances based on a user-defined distance threshold, which is visually discriminated by color in PyMOL. Last, the tool also supports further validation of user-submitted protein structures, which can include any computer-predicted protein structure and experimentally derived protein structures (i.e., from Protein Data Bank). AlphaCross-XL is available at https://github.com/sanjyotshenoy/alphacross-xl. Proteome ; Computational biology ; Scale (ratio) ; Chemistry ; Computer science ; Biochemistry ; Biology ; Physics Advanced Proteomics Techniques and Applications ; Ubiquitin and proteasome pathways ; Glycosylation and Glycoproteins Research
Authors: Adam Carlsson | Johanna Rosén | Martin Dahlqvist
Source: Advanced Theory and Simulations (article, 2025-02-12)
Field: Materials Science — Materials Chemistry

When Two Becomes Three: Predicting Stable Ternary Boron‐Based Compounds by Populating Unique Lattice Sites in Binary Prototype Structures Abstract Boron‐based materials are known for their excellent mechanical properties and structural versatility. However, the discovery of such novel materials is often hindered by challenging synthesis procedures, such as high temperature and pressure, which is why theoretical guidance can be used to identify candidates most promising for synthesis. In this study, new chemical phase spaces are explored utilizing the Materials Project database. 16 boron‐based binary prototype structures are identified, each featuring two unique non‐boron lattice sites. These sites are subsequently populated with elements from Groups 2 to 14 and expanded into 27 552 ternary compounds. Phase stability assessments identify 166 stable ternary compounds, 155 of which are mechanically stable. Analysis reveals a strong correlation between boron concentration and mechanical properties, with boron‐rich compounds exhibiting higher Vickers hardness and improving shear and Young's moduli. Notably, multiple ternary compounds demonstrate significant mechanical property enhancements over their binary counterparts, with some showing Young's modulus improvements of up to 50%. These findings exemplify a pathway for designing novel boron‐based materials with exceptional mechanical characteristics. Ternary operation ; Boron ; Binary number ; Lattice (music) ; Materials science ; Chemistry ; Crystallography ; Physics ; Computer science ; Mathematics ; Organic chemistry ; Arithmetic ; Programming language MXene and MAX Phase Materials ; Boron and Carbon Nanomaterials Research ; Machine Learning in Materials Science
Authors: Sofia Almpani | Maria Mitsiou | Paraskevi Kyriaki Monou | Catherine K. Markopoulou
Source: Molecules (article, 2025-11-19)
Field: Chemistry — Analytical Chemistry

Development and Validation of an HPLC-DAD Method for the Quantitative Determination of Benzoyl Peroxide, Curcumin, Rosmarinic Acid, Resveratrol and Salicylic Acid in a Face Mask—In Vitro/Ex Vivo Permeability Study Acne is a common skin condition that causes pimples, redness and inflammation. Benzoyl peroxide (BENZ), salicylic acid (SAL), curcumin (CUR), rosmarinic acid (ROS) and resveratrol (RESV) exhibit antimicrobial, anti-inflammatory and antioxidant properties and are recommended for its treatment. These five active pharmaceutical ingredients (APIs) were incorporated into a green clay, honey and gelatin face mask and determined by an HPLC-DAD (diode array) method. For the chromatographic separation of the analytes, a gradient mobile phase with two solvents mixtures: A, comprising H<sub>2</sub>O with 0.1% TFA-ACN with 0.1% TFA, 85:15 <i>v</i>/<i>v</i>, and B, comprising 100% ACN with 0.1% TFA, and a C18 column (250 × 4.6 mm, 5 μm), at 40 °C (diluent: MeOH-ACN 0.1% TFA 2:1 <i>v</i>/<i>v</i>), were selected. The method was validated according to the ICH guidelines for pharmaceutical products (R<sup>2</sup> > 0.999, %RSD < 1.2, % Recovery > 98.2, LOD<sub>μg/mL</sub>: ROS = 0.267, RES = 0.047, SAL = 0.636, CUR = 0.296 and BENZ = 0.083). For the processing of mask samples and the quantitative extraction of the analytes, the "D-optima mixture" experimental design methodology was applied (% Recovery 95.4-102.1%, %RSD < 2.4). Finally, the permeability rate (Papp) of the mask ingredients through the skin was studied using Franz vertical diffusion cells, in a cellulose membrane (in vitro), in rat tissue and in human skin (ex vivo). To ensure the reliability of the results, APIs' stability rate under the given experimental conditions was studied. In addition, a second method for sample processing in Franz cells was developed and validated (% Recovery > 90.6-106.9, %RSD < 5.2). Based on the results obtained, both the effectiveness of the new face mask formulation and the suitability of the membranes were evaluated. Rosmarinic acid ; Salicylic acid ; Resveratrol ; Acne ; Active ingredient ; Antioxidant ; High-performance liquid chromatography ; Coumaric acid ; Baicalin ; In vivo Analytical Methods in Pharmaceuticals ; Dye analysis and toxicity ; Electrochemical sensors and biosensors