jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Krzysztof Przybył | Katarzyna Samborska | Aleksandra Jedlińska | K. Koszela | Hanna Maria Baranowska | Łukasz Masewicz | Przemysław Łukasz Kowalczewski
Source: REVIEWS ON ADVANCED MATERIALS SCIENCE (article, 2025-01-01)
Field: Chemistry — Analytical Chemistry

The application of convolutional neural networks, LF-NMR, and texture for microparticle analysis in assessing the quality of fruit powders: Case study – blackcurrant powders Abstract It can be observed that dynamic developments in artificial intelligence contributing to the evolution of existing techniques used in food research. Currently, innovative methods are being sought to support unit processes such as food drying, while at the same time monitoring quality and extending their shelf life. The development of innovative technology using convolutional neural networks (CNNs) to assess the quality of fruit powders seems highly desirable. This will translate into obtaining homogeneous batches of powders based on the specific morphological structure of the obtained microparticles. The research aims to apply convolutional networks to assess the quality, consistency, and homogeneity of blackcurrant powders supported by comparative physical methods of low-field nuclear magnetic resonance (LF-NMR) and texture analysis. The results show that maltodextrin, inulin, whey milk proteins, microcrystalline cellulose, and gum arabic are effective carriers when identifying morphological structure using CNNs. The use of CNNs, texture analysis, and the effect of LF-NMR relaxation time together with statistical elaboration shows that maltodextrin as well as milk whey proteins in combination with inulin achieve the most favorable results. The best results were obtained for a sample containing 50% maltodextrin and 50% maltodextrin (MD50-MD70). The CNN model for this combination had the lowest mean squared error in the test set at 2.5741 × 10 −4 , confirming its high performance in the classification of blackcurrant powder microstructures. Texture (cosmology) ; Convolutional neural network ; Materials science ; Microparticle ; Quality (philosophy) ; Chemical engineering ; Computer science ; Artificial intelligence ; Image (mathematics) ; Physics ; Engineering Spectroscopy and Chemometric Analyses ; Food Chemistry and Fat Analysis ; Food composition and properties
Authors: Can Zhao | Qiaoyue Chen | Xinyuan Zhou | Xu-Cai Zhao | Bocheng Lei | Lili Zhang | Jing Zhao | Yineng Huang
Source: Nanomaterials (article, 2025-08-28)
Field: Materials Science — Materials Chemistry

First-Principles Study on the Photocatalytic Performance of K(Ta0.5Nb0.5)O3 Doped with Metals (Cd, Sn, Hf) Based on the excellent performance of the K(Ta<sub>0.5</sub>Nb<sub>0.5</sub>)O<sub>3</sub> (KTN) system, this study systematically investigated the mechanism of the influence of metal element (Cd, Sn, Hf) doping on the photocatalytic performance of KTN ferroelectric materials using the density functional theory (DFT) based on first principles. The findings indicate that after metal atom doping, the tolerance factor of doping systems is similar to that of pure KTN crystals, confirming that doping does not compromise its structural stability. However, the ion radius differences caused by doping lead to lattice distortion, significantly reducing the bandgap width. Because the impurity element substituting the Ta site exhibits a lower valence state compared to Ta, holes become the majority carriers, thereby endowing the semiconductor with p-type characteristics. These characteristics effectively suppress electron-hole recombination while enhancing electron transitions. Furthermore, the increase in the dielectric constant of the doped system indicates an enhancement in its polarization capability, which is accompanied by a significant improvement in carrier mobility. The peak of the imaginary part of the dielectric function and the peak of the absorption spectrum both shift towards the low-energy region, indicating that doping has expanded the light response range of the system. Moreover, the effective mass of the holes in all doped systems is significantly higher than that of the electrons, further demonstrating that the introduction of impurities is conducive to hindering the separation of photogenerated electron-hole pairs. These modifications significantly enhance the photocatalytic performance of the systems. Doping ; Photocatalysis ; Materials science ; Chemical engineering ; Nanotechnology ; Chemistry ; Optoelectronics ; Catalysis ; Engineering ; Organic chemistry Ferroelectric and Piezoelectric Materials ; Microwave Dielectric Ceramics Synthesis ; Multiferroics and related materials
Authors: Elina Khobotova | Vita Vasylivna Datsenko
Source: Engineering and Educational Technologies (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Artificial Intelligence in The Study of Chemistry in Universities The article reviews the use of artificial intelligence (AI) in higher education, which provides an understanding of the main aspects of AI in education: the use of AI tools to solve educational problems; solving problems of student engagement, educational inequality and time restrictions; the development of human intelligence alongside AI.The main roles that AI takes on in education in higher education institutions are indicated.The novelty of the results obtained lies in highlighting the positive and negative aspects of the application of AI in education, problematic aspects of the use of AI in teaching chemistry and unresolved issues.The most effective possibilities of using generative AI in conducting educational classes in the discipline of "Chemistry" and at the highest scientific level in conducting scientific chemical research have been identified.The results of the study show that generative AI can be used in educational classes in chemistry as a tool for creating an illustrative series, as an opponent, in monitoring with refinement of analytics and with the creation of generalized models.The advantages of AI in the study of chemistry in conducting student scientific research are considered: in analyzing large databases, identifying molecular properties, modeling molecular structure, predicting chemical reactivity and properties of substances, creating innovations in chemical research.AI can also provide a reduction in dependence on chemical experimentation.An example of our own experience using Chat GPT when conducting scientific research with students is given: existing approaches to the synthesis of ferrites are analyzed, the most optimal strategy for the synthesis of copper-zinc ferrites is selected, a generalized model of possible properties of ferrites as useful technical materials is created and methods for their research are analyzed.The synthesized ferrites have proven themselves as photocatalysts, oxidizers, sorbents, compounds with superparamagnetic properties.The practical value of the article lies in the fact that it provides stakeholders parties with information about the positive and negative features of the use of generative AI in higher education and specifically in the study of chemistry. Applications of artificial intelligence ; Expert system Machine Learning in Materials Science ; Genetics, Bioinformatics, and Biomedical Research ; Artificial Intelligence in Healthcare and Education
Authors: Haifeng Du
Source: The Innovation Materials (article, 2025-12-29)
Field: Chemistry — Organic Chemistry

A biomimetic breakthrough in glycinate aldol reaction: Enzyme-inspired efficient access to chiral β-hydroxy-α-amino acids Aldol reaction ; Catalysis ; Yield (engineering) ; Hydrolysis ; Component (thermodynamics) Carbohydrate Chemistry and Synthesis ; Asymmetric Synthesis and Catalysis ; Enzyme Catalysis and Immobilization
Authors: Pabitra Barik | Madhulika | Maibam Malemngamba Meitei | Soibam Ngasotter | Martina Meinam | Rupam Sharma | Kishore Kumar Krishnani
Source: Annals of Animal Science (article, 2025-10-16)
Field: Materials Science — Materials Chemistry

Harnessing nanotechnology for aquatic animal health: Current trends and future prospects – A review Abstract With the rapid growth of the aquaculture industry, challenges to the health of cultured organisms have also intensified, leading to frequent disease outbreaks that disrupt production and impact market stability. In response, nanotechnology has emerged as a transformative tool in aquatic animal health management, offering innovative solutions for challenges in disease prevention, water quality maintenance, and environmental sustainability. Nanotechnology is involved in many applications for the well-being of aquatic animals, such as nanoparticle-based drug delivery systems, their role as feed additives and antimicrobial agents, their use in water purification, and the development of nanosensors for disease detection and water quality monitoring. These technologies have shown significant promise in enhancing the health and productivity of aquaculture systems by enabling targeted, efficient, and sustainable interventions. For instance, nanoparticles improve vaccine delivery, enhance immune responses, and reduce pathogen loads, while nanosensors enable real-time monitoring of environmental parameters and early detection of diseases. Despite these advancements, challenges such as high production costs, potential environmental toxicity, scalability issues, and the lack of comprehensive regulatory frameworks impede their widespread adoption. This review emphasizes the need for biodegradable and biocompatible nanomaterials to mitigate environmental risks and enhance sustainability. Moreover, robust regulatory frameworks and interdisciplinary collaborations are crucial to ensuring the safe and effective implementation of nanotechnology in aquaculture. By highlighting the current trends, key achievements, and future prospects, this review underscores the potential of nanotechnology to revolutionize aquatic animal health management, paving the way for more sustainable and resilient aquaculture practices. Aquaculture ; Nanosensor ; Animal health ; Applications of nanotechnology ; Biosecurity ; Biosafety ; Sustainability ; Human health Nanoparticles: synthesis and applications ; Advanced Nanomaterials in Catalysis ; Selenium in Biological Systems
Authors: Ji-Hyun Kim | Yoona Jung | Yong-Seok Lee | Seong-Won Choi | Geelsu Hwang | Kwi‐Dug Yun
Source: Biomimetics (article, 2025-09-03)
Field: Materials Science — Biomaterials

Micro-CT and Histomorphometric Analysis of Degradability and New Bone Formation of Anodized Mg-Ca System The surface treatments and various magnesium alloys are applied to improve the fast degradation rate and resulting negative effects of magnesium alloys. This study aimed to assess the effect of anodic oxidation treatment of magnesium-calcium (Mg-Ca) systems by creating artificial bone defects in the tibia of rats. The cylinder magnesium implants were fabricated using a Mg-xCa (x = 0, 1, 5 wt.%) binary alloy. Degradability and new bone formation were observed at two and six weeks using micro-CT. Histomorphometric parameters were evaluated with Goldner's trichrome staining. The degradation rate decreased depending on the amount of calcium added. The parameters related to bone formation revealed an increasing pattern depending on the addition of calcium, anodic oxidation, and time. The amount of absorbed magnesium to assess degradability of magnesium implants by the histomorphometric analysis revealed a high value in the untreated group at two and six weeks. Bone healing parameters increased depending on the amount of calcium added, anodic oxidation treatment, and region of interest (ROI-0.5 mm, 1.00 mm, 1.5 mm, and 2.0 mm). Biodegradable magnesium systems have the potential to replace bone screws and plates. Combination with calcium combined with anodization surface treatment can improve initial corrosion resistance and promote bone formation. Anodizing ; Calcium ; Materials science ; Dentistry ; Biomedical engineering ; Nuclear chemistry ; Chemistry ; Metallurgy ; Medicine ; Aluminium Magnesium Alloys: Properties and Applications ; Bone Tissue Engineering Materials ; Orthopaedic implants and arthroplasty
Authors: Abdalla Ali Amin | Ali Rasw Hamad | Yousif Hussein Azeez | Karzan Mahmood Ahmed | Rebaz Obaıd Kareem | Rzgar Faruq Rashid | Khdir Ahmed Othman | Rebaz Anwar Omer
Source: Research Square (preprint, 2025-07-22)
Field: Chemistry — Organic Chemistry

New Bicyclic Benzylidene Oxazole Pyrimidines: Synthesis, Docking, Dynamics, and Adsorption Studies on Fe(110) and Cu(111) Oxazole ; Docking (animal) ; Bicyclic molecule ; Chemistry ; Stereochemistry ; Adsorption ; Combinatorial chemistry ; Computational chemistry ; Organic chemistry Synthesis and Characterization of Heterocyclic Compounds ; Synthesis and Biological Evaluation ; Synthesis and Reactivity of Heterocycles
Authors: Mohamed A. M. Atia | Kamal Shalabi | Mohamed A. Ismail | Magdy Abd El-Khalek | A. S. Fouda
Source: Zastita materijala (article, 2025-07-11)
Field: Materials Science — Materials Chemistry

Contribution to the corrosion inhibition of carbon steel by 5-(2-ethoxybenzylidene) 1,3-dimethylbarbituric acid in HCl solution: experimental and theoretical study The inhibiting impact of ecofriendly 5-(2-ethoxybenzylidene) 1,3-dimethylbarbituric acid (5-EBMB) in 1 M HCl on the corrosion of C-steel has been examined via weight loss (WL) method, potentiodynamic polarization (PDP), electrochemical impedance spectroscopy (EIS), electrochemical frequency modulation (EFM) techniques”. The obtained results demonstrate that the studied chemical is good 5-EBMB and that, in both PDP and EIS methods, its inhibition efficiency (%IE) increases with increasing concentration, reaching 82.5 at 21x10-6 M. Conversely, when the temperature rose, the percentage of IE reduced. “The adsorption of the investigated derivative on the surface of C-steel follows Langmuir isotherm. The adsorption process of the investigated compound is spontaneous and considered as chemisorption type”. PDP curves revealed that the studied derivative is mixed-type inhibitor. Furthermore, the EIS results verified that the compound under investigation had adsorbed on the C-steel surface by raising the charge transfer resistance (Rct) to 139.7 ohm cm2 and decreasing the double layer (Cdl) capacitance from 102 to 69 µF cm-2. The inhibitor adsorption on the C-steel surface was confirmed by surface examination using atomic force microscopy (AFM), energy dispersive X-ray (EDX), and scanning electron microscopy (SEM). Additionally, quantum chemistry and molecular dynamic simulation were used to extensively examine the mechanism of 5-EBMB's corrosion inhibition. All tested methods gave good agreement. Adsorption ; Dielectric spectroscopy ; Chemistry ; Corrosion ; Chemisorption ; Carbon steel ; Scanning electron microscope ; Double-layer capacitance ; Electrochemistry ; Analytical Chemistry (journal) ; Langmuir adsorption model ; Corrosion inhibitor ; Langmuir ; Inorganic chemistry ; Nuclear chemistry ; Physical chemistry ; Materials science ; Electrode ; Organic chemistry ; Composite material Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Yudhajit Bhattacharjee | L. N. Mielke | Mahmoud Al‐Hussein | Shivam Singh | Karen Moore Schaefer | Borja Rodriguez‐Barea | Qiong Li | Anik Kumar Ghosh | Artur Erbe | Carmen Herrmann | Yana Vaynzof | Andreas Fery | Hendrik Schlicke
Source: ArXiv.org (preprint, 2025-04-15)
Field: Materials Science — Materials Chemistry

Molecular Cross-linking of MXenes: Tunable Interfaces and Chemiresistive Sensing MXenes, a family of 2D transition metal compounds, have emerged as promising materials due to their unique electronic properties and tunable surface chemistry. However, the translation of these nanoscale properties into macroscopic devices is constrained by suitable cross-linking strategies that enable both processability and controlled inter-flake charge transport. Herein, we demonstrate the tunability of interfaces and the inter-layer spacing between Ti$_3$C$_2$T$_x$ MXene flakes through molecular cross-linking with homologous diamines. Oleylamine was first used to stabilize MXenes in chloroform, followed by diamine-mediated cross-linking to tune precisely the interlayer spacing. Grazing incidence X-ray scattering (GIXRD/GIWAXS) confirmed the correlation between ligand chain length and inter-layer spacing, which was further supported by Density Functional Theory (DFT) calculations. Furthermore, we investigated the charge transport properties of thin films consisting of these diamine-crosslinked Ti$_3$C$_2$T$_x$ MXenes and observed a strong dependence of the conductivity on the interlayer spacing. The dominating charge transport mechanism is variable range hopping (VRH) in accordance with the structure analysis of the films. Finally, we probed chemiresistive vapor sensing in MXene composites, observing pronounced water sensitivity and selectivity, highlighting their potential for use in humidity sensors. Insights into molecular cross-linking and its impact on charge transport open avenues for next-generation MXene-based electronic devices. MXenes ; Charge (physics) ; Scattering ; Density functional theory ; Variable-range hopping ; Nanoscopic scale ; Oleylamine ; Conductivity MXene and MAX Phase Materials ; Graphene and Nanomaterials Applications ; Advanced biosensing and bioanalysis techniques
Authors: Xiaoqi Zhang | Senja Barthel | Yutao Li | Berend Smit | Raffaela Cabriolu
Source: Nature Communications (article, 2025-11-27)
Field: Materials Science — Materials Chemistry

Thermal transport mechanisms in ZIFs Zeolitic imidazolate frameworks (ZIFs), a subclass of metal-organic frameworks (MOFs), exhibit tunable thermal conductivity, which is crucial for applications such as gas adsorption, catalysis, and energy storage. Despite its significance, thermal conductivity in MOFs remains less explored compared to other key performance indicators. In this work, we investigate the thermal transport properties of 196 ZIF structures with diverse net topologies and organic linkers. We develop a thermal circuit model that quantitatively integrates network topology and consolidates various atomic contributions into heat conduction units for thermal analysis. Our results reveal a strong correlation between circuit-estimated and simulated thermal conductivity, demonstrating the model's predictive power. Additionally, we find that functional groups influence thermal transport through a competing interplay between atomic mass and mechanical stability. These findings provide a systematic approach for tailoring MOF thermal properties, offering insights into the rational design of materials with optimized thermal performance. Thermal conductivity ; Thermal ; Thermal conduction ; Zeolitic imidazolate framework ; Network topology ; Topology (electrical circuits) ; Thermal fluids Thermal properties of materials ; Metal-Organic Frameworks: Synthesis and Applications ; Phase Change Materials Research
Authors: Ta‐Shun Chou | Saud Bin Anooz | Natasha Dropka | Han-Hsu Chen | Zbigniew Galazka | M. Albrecht | Andreas Fiedler | Andreas Popp
Source: Research Square (preprint, 2025-02-03)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Controlling the morphology transition on MOVPE-grown (100) β-Ga2O3 film between step-flow growth and step-bunching: A machine learning-assisted approach Supersaturation ; Metalorganic vapour phase epitaxy ; Morphology (biology) ; Epitaxy ; Materials science ; Impurity ; Flow (mathematics) ; Nanotechnology ; Chemical physics ; Artificial intelligence ; Computer science ; Algorithm ; Chemistry ; Physics ; Thermodynamics ; Geology ; Mechanics Ga2O3 and related materials ; ZnO doping and properties ; Electronic and Structural Properties of Oxides
Authors: Aleksander Katarzyna | Wojciech Zbigniew
Source: Fusion of Multidisciplinary Research An International Journal (article, 2025-01-12)
Field: Materials Science — Materials Chemistry

Hidden Strength of Nanostructured Metallic Materials Metallic materials engineered at the nanoscale demonstrate strength levels up to three times higher compared to traditional commercial crystalline alloys. This remarkable enhancement stems from recent advancements in nanostructure design strategies, which have revolutionized how we approach material engineering. Due to their unique characteristics, nanomaterials exhibit exceptional chemical reactivity and mechanical properties that their conventional counterparts simply cannot match. These advantages arise from carefully controlled grain sizes and the development of heterogeneous nanostructures in both crystalline and non-crystalline metallic materials. Furthermore, innovative approaches like supra-nano-dual-phase (SNDP) nanostructures combine supra-nano sized crystals with metallic glasses, creating materials with unprecedented performance capabilities. In this article, we will explore why nanostructured metallic materials consistently outperform traditional alloys, examine their manufacturing processes, and investigate their real-world applications across various industries. We will also analyze the cost-effectiveness and future potential of these advanced materials in engineering applications. Materials science ; Metal ; Metallurgy ; Composite material Microstructure and mechanical properties ; Metal and Thin Film Mechanics ; Aluminum Alloys Composites Properties
Authors: Yuichiro Yoshida | Luca Erhart | Takuma Murokoshi | Ryuichi NAKAGAWA | C Mori | Hirotaka Tagami | Wataru Mizukami
Source: ArXiv.org (preprint, 2025-01-31)
Field: Chemistry — Spectroscopy

Auxiliary-field quantum Monte Carlo method with seniority-zero trial wave function We present an approach that uses the doubly occupied configuration interaction (DOCI) wave function as the trial wave function in phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC). DOCI is a seniority-zero method focused on electron pairs. Although DOCI considers much fewer electron configurations than the complete active space (CAS) configuration interaction method, it efficiently captures the static correlation, while the consequent ph-AFQMC recovers the dynamical correlation across all orbitals. We also explore an orbital-optimized version (OO-DOCI) to further improve accuracy. We test this approach on several chemical systems, including single O-H bond breaking in water and polymer additives. In these cases, OO-DOCI-AFQMC closely matches CAS-based ph-AFQMC and even outperforms coupled-cluster singles, doubles, and perturbative triples. However, for strongly correlated systems, such as the carbon dimer and multi-bond dissociation in hydrogen systems and water, the method's accuracy drops. This suggests that seniority-zero space models may be insufficient as trial wave functions in ph-AFQMC for strongly correlated systems, suggesting the need for trial wave functions in an extended space. Despite such a limitation, our study demonstrates that DOCI- and OO-DOCI-based ph-AFQMC can reduce the steep cost of CAS approaches, offering a path to accurate multi-reference calculations for larger, more complex systems. Seniority ; Monte Carlo method ; Zero (linguistics) ; Physics ; Quantum Monte Carlo ; Field (mathematics) ; Statistical physics ; Wave function ; Quantum electrodynamics ; Mathematics ; Quantum mechanics ; Statistics ; Engineering ; Aerospace engineering Spectroscopy and Laser Applications