jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Panayiota Adamou | Eleana Harkou | Silvio Bellomi | Ilaria Barlocco | Dimitris Mintis | Antreas Afantitis | Juan J. Delgado | Xiaowei Chen | George Manos | Nikolaos Dimitratos | Alberto Villa | Achilleas Constantinou
Source: ChemCatChem (article, 2025-05-31)
Field: Materials Science — Materials Chemistry

H<sub>2</sub> Production from Ammonia Borane: Integrating Experiments, Computational Fluid Dynamics, and Statistical Analysis for Predicting and Optimizing Process and Reactor Design Abstract In this study, an iridium catalyst (Ir/Ni 10 Ce) was used for the catalytic hydrolysis of ammonia borane (AB). The parameters tested were temperature, stirring rate, AB concentration, and AB‐to‐catalyst molar ratio. By integrating a simple Langmuir–Hinshelwood kinetic in a computational fluid dynamics (CFD) simulation, the experimental results were validated with a maximum error of 13% observed at only two experimental conditions, while on the rest it was lower than 10%, showcasing the robustness of the model. In all experimental cases, AB resulted in over 85% H 2 yield. Statistical analysis was also implemented to uncover the effect of the four main factors: temperature, stirring rate, AB concentration, and substrate (AB) to catalyst ratio, on the three response variables: reaction time, TOF, and H 2 yield. Radar plots are also presented, illustrating how two‐factor interaction influences the response variables. By combining temperature with either concentration or catalyst amount, a profound effect on the reaction time was observed. The combination of experimental work along with computational work of CFD and statistical analysis can significantly enhance a reaction process by targeting the most impactful factors, allowing experiments with optimized reaction conditions for better results in terms of H 2 yield and catalytic performance. Considering also the interaction of the variables enables further process optimization by focusing on specific parameter combinations without wasting resources. Catalysis ; Yield (engineering) ; Chemistry ; Computational fluid dynamics ; Response surface methodology ; Reaction rate ; Robustness (evolution) ; Thermodynamics ; Chromatography ; Organic chemistry Hydrogen Storage and Materials ; Ammonia Synthesis and Nitrogen Reduction ; Nuclear Materials and Properties
Authors: Tingting Li | Na Li | Ruifeng Wang | Xuexia Ma | Ning Hua Zhu | Jing Ma | Songlei Wang | Ning Ju | Dongli Zhang | Zhongxiong Zhang
Source: Journal of Dairy Science (review, 2025-10-21)
Field: Chemistry — Analytical Chemistry

Graduate Student Literature Review: A review on near-infrared spectroscopy for rapid detection of hazardous substances in milk and dairy products Milk and dairy products are highly valued for their nutritional content, making their quality and safety critically important. However, they are prone to contamination by hazardous substances, such as veterinary drug residues, adulterants, and foodborne pathogens, which pose serious risks to consumer health. While traditional detection methods are effective, they often involve complex, time-consuming procedures, labor-intensive sample preparation, and high costs. In contrast, near-infrared spectroscopy (NIRS) has emerged as a promising alternative for dairy quality and safety testing, offering the benefits of being rapid, nondestructive, easy to operate, and cost effective. This paper provides a detailed overview of the principles, methodologies, and analytical processes of NIRS in detecting hazardous substances in milk and dairy products. The chemometric techniques involved in data preprocessing, characteristic wavelength selection, and model construction are systematically introduced. The paper also highlights recent research advancements in the detection of 3 major categories of hazardous substances (veterinary drug residues, adulterants, and foodborne pathogens) using NIRS technology. Presently, NIRS-based detection remains constrained by unresolved challenges: ambiguous optical detection mechanisms, inadequate sensitivity for trace-level analyte detection, pronounced interference from complex matrices, and suboptimal model robustness and generalizability. Moving forward, research endeavors should prioritize the seamless integration of frontier technologies, encompassing optical mechanism elucidation, signal enrichment enhancement, deep learning, multimodal analysis, and artificial intelligence. Such integration is anticipated to substantially boost the detection performance of NIRS, alongside enhancing model robustness and generalizability, thus furnishing theoretical underpinnings and technical scaffolding for the rapid detection and analysis of hazardous substances in milk and dairy products. Hazardous waste ; Robustness (evolution) ; Analyte ; Quality (philosophy) ; Consumer safety ; Contamination ; Food safety ; Dairy industry Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Listeria monocytogenes in Food Safety
Authors: Guy Trambly de Laissardière | Somepalli Venkateswarlu | Ahmed Misssaoui | Ghassen Jemaï | Khouloud Chika | Javad Vahedi | Omid Faizy Namarvar | Jean-Pierre Julien | A. Honecker | Laurence Magaud | Jouda Jemaa Khabthani | Didier Mayou
Source: Physica E Low-dimensional Systems and Nanostructures (article, 2025-09-10)
Field: Materials Science — Materials Chemistry

Electronic structure and transport in materials with flat bands: 2D materials and quasicrystals In this review, we present recent works on materials whose common point is the presence of electronic bands of very low dispersion, called "flat bands", which are due to specific atomic order effects without electron interactions. These states are always indicative of some form of confinement and have consequences on the electronic properties. A first part is devoted to the cases where this confinement is due to the long-range geometry of the defect-free structure. We have thus studied periodic approximant structures of quasiperiodic Penrose and octagonal tilings, and twisted bilayers of graphene (TBG) or transition metal dichalcogenides (TMDs) whose rotation angle between the two layers assumes a special value, called "magic angle". In these materials, the flat bands correspond to electronic states distributed over a very large number of atoms (several hundreds or even thousands of atoms). We have shown that their electronic transport properties cannot be described by usual Bloch-Boltzmann theories, because the interband terms of the velocity operator dominate the intraband terms as far as quantum diffusion is concerned. In the case of TBG, flat bands can induce a magnetic state and other electron-electron correlation effects. The second part focuses on two-dimensional nanomaterials in the presence of local point defects that cause resonant electronic states (vacancies, adsorbed atoms or molecules). We present studies on monolayer graphene, twisted or Bernal bilayer graphene, carbon nanotubes, monolayer and multilayer black phosphorene, and monolayer TMDs. A recent result is the discovery that the selective functionalization of a Bernal bilayer graphene sublattice leads to a metallic or insulating behavior depending on the functionalized sublattice type. This result suggests that functionalization can be a key parameter to control the electronic properties of 2D materials. Monolayer ; Quasiperiodic function ; Electronic structure ; Quasicrystal ; Bilayer graphene ; Bilayer ; Graphene ; Electron ; Superlattice Graphene research and applications ; 2D Materials and Applications ; Topological Materials and Phenomena
Authors: Seyfal Sultanov | R. A. W. Ayyubi | J. P. Buban | Robert F. Klie
Source: Small (article, 2025-07-06)
Field: Materials Science — Materials Chemistry

Robust Spectral Anomaly Detection in EELS Spectral Images via 3D Convolutional Variational Autoencoders A 3D Convolutional Variational Autoencoder (3D-CVAE) is introduced for automated anomaly detection in electron energy-loss spectroscopy spectrum imaging (EELS-SI) data. This approach leverages the full 3D structure of EELS-SI data to detect subtle spectral anomalies while preserving both spatial and spectral correlations across the datacube. By employing cross-entropy loss and training on bulk spectra, the model learns to reconstruct bulk features characteristic of the defect-free material. In exploring methods for anomaly detection, both the 3D-CVAE approach and principal component analysis (PCA) are evaluated, testing their performance using Fe L-edge ΔE peak shifts designed to simulate material defects. These results show that 3D-CVAE achieves superior anomaly detection and maintains consistent performance across various shift magnitudes. The method demonstrates clear bimodal separation between bulk and anomalous spectra, enabling reliable classification. Further analysis verifies that lower-dimensional representations are robust to anomalies in the data. While performance advantages over PCA diminish with decreasing anomaly concentration, our method maintains high reconstruction quality even in challenging, noise-dominated spectral regions. This approach provides a robust framework for unsupervised automated detection of spectral anomalies in EELS-SI data, particularly valuable for analyzing complex material systems. Autoencoder ; Anomaly detection ; Pattern recognition (psychology) ; Principal component analysis ; Computer science ; Artificial intelligence ; Anomaly (physics) ; Entropy (arrow of time) ; Convolutional neural network ; Biological system ; Physics ; Deep learning Machine Learning in Materials Science ; Electron and X-Ray Spectroscopy Techniques ; Electrochemical Analysis and Applications
Authors: Mohsen Rabbani | Olivia Tahti | Sabinus Arthur | Macy Hopping | Christopher J. Barile | Hassan Karim | Ario Fahimi | Ehsan Vahidi
Source: RSC Sustainability (article, 2025-01-01)
Field: Materials Science — Polymers and Plastics

Assessing the environmental footprint of electrochromic windows: a comparative LCA with AI-based forecasting Electrochromic windows exhibit 35% lower carbon emissions than conventional double-pane windows. Coupling LCA with AI-based forecasting (ANN and ANFIS) reveals that electricity use and frame design are the primary environmental hotspots. Carbon footprint ; Life-cycle assessment ; Electricity ; Frame (networking) ; Ecological footprint ; Production (economics) Transition Metal Oxide Nanomaterials
Authors: E Elavarasi | Venkateswara Rao T | S Harinisri | M Farhatyassir | A Kavinragul | Rajavel Srinivasan
Source: Journal of Pharma Insights and Research. (article, 2025-04-05)
Field: Materials Science — Biomaterials

Biodegradable Nanomaterials in Drug Delivery Systems Biodegradable nanoparticles have revolutionized drug delivery by enhancing therapeutic efficacy while minimizing environmental impact. These nanocarriers, composed of biocompatible polymers, lipids, proteins, and inorganic materials, enable targeted drug delivery and controlled release kinetics, reducing dosing frequency and improving patient compliance. Their natural degradation into non-toxic byproducts addresses long-term toxicity concerns and offers an environmentally conscious alternative to conventional delivery systems. Polymeric nanoparticles, particularly those based on chitosan, polylactic acid (PLA), and poly(lactic-co-glycolic acid) (PLGA), demonstrate remarkable versatility in drug encapsulation and release profiles. Lipid-based carriers like liposomes and solid lipid nanoparticles effectively transport both hydrophilic and hydrophobic drugs. Protein-based and inorganic biodegradable nanocarriers further expand the scope of sustainable drug delivery, especially in targeted therapies. Recent advances include the development of smart, stimuli-responsive nanomaterials that release drugs in response to specific environmental triggers such as pH, temperature, or enzymatic activity. While these systems show tremendous potential, challenges in scalability, stability, and regulatory compliance need resolution for widespread clinical implementation. Green synthesis methods are emerging to enhance production sustainability and reduce environmental impact. Drug delivery ; Nanomaterials ; Drug ; Nanotechnology ; Business ; Risk analysis (engineering) ; Pharmacology ; Materials science ; Medicine Nanoparticle-Based Drug Delivery
Authors: Lars C. P. Binkhorst | I Josimović | Daan de Vetten | Tyrone J. Nijman | Niels J. Hauwert | Sufyan Ahmad | Oscar P. J. van Linden | Iwan J. P. de Esch | Henry F. Vischer | Maikel Wijtmans | Rob Leurs
Source: RSC Medicinal Chemistry (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Design and synthesis of photoswitchable desloratadine ligands for histamine H <sub>1</sub> receptor photopharmacology Despite the pharmacological relevance of the histamine H<sub>1</sub> receptor (H<sub>1</sub>R), the second most therapeutically targeted G protein-coupled receptor (GPCR), an effective photoswitchable ligand to optically control this receptor remains elusive. In this work, we aimed to identify a suitable photoswitchable H<sub>1</sub>R ligand by performing an 'azoscan' on the H<sub>1</sub>R antagonist desloratadine. Taking advantage of the synthetic toolbox available for the desloratadine scaffold, aniline groups were regioselectively installed on the aromatic positions of this scaffold to enable the synthesis of azobenzene analogs targeting the orthosteric binding pocket of H<sub>1</sub>R. Additionally, we functionalized the piperidine ring of desloratadine with azobenzene moieties. These two strategies resulted in a total of nine photoswitchable compounds, displaying efficient <i>trans</i> to <i>cis</i> isomerization (PSS <sub><i>cis</i></sub> > 87%) and a broad range of thermal relaxation half-lives. Pharmacological evaluation revealed the 2-position (10a) to be most suitable for accommodation of a photoswitchable group, as it exhibits the most balanced profile in absolute affinity (<i>K</i> <sub>i</sub> <i>trans</i> = 2 nM) and a 3.2-fold light-induced affinity shift. Computational docking studies provide a rationale, with the binding pose of the <i>trans</i> and <i>cis</i> isomer in the H<sub>1</sub>R binding pocket potentially being inverted. While the development of effective photoswitchable ligands for H<sub>1</sub>R remains challenging, this study provides promising opportunities for future optimization to achieve optical control of this GPCR. Desloratadine ; Histamine ; Histamine receptor ; Chemistry ; Receptor ; Combinatorial chemistry ; Stereochemistry ; Pharmacology ; Medicine ; Biochemistry ; Antagonist Photochromic and Fluorescence Chemistry ; Photoreceptor and optogenetics research ; Nanoplatforms for cancer theranostics
Authors: Mutasem Alshalalfeh | Xi‐Yan Dong | Shyam Parshotam | Guojie Li | James R. Cheeseman | Shuang‐Quan Zang | Yunjie Xu
Source: Small (article, 2025-09-27)
Field: Materials Science — Materials Chemistry

Vibrational Circular Dichroism Spectra of Atomically‐Precise Metal Clusters: Unveiling Conformational Structures and Mechanism of VCD Enhancement via Full Models While the inherent imprecision of nanoparticles has hindered a thorough comprehension of chirality transfer and enhancement events at the nanoscale, recent advances in ultrastable, chiral metal clusters offer a unique opportunity to tackle this challenge with atomic precision. Four atomically-precise metal clusters with octahedral metal cores protected by monolayer organic ligands, namely Ag<sub>6</sub>PL<sub>6</sub>/PD<sub>6</sub>, and Cu<sub>6</sub>PL<sub>6</sub>/PD<sub>6</sub> (PL<sub>6</sub>/PD<sub>6</sub> = (S)-/(R)-4-phenylthiazolidine-2-thione) are investigated using vibrational circular dichroism (VCD) in conjunction with theoretical modeling and electronic CD. Extensive and systematic conformational searches are carried out for the ligand and metal clusters. The IR and VCD spectra of the most stable conformers are simulated using full models, demonstrating excellent agreements with experiment and uncovering the preferred ligand conformational arrangements. A modified modes approach is developed to unveil the roles of individual ligands, their collective arrangements and numbers, and the metal core asymmetry in the drastic VCD enhancement. While commonly used truncated models with fewer metal atoms and/or ligands exhibit their critical deficiencies, the full models provide a solid foundation for accurately predicting the chiral properties of nanosized materials. Vibrational circular dichroism ; Conformational isomerism ; Chirality (physics) ; Metal ; Circular dichroism ; Ligand (biochemistry) ; Monolayer ; Spectral line Nanocluster Synthesis and Applications ; Molecular spectroscopy and chirality ; Algebraic structures and combinatorial models
Authors: Sudarshan Vijay | Martin Schlipf | Henrique Miranda | Ferenc Karsai | Merzuk Kaltak | Martijn Marsman | Georg Kresse
Source: arXiv (Cornell University) (preprint, 2025-01-05)
Field: Chemistry — Physical and Theoretical Chemistry

Efficient periodic density functional theory calculations of charged molecules and surfaces using Coulomb kernel truncation Density functional theory (DFT) calculations of charged molecules and surfaces are critical to applications in electro-catalysis, energy materials and related fields of materials science. DFT implementations such as the Vienna ab-initio Simulation Package (VASP) compute the electrostatic potential under 3D periodic boundary conditions, necessitating charge neutrality. In this work, we implement 0D and 2D periodic boundary conditions to facilitate DFT calculations of charged molecules and surfaces respectively. We implement these boundary conditions using the Coulomb kernel truncation method. Our implementation computes the potential under 0D and 2D boundary conditions by selectively subtracting unwanted long-range interactions in the potential computed under 3D boundary conditions. By combining the Coulomb kernel truncation method with a computationally efficient padding approach, we remove nonphysical potentials from vacuum in 0D and 2D systems. To illustrate the computational efficiency of our method, we perform large supercell calculations of the formation energy of a charged chlorine defect on a sodium chloride (001) surface and perform long time-scale molecular dynamics simulations on a stepped gold (211) | water electrode-electrolyte interface. Density functional theory ; Truncation (statistics) ; Coulomb ; Kernel (algebra) ; Time-dependent density functional theory ; Physics ; Statistical physics ; Classical mechanics ; Mathematics ; Quantum mechanics ; Pure mathematics ; Statistics Advanced Physical and Chemical Molecular Interactions ; Advanced Chemical Physics Studies
Authors: Igor S. Vicente | Gaspar Andrade | Bruno Hessel Silva | Jéssica Bruna Ponsoni | Jeferson Almeida Dias | Guilherme Zepon | Renato Belli Strozi | Sabrina Sartori | Ricardo Floriano
Source: Energy & Fuels (article, 2025-08-07)
Field: Materials Science — Materials Chemistry

Exploring the Dual-Phase Configuration of Multicomponent Alloys in the Ti<sub>21</sub>Zr<sub>21</sub>V<sub><i>x</i></sub>Fe<sub><i>y</i></sub>Ni<sub><i>z</i></sub> (<i>x</i> + <i>y</i> + <i>z</i> = 58 at %) System for Room Temperature Hydrogen Storage This study investigates the dual-phase configuration of multicomponent alloys (MCAs) within the Ti 21 Zr 21 V x Fe y Ni z (x + y + z = 58 at %) system for hydrogen storage.The design strategy involved the use of the Calculation of Phase Diagrams (CALPHAD) method, which obtained four dual-phase alloys with varying proportions of C14 Laves and body-centered cubic (BCC) phases.All alloys exhibited fast hydrogen absorption kinetics, reaching maximum capacity within 5 min, and demonstrated good hydrogen storage capacity at room temperature.Ti 21 Zr 21 Fe 41 Ni 17 (V1), with the lower BCC content (8.2 wt %), absorbed the lowest amount of hydrogen (1.2 wt %), whereas Ti 21 Zr 21 V 14 Fe 4.3 Ni 39.7 (V4) absorbed up to 1.7 wt %.When analyzing the thermodynamics of the alloys, V1 exhibited a superior reversible hydrogen capacity of 0.91 wt % when compared to V4, which retained 0.56 wt %.This behavior is attributed to the thermodynamic stability of the C14 Laves phase, which predominantly governs the absorption characteristics at room temperature, as confirmed by pressure-composition-temperature (PCT) simulations, and to hydrogen retention within the BCC structure. Materials science ; Phase (matter) ; Crystallography ; Chemistry Hydrogen Storage and Materials ; High Entropy Alloys Studies ; Titanium Alloys Microstructure and Properties
Authors: Jingchi Guo | Hong Zhang | Quan Xu | Yang Liu | Haonan Xue | Shengkun Dong
Source: Horticulturae (article, 2025-09-01)
Field: Chemistry — Analytical Chemistry

Synchronous Detection Method of Physical Quality for Korla Fragrant Pear with Different Damage Types During Storage Mechanical damage reduces the marketability of Korla fragrant pears, severely restricting industry development. To enhance the commercial value of pears, this study investigated the effects of impact, compressive, and combined impact-compressive damage types on the weight loss rate, L*, a*, and b* of pears, and constructed a multi-output prediction model for the weight loss rate, L*, a*, and b* of damaged pears during storage by integrating partial least squares regression (PLSR), support vector regression (SVR), and long short-term memory (LSTM), from which the optimal prediction model was selected to achieve synchronous detection of the physical quality of damaged pears during storage. The results indicated that during storage, the weight loss rate, a*, and b* of pears subjected to different damage types gradually increased with prolonged storage time, while L* gradually decreased. Under the same damage volume situation, pears subjected to impact-static pressure combined action exhibited the fastest storage quality change speed, followed by impact action, static pressure action. The SVR multi-output model demonstrated optimal performance in predicting the weight loss rate, L*, a*, and b* of damaged pears during storage, achieving mean coefficient of determination R2, root mean square error (RMSE), and residual prediction deviation (RPD) values of 0.988, 0.513, and 10.072, respectively, for these four quality indicators. These results establish a theoretical foundation for the development of simultaneous monitoring techniques for fruit storage quality. PEAR ; Horticulture ; Botany ; Chemistry ; Biology Spectroscopy and Chemometric Analyses ; Fermentation and Sensory Analysis ; Phytochemicals and Antioxidant Activities
Authors: Thomas Fix | X. Henning | D. Müller | Rachmat Adhi Wibowo | M. V. Rastei | A. Dinia | A. Slaoui
Source: Journal of Alloys and Compounds (article, 2025-04-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Effect of sulfur implantation in BiFeO3 thin films Materials science ; Sulfur ; Thin film ; Nanotechnology ; Metallurgy Multiferroics and related materials ; Transition Metal Oxide Nanomaterials ; Advanced Fiber Optic Sensors