jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Diola Bagayoko | Yacouba Issa Diakité | Allé Dioum | Y. M. Malozovsky
Source: Annals of computational physics and material science. (article, 2025-01-13)
Field: Materials Science — Materials Chemistry

The Completed Density Functional Theory (cDFT) for Accurate Description and Prediction of Properties of Materials The foundational theorems of DFT require, for its correct application, the use of the ground state charge density of a material for calculating its electronic and related properties. The à priori unknown nature of this ground state charge density points to the incomplete nature of the seminal DFT. Mainstream calculations have mostly assumed that results obtained with self-consistent iterations using a single basis set represent the ground state of a material; such results are stationary states among an infinite number of such states – with no relation to the ground state of the material under study. The Completion of DFT [AIP Advance, 4, 127104 (2014)] entailed (a) the introduction of the second corollary to the first DFT theorem and (b) the methodical search for and attainment of the ground state of a material with successive, self-consistent calculations with progressively augmented basis sets. With (a) and (b), the completed density functional theory (cDFT) has unfailingly and accurately predicted properties of several materials and described electronic and related properties of dozens of semiconductors, including their band gaps. The cDFT does not invoke a self-interaction correction or a derivative discontinuity of the exchange-correlation energy. It does not utilize ad hoc potentials. Results of cDFT calculations possess the full physical content of the theory and are in accord with corresponding, experimental ones; they clearly indicate that objectives of the Materials Genome Initiative (MGI) can be reached with a widespread utilization of cDFT [MRS Advances 8, 619-625 (2023)]. Density functional theory ; Computer science ; Statistical physics ; Computational chemistry ; Physics ; Chemistry Machine Learning in Materials Science ; X-ray Diffraction in Crystallography
Authors: Rachel L. Edwards | Kathleen N. McAllister | Jenna C. McGuffey | Cory J. Knoot | Anna J. Hooppaw | Joseph J. Mackel | Bibi Zhou | Lloyd S. Robinson | Nichollas E. Scott | Christian M. Harding
Source: Journal of Biological Chemistry (article, 2025-11-06)
Field: Chemistry — Organic Chemistry

Enhancing O-linking oligosaccharyltransferase functionality through directed evolution Polysaccharide protein conjugate vaccines consist of bacterial polysaccharides covalently linked to carrier proteins. Bioconjugate vaccines are a type of polysaccharide protein conjugate vaccine produced by oligosaccharyltransferases, which catalyze the en bloc transfer of polysaccharides to specific amino acid motifs, called sequons, engineered into carrier proteins. The O-linking oligosaccharyltransferase PglS has been shown to have the broadest substrate repertoire, transferring virtually any saccharide to engineered carrier proteins, making it an attractive bioconjugation tool for next generation vaccine development. Yet, the efficiency of glycan transfer varies depending on the polysaccharide substrate. Successful bioconjugation hinges upon the ability of an oligosaccharyltransferase to efficiently transfer a polysaccharide to the engineered carrier protein. Therefore, enhancing glycosylation efficiency to produce carrier proteins that are highly glycosylated is a key aspect of developing scalable processes. Using directed evolution and the group B Streptococcal serotype V capsular polysaccharide as substrate, we identified single amino acid substitutions in PglS that improved enzymatic transfer of the group B Streptococcal serotype V polysaccharide to carrier proteins. Combinatorial amino acid substitutions and the incorporation of multiple sequons in the carrier protein further increased production and quality of the bioconjugate as determined by enzyme-linked immunosorbant assay and mass spectrometry (MS). Unexpectedly, the PglS variants were found to glycosylate two independent serine residues located within the sequon, a phenomenon not observed for the wildtype enzyme, resulting in significantly enhanced glycosylation activity. Such engineered PglS oligosaccharyltransferases, which increase the ratio of polysaccharide to carrier protein, are expected to improve large scale bioconjugation processes. Bioconjugation ; Glycosylation ; Glycan ; Polysaccharide ; Conjugate ; Carbohydrate conformation ; Protein engineering ; Directed evolution Carbohydrate Chemistry and Synthesis ; Glycosylation and Glycoproteins Research ; Pneumonia and Respiratory Infections
Authors: Saima Altaf  1 | Qandeel Fatima  1 | Bisma  2 | Anoosha Ramzan  1 | Memona Sarwar  3 | Bano Rani | Rabia Tabassum  1 and Zainab Bibi  1*
Source: Agrobiological Records (article, 2025-01-01)
Field: Materials Science — Biomaterials

TAILORED NANOPARTICLES IN PRECISION ANIMAL AND HUMAN ONCOLOGY: ENGINEERING TUMOR-SELECTIVE DELIVERY AND MICROENVIRONMENT INTERPLAY Precision oncology aims to provide personalized cancer treatment to maximize efficacy while minimizing systemic toxicity.Conventional therapies such as chemotherapy and radiotherapy have the drawbacks of lacking specificity in their toxicity, tumor selectivity, and resistance.Tailored nanoparticles (NPs) have demonstrated outstanding potential to remove such barriers by infiltrating tumors selectively, releasing their cargo in a controlled manner, and by altering the tumor microenvironment (TME).This review summarizes recent advancements in NPs engineering, including lipid-based, polymeric, inorganic, and hybrid carriers, as well as surface conjugations and stimuli-responsive designs that can improve targeting specificity.The complex interactions of NPs with the TME have been outlined, and strategies to address the adverse effects of hypoxia, acidity, enzyme activity, and extracellular barriers are discussed.Applications to targeted chemotherapy, gene and RNA therapeutics, photothermal and photodynamic therapies, immunotherapy, and theranostics are discussed in animals and humans, along with preclinical and clinical translation successes.Challenges and considerations towards successful translation into clinical practice are outlined.Overall, tailored NP-based therapy is highly encouraging for reengineering cancer treatment with precision, efficacy, and versatility in the era of next-generation oncology. Nanoparticle ; Nanomedicine ; Animal model ; Drug delivery Nanoparticle-Based Drug Delivery ; Nanoparticles: synthesis and applications ; Cancer Research and Treatments
Authors: Omid Moztarzadeh | Arezou Taherpour | Avat Taherpour | Morteza Jamshidi | Václav Babuška
Source: Scientific Reports (article, 2025-12-05)
Field: Chemistry — Organic Chemistry

Study of fullerene C60 effect on Escherichia coli in presence of antibiotics The growing concern over antibiotic resistance necessitates novel strategies to enhance antimicrobial efficacy. This study investigates the synergistic effect of fullerene C<sub>60</sub> on antibiotic susceptibility in Escherichia coli. In a standardized modification of the disc diffusion method, the zones of inhibition were measured on Mueller-Hinton agar with and without supplementation of fullerene C<sub>60</sub> after incubation for 10 and 24 h, respectively. Fullerene C<sub>60</sub> was noted for strengthening the antibacterial action of several antibiotics, especially to the extent of conversion of the bacteriostatic effect to bactericidal over a period. A statistically significant enhancement in the diameter of zones of inhibition was observed with tetracycline and co-trimoxazole, whereas amikacin and gentamicin evidenced only slight increases. The findings indicate that fullerene C<sub>60</sub> could disrupt bacterial membrane integrity or metabolic activity, thereby potentiating the antibiotics. This paves the way for introducing nanomaterials like fullerene C<sub>60</sub> into treatment strategies to target antibiotic resistance and bring about better therapeutic outcomes in bacterial infections. Amikacin ; Antibiotics ; Escherichia coli ; Gentamicin ; Fullerene ; Tetracycline ; Antimicrobial ; Antibiotic resistance Fullerene Chemistry and Applications ; Boron and Carbon Nanomaterials Research ; Graphene and Nanomaterials Applications
Authors: Efi-Maria Papia | Vassilios Constantoudis | Youmin Hou | Prexa Shah | Michael Kappl | Εvangelos Gogolides
Source: Metrology (article, 2025-05-07)
Field: Materials Science — Polymers and Plastics

Spatial Patterns in Fibrous Materials: A Metrological Framework for Pores and Junctions Several materials widely used in scientific research and industrial applications, including nano-filters and neuromorphic circuits, consist of fiber structures. Despite the fundamental structural similarity, the key feature that should be considered depends on the specific application. In the case of membranes and filters, the main concern has been on the pores among fibers, whereas in neuromorphic networks the main functionality is performed through the junctions of nanowires simulating neuron synapses for information dissemination. Precise metrological characterization of these structural features, along with methods for their effective control and replication, is essential for optimizing performance across various applications. This paper presents a comprehensive metrological framework for characterizing the spatial point patterns formed by pores or junctions within fibrous materials. The aim is to probe the influence of fiber randomness on both the point patterns of intersections (ppi) and pores (ppp). Our findings indicate a strong tendency of ppi toward aggregation, contrasting with a tendency of ppp toward periodicity and consequent pore uniformity. Both patterns are characterized by peculiarities related to collinearity effects on neighboring points that cannot be captured by the conventional anisotropy analysis of point patterns. To characterize local collinearity, we develop a method that counts the number of collinear triplets of nearest neighbor points in a pattern and designs an appropriate parameter to quantify them, also applied to scanning electron microscopy (SEM) images of membranes, demonstrating consistency with simulated data. Metrology ; Materials science ; Nanotechnology ; Computer science ; Physics ; Optics Textile materials and evaluations ; Advanced Sensor and Energy Harvesting Materials ; Material Properties and Processing
Authors: N. Mohammed
Source: Materials research proceedings (article, 2025-02-12)
Field: Materials Science — Materials Chemistry

Assessment of ready-mix concrete properties in various zones of concrete samples Abstract. In this work, the surface, core, and interface portions of concrete samples are examined to determine the characteristics of ready-mix concrete. The goal of the study is to comprehend how distinct zones inside concrete samples impact water absorption and compressive strength test. For the purpose of assessing these qualities, concrete samples were gathered and processed in accordance with conventional protocols. As the surface displays distinct properties from the core and interface areas, the results show notable differences in attributes between the zones. The concrete's top zone side was found to have the highest water absorption. In addition, site curing (SC2) has been resulted to be an improved way to cure concrete since it leads to lower water absorption and greater compressive strength as compared to Site Curing (SC1). Compressive strength in every zone remained within the expected range, indicating effective mix design and compaction. There is a significant difference between the two sites, site cures SC2 and SC1. In order to maximize the performance of concrete, zone-specific features are considered. These findings have consequences for concrete mix design and building techniques. Computer science Structural mechanics and materials ; Industrial Engineering and Technologies ; Advanced Energy Technologies and Civil Engineering Innovations
Authors: Asiye Akyıldız | Tüba Şimşek Mertoğlu | Nuray İnan Çınkır | Erdal Ağçam
Source: Harran Tarım ve Gıda Bilimleri Dergisi (article, 2025-06-11)
Field: Chemistry — Analytical Chemistry

Modeling quality changes in heat-processed orange juice: a comparative study of artificial neural network and multiple linear regression approaches The purpose of the study was to assess the prediction ability of multiple linear regression (MLR) and artificial neural network (ANN) models for the browning index, total carotenoid content, 5-hydroxymethylfurfural (HMF) and ascorbic acid of orange juice during storage after heat processing. For ANN models, the effect of neuron number of the hidden layer, epoch number, training algorithms and transfer functions are investigated using the trial-error method for selecting best design ANN models. The different methods (stepwise and enter) in multiple linear regression models were performed for detecting impact of independent variables on dependent variables. The performance of ANN and MLR models was determined through unseen data by means of statistical analysis. Regarding performance indices of ANN models for test data, overall R and R2 were recorded as follows: 0.92 and 0.84 (browning index), 0.99 and 0.98 (HMF), 0.92 and 0.86 (ascorbic acid), 0.97 and 0.94 (total carotenoid content), respectively. R and R2 values of MLR models for test data were 0.79 and 0.68 (browning index), 0.94 and 0.88 (HMF), 0.92 and 0.85 (ascorbic acid), 0.93 and 0.90 (total carotenoid content), respectively. Both models provided accurate predictions. However, the superior predictive power of ANN models is that they can learn directly from examples without calculating the parameters using statistical techniques. The results revealed that ANN models showed greater potential with high R and R2 value, and the lowest error values when compared with the MLR model, but both ANN and MLR had almost same performance for prediction of ascorbic acid. Artificial neural network ; Orange juice ; Linear regression ; Computer science ; Artificial intelligence ; Biological system ; Food science ; Machine learning ; Chemistry ; Biology Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Advanced Chemical Sensor Technologies
Authors: Laia Coronas Sala | Parfait Atchade-Adelomou
Source: Electronics (article, 2025-07-14)
Field: Materials Science — Materials Chemistry

QMProt: A Comprehensive Dataset of Quantum Properties for Proteins We introduce Quantum Mechanics for Proteins (QMProt), a dataset developed to support quantum computing applications in protein research. QMProt contains precise quantum-mechanical and physicochemical data, enabling the accurate characterization of biomolecules and supporting advanced computational methods like molecular fragmentation and reassembly. The dataset includes 45 molecules covering all 20 essential human amino acids and their core structural elements: amino terminal groups, carboxyl terminal groups, alpha carbons, and unique side chains. QMProt primarily features organic molecules with up to 15 non-hydrogen atoms (C, N, O, S), offering comprehensive molecular Hamiltonians, ground state energies, and detailed physicochemical properties to enhance reproducibility and advance quantum simulations in molecular biology, biochemistry, and drug discovery. Quantum ; Computer science ; Computational biology ; Physics ; Biology ; Quantum mechanics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: А. В. Лавров | Nikita Shepelev | О. А. Донцова | Maria P. Rubtsova
Source: Biochemistry (Moscow) (review, 2025-11-01)
Field: Chemistry — Spectroscopy

Methodological Toolbox for Identifying and Studying Micropeptides: From Genome to Function Micropeptides encoded by small open reading frames (sORFs) represent a novel, actively studied class of functional molecules regulating key cellular processes. Studying micropeptides is complicated by methodological challenges, in particular, their small size, low cellular abundance, and difficulty in generating specific antibodies. The review systematizes modern approaches to the identification and functional characterization of micropeptides. The main strategies for their discovery include the use of bioinformatic algorithms, global translation analysis via ribosome profiling, direct detection using mass spectrometry-based proteomics, and phenotypic screenings. The methods for confirming the functions of micropeptides and elucidating molecular mechanisms of their action genetic knockouts, affinity tagging for visualization, and investigation of protein-protein interactions. The review discusses key challenges and future prospects in the field, emphasizing the importance of an integrated multi-omics approach for the comprehensive micropeptidome mapping. Toolbox ; Identification (biology) ; Function (biology) ; Key (lock) ; Translation (biology) ; Genome ; Class (philosophy) Advanced Proteomics Techniques and Applications ; vaccines and immunoinformatics approaches ; Monoclonal and Polyclonal Antibodies Research
Authors: Song‐Jeng Huang | Chunhua Liu | Sathiyalingam Kannaiyan | Yudhistira Adityawardhana
Source: International Journal of Engineering and Technology Innovation (article, 2025-07-25)
Field: Materials Science — Biomaterials

Effect of Silicon Dioxide-Reinforcement on the Mechanical Properties of AZ91 Alloy through Equal Channel Angular Pressing This study aims to investigate the enhancement of AZ91 magnesium-aluminum alloy by reinforcing it with 3 wt.% silicon dioxide and processing it through Equal Channel Angular Pressing (ECAP). Specimens with 0 wt.% and 3 wt.% silicon dioxide are fabricated using gravity casting and mechanical stirring, followed by T4 heat treatment and ECAP. Microstructural analysis using scanning electron microscopy (SEM) and X-ray diffraction (XRD) reveals that silicon dioxide is uniformly dispersed, refining the grain structure and dissolving the β-phase, leading to improved ductility. Mechanical testing shows that adding 3 wt.% silicon dioxide increases the yield strength (YS) by 15.26% and the ultimate tensile strength (UTS) by 23.65% after T4 treatment. ECAP further enhances these values by 19.92% and 41.35%, respectively, while increasing hardness by 15.95%. The improved strength-to-weight ratio makes this alloy suitable for automotive, aerospace, and electronics applications, particularly for lightweight structural components. Pressing ; Materials science ; Alloy ; Silicon dioxide ; Reinforcement ; Channel (broadcasting) ; Silicon ; Composite material ; Metallurgy ; Engineering ; Electrical engineering Magnesium Alloys: Properties and Applications ; Aluminum Alloys Composites Properties ; Advanced Welding Techniques Analysis
Authors: Indra Wahyudi | Sitti Wajizah | Agus Arip Munawar | Efstathios Kaloudis | Samadi Samadi
Source: BIO Web of Conferences (article, 2025-01-01)
Field: Chemistry — Analytical Chemistry

Chemometric approach based on feed NIR spectra for rapid assessment of digestibility profiles in unconventional feedstuffs Digestibility profiles serve as vital indicators of feedstuffs' quality, determining how effectively livestock utilise feed nutrients for growth and production. This study develops a rapid and non-destructive model for the digestibility quality of unconventional feedstuffs, which integrates feed NIR spectra with chemometric techniques. A total of 30 samples (citronella residues) obtained from the fermentation process were used, and their NIR spectra (1000~2500 nm) were acquired using a BUCHI NIRFlex N-500 spectrometer. Reference digestibility profiles, including dry matter (IVDMD), organic matter (OM), and pH of rumen fluid, were measured using the two-stage digestion method. Partial least squares regression (PLSR), ridge regression (Ridge), adaptive boosting (AdaBoost), and support vector machine regression (SVMR) models were then constructed to assess digestibility quality. Model performance was assessed using the coefficient of determination (R 2 ), root-mean-square error (RMSE), and residual predictive deviation (RPD). The results show that the performance of the digestibility profile prediction model meets the accepted standards for NIRS calibration. Notably, the SVMR model exhibits exceptional stability and performance, achieving an R 2 value of ≥ 0.97 and a low RMSE, outperforming the AdaBoost, Ridge, and PLSR models. These findings confirm that the calibration model has significant potential for further independent validation to serve as a rapid-quality assessment tool in analyzing the digestibility profiles of feedstuffs. Partial least squares regression ; Dry matter ; Calibration ; Coefficient of determination ; Linear regression ; Regression analysis ; Regression ; Organic matter ; Residual Spectroscopy and Chemometric Analyses ; Soil Geostatistics and Mapping ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Sophie Primig | Megumi Kawasaki
Source: Journal of Materials Science Metallurgy (article, 2025-11-20)
Field: Materials Science — General Materials Science

Editorial: Journal of Materials Science: Metallurgy Weldability ; Extractive metallurgy ; Materials testing ; Welding ; Work (physics) Metallurgical and Alloy Processes ; Material Selection and Properties ; Advanced materials and composites
Authors: Sk.R. Anisur | D. Debashis
Source:  (article, 2025-02-13)
Field: Materials Science — Materials Chemistry

INVESTIGATION OF HYDROGEN PRODUCTION IN ACCIDENT SCENARIOS OF VVER-1200 REACTOR COMPARING ZIRCONIUM-BASED CLADDING WITH ACCIDENT TOLERANT FUEL USING SERPENT MONTE CARLO CODE Hydrogen production in severe nuclear accidents poses a significant threat to reactor safety, as exemplified by the Fukushima Daiichi disaster. This study investigates hydrogen generation in the VVER-1200 reactor under accident conditions, focusing on the zirconium-steam reaction responsible for hydrogen release in Zircaloy cladding. Using the SERPENT Monte Carlo simulation code, we model the reaction rates and hydrogen production volumes at elevated temperatures (1200°C), simulating a loss-of-coolant accident (LOCA). Results show substantial hydrogen production from the zirconium-steam reaction, with rates escalating with increasing burnup due to thermal and neutron flux effects. Conversely, Accident Tolerant Fuel (ATF) cladding materials such as SiC composites and FeCrAl alloys exhibit negligible hydrogen production, as they do not react with steam under similar conditions. The findings highlight ATF’s superiority in mitigating hydrogen-related risks, ensuring reactor integrity, and preventing potential explosions. This comparative analysis highlights the clear advantages of ATF cladding materials in reducing oxidation kinetics, minimizing hydrogen evolution, and enhancing reactor safety margins. The findings underscore the critical importance of incorporating ATF into the design and operation of VVER-1200 reactors and other advanced nuclear systems to mitigate hydrogen-related risks, prevent explosions, and ensure reactor integrity during severe accidents. VVER ; Nuclear engineering ; Cladding (metalworking) ; Monte Carlo method ; Zirconium ; Hydrogen ; Materials science ; Environmental science ; Computer science ; Engineering ; Chemistry ; Metallurgy ; Mathematics ; Statistics Nuclear Materials and Properties ; Nuclear reactor physics and engineering ; Nuclear and radioactivity studies