Browse Articles

RGO-Pt as an effective catalyst for U(IV) generation under hydrogen

Abstract Effective generation of U(IV) from U(VI) is a key step to achieve the partitioning of Pu from U in a spent nuclear fuel reprocessing plant. Reduction under a hydrogen atmosphere is one of the methods for the generation of U(IV) from U(VI) in the presence of a catalyst. Towards this, we have developed novel reduced graphene oxide (RGO)-supported Pt catalysts with varying RGO to Pt ratios. All these catalysts were tested for their catalytic performance for U(VI) to U(IV) reduction under hydrogen, and the performance was compared with the literature-reported SiO2-Pt model catalyst. During the catalytic study, the dual role of Pt was confirmed. It helps the dispersion of materials in the aqueous reaction medium and provides the active surface for the U(VI) reduction reaction using hydrogen. In this regard, Pt nanoclusters with larger sizes were identified for effective catalysis instead of the smallest size.

Numerically efficient quasi-adiabatic propagator path integral approach with two independent non-commuting baths

Path integral methods, such as the quasi-adiabatic propagator path integral (QUAPI), are widely used in general-purpose and highly accurate numerical benchmark simulations of open quantum systems, particularly in regimes inaccessible to perturbative methods. Nevertheless, the applicability of the QUAPI method to realistic systems of interest is restricted by the exponentially growing computer memory requirements with respect to the size of the quantum system and the time range of non-Markovian correlation effects. This exponential “wall” becomes even more severe for multiple non-commuting fluctuating environments. In the present work, we address the numerical efficiency and accuracy of approximations that have been introduced for the QUAPI method with a single general environment, for the case of two independent non-commuting environments where one of them is considered as a pure dephasing environment. In particular, we consider a sharply defined cutoff of the memory time, path filtering, and mask assisted coarse graining of influence functional coefficients as approximations. We demonstrate that commonly applied numerical techniques, such as path filtering, cannot be straightforwardly transferred to the two-bath case even in the weak-coupling and quasi-Markovian limits. On the other hand, the sharply defined memory cutoff can be accurately handled with the mask assisted coarse graining approach. Our findings demonstrate that if system coupling operators to different baths do not commute, the additive nature of the statistically independent environments may be misleading. In particular, the quasi-Markovian nature of a pure dephasing bath is lost once there simultaneously exists another non-commuting source of fluctuations.

Metabolomics combined with metagenomics analysis reveals the potential mechanism of Zhejiang psyllium polysaccharides against hyperuricemia in rats

Magnetic properties and spin–spin interaction in nitrogen-doped fullerene nanostructures

Fullerenes encapsulating nitrogen atoms, also called endohedral fullerenes, are spin active. The magnetic moment is localized on the nitrogen atom, but the spin dynamics is shown to be governed by the coupling to the fullerene orbitals, allowing for an indirect spin manipulation by acting on the fullerene and its environment. Here, for multiple ground-state endohedral fullerenes, the inter-fullerene spin–spin interactions are investigated with a focus on the effects of stable geometric arrangements (linear, triangular, and more complex arrangements). Performing full ab initio simulations, we aim at an understanding of how the interactions between spins depend on both the structural features of the fullerene molecules and their molecular orbitals. Our computational study explores the role of spin exchange interactions, potential spin frustration, and how these phenomena can be manipulated to achieve desired magnetic behaviors; thus, it can guide the design of new materials for spintronic devices, quantum information processing, and other applications that require control over spin–spin interactions is decisive.

Serial mediating role of future time perspective and grit in the relationship between growth mindset and academic engagement

Supercooling behaviors of normal alkanes in the homologous series C6H14 to C11H24 under Titan conditions

The supercooling behaviors of n-alkanes during the solid–liquid phase transition offer a promising explanation to the phenomenon of energy conversion and transfer across seasons and regions observed on Titan. However, research on the supercooling behaviors of n-alkanes under Titan’s internal pressure (P) and temperature (T) conditions (<4.9 GPa; 93–900 K) remains inadequate. Here, we present findings from laboratory experiments conducted under high P–T conditions, exploring the P–T phase diagrams and supercooling behaviors of six n-alkanes [n-CnH2n+2 (6 ≤ n ≤ 11)]. The current results indicate that all measured n-alkanes exhibit supercooling behaviors, with the supercooling degree increasing as pressure increases. At the same pressure, the supercooling degree of both odd and even n-alkanes decreases as the carbon chain length increases. Under Titan’s central pressure of 4.9 GPa, n-heptane shows the highest supercooling degree among the measured n-alkanes, reaching up to 63 K.

An enhanced fusion of transfer learning models with optimization based clinical diagnosis of lung and colon cancer using biomedical imaging

Extension of a hydrate model for structure H applied to multiparameter equations of state

This work introduces an extension of an existing thermodynamic model for gas hydrates based on the van der Waals and Platteeuw (vdWP) approach for structure H (sH) hydrates. A model for the hydrate volume is adapted to the hexagonal unit cell with a universal correlation for the thermal expansion, guest-specific lattice parameters at reference conditions, a compressibility relation given in terms of the Murnaghan equation of state (EOS), and a multi-layered description of the hydrate cavities. Available experimental data for the lattice parameters are represented within ±0.05 Å, while molecular simulation predictions show larger deviations. The results allow for the determination of lattice parameters for 10 help gases and 15 large-guest molecule substances (LGMSs), which enables the application to a wide range of hydrate-forming mixtures. In combination with multiparameter EOS for fluid phases, i.e., the IAPWS-95 for water, the proposed vdWP-type model is validated by comparing predicted hydrate formation conditions with experimental data for methylcyclohexane or 2-methylbutane containing mixtures, demonstrating good agreement. The fluid EOS for methylcyclohexane systems with water, carbon dioxide, and methane and 2-methylbutane with water is revised.

Machine learning ensemble technique for exploring soil type evolution

Transport properties of nanoconfined fluids: A review

The diffusion coefficient, viscosity, and thermal conductivity of fluids serve as the primary metrics for characterizing mass, momentum, and heat transfer. However, these transport properties exhibit significant deviations from those of bulk fluids when confined in nanoscale environments. In this work, we present a comprehensive overview of the transport properties of nanoconfined fluids (NCFs) with a focus on simple confinement systems and water by integrating findings from previous and recent researches. This discussion begins with an examination of methodologies for assessing transport properties through molecular dynamic (MD) simulations, with a focus on the equilibrium MD method. Subsequently, we delineate the unique characteristics of NCFs’ transport properties, which include anisotropy, size dependence, and layered distribution. Furthermore, we conduct a thorough analysis of the fundamental physical mechanisms that dominate these transport properties. We highlight that the diffusion coefficient, viscosity, and thermal conductivity are significantly affected by these rationales such as the displacement, friction, and collision frequency of molecular motions within the NCFs. We then identify various factors that may directly or indirectly influence these mechanisms and related transport properties, including surface electrostatic property, surface wettability, surface roughness, surface flexibility, and fluid composition. In conclusion, we provide a comprehensive summary and perspective on the research emphasis and challenges associated with the transport properties of NCFs. This review not only facilitates the comprehension of the fundamental mechanisms governing the transport properties of NCFs but also holds promise for informing a range of industrial applications, including seawater desalination, gas separation, and chip cooling.

Association between left ventricular remodeling and coronary chronic total occlusion in hypertensive coronary artery disease patients

Electron–vibrational resonance and optical lineshapes: Complex time-dependent Redfield theory vs vibronic picture

We study the validity of the complex time-dependent Redfield (ctR) theory in describing optical lineshapes near electron–vibrational resonance, when a mixing of the electronic states is promoted by a vibrational quantum. We explore the model system containing an electronically excited state coupled to a red-shifted charge-transfer (CT) state. When the vibrational sublevels of the CT are in resonance with the zero-phonon line of the excited state, they can borrow a significant part of the dipole strength, thus producing a mixed configuration with splitting and shifting of the excited state transitions. Comparing the ctR lineshapes with explicit exciton–vibrational structure and with nonperturbative absorption spectra, we have found that ctR theory reproduces (at least qualitatively) the main features of the vibronic picture emerging from resonant exciton–vibrational mixing. On the contrary, these resonant phenomena cannot be explained by the modified Redfield theory, where the off-diagonal phonon-induced modulations of the exciton transitions are treated in a simplified way. On the other hand, we reveal shortcomings of the ctR approaches that are working in a pure exciton basis, where the exciton-CT mixing is supposed to be uniform (i.e., not dependent on nuclear coordinates). As a result, the degree of exciton-CT mixing is typically overestimated in the ctR model, thus leading to the appearance of spectral components with the intensities and energies deviating from the exact (nonperturbative) solution.

Subgroup analysis of treatment pathways and clinical outcomes in Hodgkin lymphoma in Latin America from the retrospective B-HOLISTIC study

Abstract Real-world data on Hodgkin lymphoma (HL) treatment and outcomes in Latin America are limited. The B-HOLISTIC study (2010–2013) retrospectively assessed treatment patterns and outcomes in patients with stage IIB–IV classical HL receiving frontline chemotherapy (frontline cHL) or relapsed/refractory HL (RRHL) in regions outside Europe and North America. This subgroup analysis presents findings from patients enrolled from treatment centers in Argentina, Colombia, and Mexico. The primary endpoint was progression-free survival (PFS) in patients with RRHL. Other endpoints included overall survival (OS), best clinical response, and treatment patterns. In Latin America (frontline cHL: 344; RRHL: 92), the most common frontline regimen was ABVD (doxorubicin, bleomycin, vinblastine, dacarbazine). In patients with RRHL receiving salvage chemotherapy (92.4%), common regimens were ESHAP (etoposide, methylprednisolone, cytarabine, cisplatin) and ICE (ifosfamide, carboplatin, etoposide). Overall, 68.2% of eligible patients with RRHL underwent stem cell transplantation (SCT). Median PFS and OS in the RRHL group was 20.2 and 87 months, respectively; the 5-year PFS rate was 27.1%. Survival outcomes were improved in patients who underwent SCT than those without SCT. Median PFS and OS in the cHL group were not reached. These data demonstrated that while real-world HL treatment in Latin America was consistent with guidelines during the study period, clinical outcomes were suboptimal compared with developed regions. This emphasizes the need for novel therapies and improved progression to SCT in this patient population. These findings may offer valuable insights and serve as a reference for future studies in this region. ClinicalTrials.gov Identifier: NCT03327571, registered October 31, 2017.

A practical quasi-classical trajectory method to avoid zero-point energy leakage in dissociative chemisorption of polyatomic molecules on surfaces

An accurate prediction of dissociative sticking probabilities (S0) of polyatomic molecules on surfaces has long been a challenging task, because a fully coupled quantum mechanical treatment of numerous degrees of freedom is computationally forbidden. While a quasi-classical trajectory (QCT) approach is much more effective, it often suffers from the leakage of vibrational zero-point energy of the polyatomic molecule, leading to significant and, moreover, initial-state-dependent overestimation of S0 at low incidence energies. Here, inspired by the most frequently used QCT implementation in gas-phase reactions, we propose applying Gaussian binning (GB) instead of standard histogram binning for both scattered and adsorbed species to calculate S0 by the weighted population of trajectories. This new recipe, coupled with two different initial sampling conditions, is tested against the fully coupled quantum dynamical method in D2O dissociation on a rigid Ni(111) surface. We find direct evidence of zero-point energy leakage, rendering the energy in the O–D vibration of the dissociated OD* adsorbate much smaller than its zero-point energy, while GB largely avoids the influence of this artifact on the reactivity. The corrected QCT reaction probabilities thus yield much better agreement with quantum ones than standard QCT results. Impressively, similar improvements are achieved for D2O in both the vibrationally ground state and excited states. This practical QCT method makes it possible to predict reliable quantum-state-resolved S0 of polyatomic molecules on surfaces well below the barrier height and the associated mode-specificity.

Integrated bioinformatics analysis identifies CHAD association with osteoporosis and in vitro chondrogenic effects of Wogonin

Toward an accurate equation of state for hard polyhedron fluids

An alternative to corrected high-order virial expansions to derive an accurate equation of state for fluids made up of bodies of extreme nonsphericity is proposed. Instead of empirically corrected virial expansions of high order, we use the virial coefficients within the functional form of the hard convex body equation of state. The balance between the accuracy of the equation and the number of the used virial coefficients and adjustable parameters is examined. First, for the fluid of tetrahedra, the recommended equation with only three virial coefficients and four adjustable parameters is considered for the complete set of fourteen polyhedron fluids. An excellent agreement with simulation data is achieved for all the models. The next equation in accuracy is the equation of Tian et al. [Phys. Chem. Chem. Phys. 21, 13109 (2019)], which employs seven virial coefficients and two adjustable parameters. The results are also compared with purely theoretical equations, which are considerably inferior and have unpredictable accuracy for different models.

Reinforcing polyvinyl alcohol with corn stover-derived nanofibrillated cellulose for improved mechanical and barrier properties

Chiral vibrational modes in small molecules

The development of quantitative methods for characterizing molecular chirality can provide an important tool for studying chirality-induced phenomena in molecular systems. Significant progress has been made in recent years toward understanding the chirality of molecular normal vibrational modes, mostly focusing on vibrations of helical molecular structures. In the present study, we examine the applicability of two methodologies previously used for helical structures for the quantification of the chirality of molecular normal modes across a range of small, not necessarily helical, molecules. The first approach involves the application of the Continuous Chirality Measure (CCM) to each normal mode by associating the mode with a structure formed by imposing the corresponding motion relative to a common origin. The second approach assigns to each normal mode a pseudoscalar defined as the product of atomic linear and angular momentum summed over all atoms. In particular, using the CCM also as a measure of the chirality of the underlying molecular structure, we establish the existence of a correlation between the chirality of molecular normal modes and that of the underlying molecular structure. Furthermore, we find that normal modes associated with different frequency ranges of the molecular vibrational spectrum exhibit distinct handedness behavior.

A recurrent multimodal sparse transformer framework for gastrointestinal disease classification

Abstract Accurate and early diagnosis of gastrointestinal (GI) tract diseases is essential for effective treatment planning and improved patient outcomes. However, existing diagnostic frameworks often face limitations due to modality imbalance, feature redundancy, and cross-modal inconsistencies, particularly when dealing with heterogeneous data such as medical text and endoscopic images. To bridge these gaps, this study proposes a novel recurrent multimodal principal gradient K-proximal sparse transformer (RMP-GKPS-transformer) framework for comprehensive GI disease classification. The approach integrates clinical text and WCE images using a robust multi-modal fusion strategy that incorporates Bio-RoBERTa for textual feature extraction, a graph vision spatial channel attention transformer network for image feature learning, and cross-attention mechanisms for modality alignment. Further, the model employs principal component analysis (PCA) for dimensionality reduction and gradient boosting machines (GBMs) for semantic conflict resolution. Classification is performed using an ensemble of random forest KNN, proximal policy optimization (PPO), and a sparse radial basis function (RBF) kernel to ensure accuracy and interpretability. Experimental evaluation on publicly available datasets achieved 99.82% accuracy, a Dice coefficient of 98.7%, and significantly lower execution time compared to state-of-the-art methods. The results confirm the framework’s effectiveness in aligning and leveraging multi-modal data for precise classification of six GI diseases, offering a scalable and interpretable solution for enhanced clinical decision-making in gastroenterology.

Ions at electrochemical interfaces: From explicit to implicit molecular solvent descriptions

We investigate the interplay between electronic screening inside a metal and screening by a polar molecular solvent, focusing on their impact on the charge induced by an ion and the solvent structure at the interface. To that end, we consider atomistically resolved electrodes within the Thomas–Fermi model of screening and describe the molecular solvent either explicitly via classical molecular dynamics or implicitly using molecular density functional theory (MDFT). In particular, we examine the effect of screening by tuning the Thomas–Fermi screening length lTF, the ion charge by considering Na+ and Cl−, and the solvent nature by studying water and acetonitrile. Consistent with our previous findings without solvent, lTF significantly affects the charge distribution inside the metal. However, lTF has no significant impact on the interfacial solvent structure, suggesting that its effect on the charge distribution induced inside the metal by the ion is essentially due to how the metal responds to the (same) external charge distribution, including the solvent, even though the coupling between both sides of the interface may play a secondary role. Furthermore, MDFT accurately reproduces fine details of the interfacial solvent structure around the ion at a fraction of the computational cost of MD simulations. These results highlight the relevance of MDFT as a powerful tool to model electrochemical systems at the molecular level.