搜索结果：Nitric oxide : biology and chemistry

The oxygen evolution reaction (OER) plays an important role in evaluating a photocatalyst and to understand its surface chemistry. In this work we present a comparative study of the OER on the oxide NaTaO$_3$ (113) surface and the oxynitride SrTaO$_2$N (001) surface. Oxynitrides are highly promising photocatalysts due to their smaller band gap and resulting better visible light absorption compared to oxides but our knowledge about their surface structure and chemistry is still very limited. With the goal to compare the surface chemistry of oxides and oxynitrides, we perform density functional theory calculations to obtain the free energy changes associated with the OER reaction steps. For the OER at the Ta site of the clean surfaces, our results predict the rate-limiting step for both materials to be the formation of the *OOH intermediate, with a larger overpotential for the oxide than the oxynitride (1.30 V vs 1.01 V). The Na site is found to be more active than the Ta site on the oxide surface with an OER overpotential of 0.88 V, whereas the OER at the Sr site on the oxynitride has an overpotential of 1.14 V. For the A sites, contrary to the Ta site, the deprotonation of *OH was

A tunable far-infrared laser sideband spectrometer was used to investigate a nitric oxide sample enriched in 18O between 0.99 and 4.75 THz. Regular, electric dipole transitions were recorded between 0.99 and 2.52 THz, while magnetic dipole transitions between the 2Pi(1/2) and 2Pi(3/2) spin-ladders were recorded between 3.71 and 4.75 THz. These data were combined with lower frequency data of N(18)$O (unlabeled atoms refer to (14)N and (16)O, respectively), with rotational data of NO, (15)NO, N(17)O, and (15)N(18)O, and with heterodyne infrared data of NO to be subjected to one isotopic invariant fit. Rotational, fine and hyperfine structure parameters were determined along with vibrational, rotational, and Born-Oppenheimer breakdown corrections. The resulting spectroscopic parameters permit prediction of rotational spectra suitable for the identification of various nitric oxide isotopologs especially in the interstellar medium by means of rotational spectroscopy.

We study the temporal and the synchronous behaviours in p53-Mdm2 regulatory network due to the interaction of its complex network components with the nitric oxide molecule. In single cell process, increase in nitric oxide concentration gives rise the transition to various p53 temporal behaviours, namely fixed point oscillation, damped oscillation and sustain oscillation indicating stability, weakly activated and strongly activated states. The noise in stochastic system is found to help to reach these states much faster as compared to deterministic case which is evident from permutation entropy dynamics. In coupled system with nitric oxide as diffusively coupling molecule, we found nitric oxide as strong coupling molecule within a certain range of coupling strength εbeyond which it become weak synchronizing agent. We study these effects by using correlation like synchronization indicator γobtained from permutation entropies of the coupled system, and found five important regimes in (ε-γ) phase diagram, indicating desynchronized, transition, strongly synchronized, moderately synchronized and weakly synchronized regimes respectively. We claim that there is the competition between the

Energetic electrons from the magnetosphere deposit their energy in the atmosphere and lead to production of nitric oxide (NO) in the mesosphere and lower thermosphere. We study the atmospheric NO response to a geomagnetic storm in April 2010 with WACCM (Whole Atmosphere Community Climate Model). Modeled NO is compared to observations by Solar Occultation For Ice Experiment/Aeronomy of Ice in the Mesosphere at 72-82$^{\circ}$S latitudes. We investigate the modeled NOs sensitivity to changes in energy and chemistry. The electron energy model input is either a parameterization of auroral electrons or a full range energy spectrum (1-750 keV) from National Oceanic and Atmospheric Administration/Polar Orbiting Environmental Satellites and European Organisation for the Exploitation of Meteorological Satellites/Meteorological Operational satellites. To study the importance of ion chemistry for the production of NO, WACCM-D, which has more complex ion chemistry, is used. Both standard WACCM and WACCM-D underestimate the storm time NO increase in the main production region (90-110 km), using both electron energy inputs. At and below 80 km, including medium-energy electrons ($>$30 keV) is

We introduce ChemPro, a progressive benchmark with 4100 natural language question-answer pairs in Chemistry, across 4 coherent sections of difficulty designed to assess the proficiency of Large Language Models (LLMs) in a broad spectrum of general chemistry topics. We include Multiple Choice Questions and Numerical Questions spread across fine-grained information recall, long-horizon reasoning, multi-concept questions, problem-solving with nuanced articulation, and straightforward questions in a balanced ratio, effectively covering Bio-Chemistry, Inorganic-Chemistry, Organic-Chemistry and Physical-Chemistry. ChemPro is carefully designed analogous to a student's academic evaluation for basic to high-school chemistry. A gradual increase in the question difficulty rigorously tests the ability of LLMs to progress from solving basic problems to solving more sophisticated challenges. We evaluate 45+7 state-of-the-art LLMs, spanning both open-source and proprietary variants, and our analysis reveals that while LLMs perform well on basic chemistry questions, their accuracy declines with different types and levels of complexity. These findings highlight the critical limitations of LLMs in

Nitric Oxide (NO) significantly impacts energy distribution and chemical processes in the mesosphere and lower thermosphere (MLT). During geomagnetic storms, a substantial influx of energy in the thermosphere leads to an increase in NO infrared emissions. Accurately predicting the radiative flux of Nitric Oxide is crucial for understanding the thermospheric energy budget, particularly during extreme space weather events. With advancements in computational techniques, machine learning (ML) has become a highly effective tool for space weather forecasting. This effort becomes even more worthwhile considering the availability of two decades of continuous NO infrared emissions measurement by TIMED/SABER along with several other key thermospheric variables. We present the scheme of development of an ML-based predictive model for Nitric Oxide Infrared Radiative Flux (NOIRF). Various ML algorithms have been tested for better predictive ability, and an optimized model (NOEMLM) has been developed for the study of NOIRF. This model is able to extract the underlying relationships between the input features and effectively predict the NOIRF. The NOEMLM predictions have very good agreements with

The remarkably strong chemical adsorption behaviors of nitric oxide on magnesia (001) film deposited on metal substrate have been investigated by employing periodic density functional calculations with Van der Waals corrections. The molybdenum supported magnesia (001) show significantly enhanced adsorption properties and the nitric oxide is chemisorbed strongly and preferably trapped in flat adsorption configuration on metal supported oxide film, due to the substantially large adsorption energies and transformation barriers. The analysis of Bader charges, projected density of states, differential charge densities, electron localization function, highest occupied orbital and particular orbital with largest Mg-NO-Mg bonding coefficients, are applied to reveal the electronic adsorption properties and characteristics of bonding between nitric oxide and surface as well as the bonding within the hybrid structure. The strong chemical binding of nitric oxide on magnesia deposited on molybdenum slab offers new opportunities for toxic gas detection and treatment. We anticipate that hybrid structure promoted remarkable chemical adsorption of nitric oxide on magnesia in this study will provide

We present new molecular modelling for 14NO and 15NO and a deep, blind molecular line survey at low radio frequencies (99-129 MHz). This survey is the third in a series completed with the Murchison Widefield Array (MWA), but in comparison with the previous surveys, uses four times more data (17 hours vs. 4 hours) and is three times better in angular resolution (1' vs. 3'). The new molecular modelling for nitric oxide and its main isotopologue has seven transitions within the MWA frequency band (although we also present the higher frequency transitions). Although we did not detect any new molecular lines at a limit of 0.21 Jy beam^-1, this work is an important step in understanding the data processing challenges for the future Square Kilometre Array (SKA) and places solid limits on what is expected in the future of low-frequency surveys. The modelling can be utilised for future searches of nitric oxide.

An accurate estimate of the energy budget (heating and cooling) of the ionosphere and thermosphere, especially during space weather events, has been a challenge. The abundance of Nitric Oxide (NO), a minor species in the thermosphere, is an important component of energy balance here because its production comes from energy sources able to break the strong bond of molecular nitrogen, and infrared emissions from NO play an important role in thermospheric cooling. Recent studies have significantly improved our understanding of NO chemistry and its relationship to energy deposition in the thermospheric photochemical reactions. In this study, the chemical scheme in the Global Ionosphere Thermosphere Model (GITM) is updated to better predict the lower thermospheric NO responses to solar and geomagnetic activity. We investigate the sensitivity of the 5.3-micron NO emission to F10.7 and Ap indices by comparing the global integrated emission from GITM with an empirical proxy derived from the Sounding of the Atmosphere using Broadband Emission Radiometry measurements. GITM's total emission agrees well within 20% of the empirical values. The updated chemistry scheme significantly elevates the

Nitric oxide is an open-shell molecule abundantly detected in the interstellar medium. A precise modeling of its radiative and collisional processes opens the path to a precise estimate of its abundance. We present here the first rate coefficients for fine and hyperfine (de-)excitation of NO by collisions with the most ubiquitous collision partner in the interstellar medium, $para$-H$_2$ hydrogen molecules, using a recently developed accurate interaction potential. We report quantum scattering calculations for transitions involving the first 74 fine levels and the corresponding 442 hyperfine levels belonging to both $F_1$ and $F_2$ spin-orbit manifolds. To do so, we have calculated cross sections by means of the quantum mechanical close-coupling approach up to 1000 cm$^{-1}$ of total energy and rate coefficients from 5 to 100 K. Propensity rules are discussed and the new NO-H$_2$ rates are compared to those available in the literature, based on scaled NO-He rates. Large differences are observed between the two sets of rate coefficients, and this comparison shows that the new collision rates must be used in interpreting NO emission lines. We also examined the effect of these new rat

We study how the temporal behaviours of p53 and MDM2 are affected by stress inducing bioactive molecules NO (Nitric Oxide) in the p53-MDM2-NO regulatory network. We also study synchronization among a group of identical stress systems arranged in a three dimensional array with nearest neighbour diffusive coupling. The role of NO and effect of noise are investigated. In the single system study, we have found three distinct types of temporal behaviour of p53, namely, oscillation death, damped oscillation and sustain oscillation, depending on the amount of stress induced by the NO concentration, indicating how p53 responds to the incoming stress. The correlation among the coupled systems increases as the value of coupling constant (ε) is increased (γincreases) and becomes constant after certain value of ε. The permutation entropy spectra H(ε) for p53 and MDM2 as a function of εare found to be different due to direct and indirect interaction of NO with the respective proteins. γversus εfor p53 and MDM2 are found to be similar in deterministic approach, but different in stochastic approach and the separation between γof the respective proteins as a function of εdecreases as system size i

This article frames the relation between biology and physics by characterizing the former as a subdiscipline rather than a special case of the latter. To do this, we posit biological physics as the science of living matter in contrast to classic biophysics, the study of organismal properties by physical techniques. At the scale of the individual cell, living matter is nonunitary, i.e., not composed of aggregated subunits, and has features (e.g., intracellular organizational arrangements and biomolecular condensates) that are unlike any materials of the nonliving world. In transiently or constitutively multicellular forms (social microorganisms, animals, plants), living matter sustains physical processes that are generic (shared with nonliving matter, e.g., subunit communication by molecular diffusion in cellular slime molds), biogeneric (analogous to nonliving matter but realized through cellular activities, e.g., subunit demixing in animal embryos) or nongeneric (pertaining to sui generis materials, e.g., budding of active solids in plants). This "forms of matter" perspective is philosophically situated in the dialectical materialism of Engels and Hessen and the multilevel physica

We survey and introduce concepts and tools located at the intersection of information theory and network biology. We show that Shannon's information entropy, compressibility and algorithmic complexity quantify different local and global aspects of synthetic and biological data. We show examples such as the emergence of giant components in Erdos-Renyi random graphs, and the recovery of topological properties from numerical kinetic properties simulating gene expression data. We provide exact theoretical calculations, numerical approximations and error estimations of entropy, algorithmic probability and Kolmogorov complexity for different types of graphs, characterizing their variant and invariant properties. We introduce formal definitions of complexity for both labeled and unlabeled graphs and prove that the Kolmogorov complexity of a labeled graph is a good approximation of its unlabeled Kolmogorov complexity and thus a robust definition of graph complexity.

Malfunction of the system which regulates the bloodflow in the brain is a major cause of stroke and dementia, costing many lives and many billions of pounds each year in the UK alone. This regulatory system, known as cerebral autoregulation, has been the subject of much experimental and mathematical investigation yet our understanding of it is still quite limited. One area in which our understanding is particularly lacking is that of the role of nitric oxide, understood to be a potent vasodilator. The interactions of nitric oxide with the better understood myogenic response remain un-modelled and poorly understood. In this thesis we present a novel model of the arteriolar control mechanism, comprising a mixture of well-established and new models of individual processes, brought together for the first time. We show that this model is capable of reproducing experimentally observed behaviour very closely and go on to investigate its stability in the context of the vasculature of the whole brain. In conclusion we find that nitric oxide, although it plays a central role in determining equilibrium vessel radius, is unimportant to the dynamics of the system and its responses to variation

We report on the collisional shift and line broadening of Rydberg states in nitric oxide (NO) with increasing density of a background gas at room temperature. As a background gas we either use NO itself or nitrogen (N$_{2}$). The precision spectroscopy is performed by a sub-Doppler three-photon excitation scheme with a subsequent readout of the Rydberg states realized by the amplification of a current generated by free charges due to collisions. The shift shows a dependence on the rotational quantum state of the ionic core and no dependence on the principle quantum number of the orbiting Rydberg electron. The experiment was performed in the context of developing a trace-gas sensor for breath-gas analysis in a medical application.

Understanding the biological mechanisms of disease is crucial for medicine, and in particular, for drug discovery. AI-powered analysis of genome-scale biological data holds great potential in this regard. The increasing availability of single-cell RNA sequencing data has enabled the development of large foundation models for disease biology. However, existing foundation models only modestly improve over task-specific models in downstream applications. Here, we explored two avenues for improving single-cell foundation models. First, we scaled the pre-training data to a diverse collection of 116 million cells, which is larger than those used by previous models. Second, we leveraged the availability of large-scale biological annotations as a form of supervision during pre-training. We trained the \model family of models comprising six transformer-based state-of-the-art single-cell foundation models with 70 million, 160 million, and 400 million parameters. We vetted our models on several downstream evaluation tasks, including identifying the underlying disease state of held-out donors not seen during training, distinguishing between diseased and healthy cells for disease conditions and

High Rydberg states of nitric oxide (NO) with principal quantum numbers between 40 and 100 and lifetimes in excess of 10 $μ$s have been prepared by resonance enhanced two-color two-photon laser excitation from the X $^2Π_{1/2}$ ground state through the A $^2Σ^+$ intermediate state. Molecules in these long-lived Rydberg states were detected and characterized 126 $μ$s after laser photoexcitation by state-selective pulsed electric field ionization. The laser excitation and electric field ionization data were combined to construct two-dimensional spectral maps. These maps were used to identify the rotational states of the NO$^+$ ion core to which the observed series of long-lived hydrogenic Rydberg states converge. The results presented pave the way for Rydberg-Stark deceleration and electrostatic trapping experiments with NO, which are expected to shed further light on the decay dynamics of these long-lived excited states, and are of interest for studies of ion-molecule reactions at low temperatures.

Multimodal scientific reasoning remains a significant challenge for large language models (LLMs), particularly in chemistry, where problem-solving relies on symbolic diagrams, molecular structures, and structured visual data. Here, we systematically evaluate 40 proprietary and open-source multimodal LLMs, including GPT-5, o3, Gemini-2.5-Pro, and Qwen2.5-VL, on a curated benchmark of Olympiad-style chemistry questions drawn from over two decades of U.S. National Chemistry Olympiad (USNCO) exams. These questions require integrated visual and textual reasoning across diverse modalities. We find that many models struggle with modality fusion, where in some cases, removing the image even improves accuracy, indicating misalignment in vision-language integration. Chain-of-Thought prompting consistently enhances both accuracy and visual grounding, as demonstrated through ablation studies and occlusion-based interpretability. Our results reveal critical limitations in the scientific reasoning abilities of current MLLMs, providing actionable strategies for developing more robust and interpretable multimodal systems in chemistry. This work provides a timely benchmark for measuring progress in

We report novel total electron scattering cross sections (TCS) from nitric oxide (NO) in the impact energy range from 1 to 15 eV by using a magnetically confined electron transmission apparatus. The accuracy of the data to within 5% and its consistency across the energy range investigated, shows significant discrepancies from previous works as to the major resonance features and magnitude of the TCS. Within the shape of the TCS, we have identified nine features which have been assigned to electron attachment resonances, most of them reported for the first time, while a comprehensive analysis of those peaking at 7.0, 7.8, and 8.8 eV has led to solve the controversy about dissociative electron attachment (DEA) cross-section that persisted for more than 50 years.