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High-resolution CARMA Observation of Molecular Gas in the North America and Pelican Nebulae
In this paper, we present the first results from a CARMA high-resolution {sup 12}CO(1-0), {sup 13}CO(1-0), and C{sup 18}O(1-0) molecular line survey of the North America and Pelican (NAP) Nebulae. CARMA observations have been combined with single-dish data from the Purple Mountain 13.7 m telescope, to add short spacings and to produce high-dynamic-range images. We find that the molecular gas is predominantly shaped by the W80 H ii bubble, driven by an O star. Several bright rims noted in the observation are probably remnant molecular clouds, heated and stripped by the massive star. Matching these rims in molecular lines and optical images, we construct a model of the three-dimensional structure of the NAP complex. Two groups of molecular clumps/filaments are on the near side of the bubble: one is being pushed toward us, whereas the other is moving toward the bubble. Another group is on the far side of the bubble, and moving away. The young stellar objects in the Gulf region reside in three different clusters, each hosted by a cloud from one of the three molecular clump groups. Although all gas content in the NAP is impacted by feedback from the central O star, some regions show no signs of star formation, while other areas clearly exhibit star formation activity. Additional molecular gas being carved by feedback includes cometary structures in the Pelican Head region, and the boomerang features at the boundary of the Gulf region. The results show that the NAP complex is an ideal place for the study of feedback effects on star formation.
Structural evidence for intermediates during O 2 formation in photosystem II
In natural photosynthesis, the light-driven splitting of water into electrons, protons and molecular oxygen forms the first step of the solar-to-chemical energy conversion process. The reaction takes place in photosystem II, where the Mn 4 CaO 5 cluster first stores four oxidizing equivalents, the S 0 to S 4 intermediate states in the Kok cycle, sequentially generated by photochemical charge separations in the reaction center and then catalyzes the O–O bond formation chemistry. Here, we report room temperature snapshots by serial femtosecond X-ray crystallography to provide structural insights into the final reaction step of Kok’s photosynthetic water oxidation cycle, the S 3 →[S 4 ]→S 0 transition where O 2 is formed and Kok’s water oxidation clock is reset. Our data reveal a complex sequence of events, which occur over micro- to milliseconds, comprising changes at the Mn 4 CaO 5 cluster, its ligands and water pathways as well as controlled proton release through the hydrogen-bonding network of the Cl1 channel. Importantly, the extra O atom O x , which was introduced as a bridging ligand between Ca and Mn1 during the S 2 →S 3 transition disappears or relocates in parallel with Y z reduction starting at approximately 700 μs after the third flash. The onset of O 2 evolution, as indicated by the shortening of the Mn1–Mn4 distance, occurs at around 1,200 μs, signifying the presence of a reduced intermediate, possibly a bound peroxide.
OpenAWSEM with Open3SPN2: A fast, flexible, and accessible framework for large-scale coarse-grained biomolecular simulations
We present OpenAWSEM and Open3SPN2, new cross-compatible implementations of coarse-grained models for protein (AWSEM) and DNA (3SPN2) molecular dynamics simulations within the OpenMM framework. These new implementations retain the chemical accuracy and intrinsic efficiency of the original models while adding GPU acceleration and the ease of forcefield modification provided by OpenMM’s Custom Forces software framework. By utilizing GPUs, we achieve around a 30-fold speedup in protein and protein-DNA simulations over the existing LAMMPS-based implementations running on a single CPU core. We showcase the benefits of OpenMM’s Custom Forces framework by devising and implementing two new potentials that allow us to address important aspects of protein folding and structure prediction and by testing the ability of the combined OpenAWSEM and Open3SPN2 to model protein-DNA binding. The first potential is used to describe the changes in effective interactions that occur as a protein becomes partially buried in a membrane. We also introduced an interaction to describe proteins with multiple disulfide bonds. Using simple pairwise disulfide bonding terms results in unphysical clustering of cysteine residues, posing a problem when simulating the folding of proteins with many cysteines. We now can computationally reproduce Anfinsen’s early Nobel prize winning experiments by using OpenMM’s Custom Forces framework to introduce a multi-body disulfide bonding term that prevents unphysical clustering. Our protein-DNA simulations show that the binding landscape is funneled towards structures that are quite similar to those found using experiments. In summary, this paper provides a simulation tool for the molecular biophysics community that is both easy to use and sufficiently efficient to simulate large proteins and large protein-DNA systems that are central to many cellular processes. These codes should facilitate the interplay between molecular simulations and cellular studies, which have been hampered by the large mismatch between the time and length scales accessible to molecular simulations and those relevant to cell biology.
Tailoring Cu-Zr gradient nanoglass structures: Influence of nanoparticle size and cooling rates on glass-glass interfaces
The study of gradient nanoglasses (GNGs) has gained attention due to their unique mechanical properties and potential applications in advanced materials. This study employs molecular dynamics simulations to synthesize a GNG using Cu-Zr metallic glass nanoparticles (NPs) sized from 3 to 15 nm. The NPs were produced by melting and quenching metallic clusters at a relatively slow quench rate of 10 9 K/s. The synthesis of GNG is elucidated along with the characterization of its heterogeneous metallic glass nanostructure. A seamless GNG structure is formed through cold compression of Cu 64 Zr 36 amorphous NPs of varying sizes. The influence of NP size on the GNG structure is investigated, utilizing deeply relaxed NPs, which exhibit a characteristic Cu segregation pattern on their surfaces. The results highlight an increase in structural heterogeneity due to heterogeneous mass transport and the development of local composition and density variations caused by Cu segregation at glass-glass interfaces (GGIs). A reduction in NP size is correlated with decreased Cu atomic displacements and local density at GGIs, suggesting that larger NPs may produce stronger GGIs. This research presents a novel methodology for synthesizing heterogeneous metallic glasses, demonstrating the capacity to control and customize nanostructure heterogeneity through the manipulation of NP sizes and cooling rates. Furthermore, these findings enhance our understanding of structural evolution during nanoglass synthesis and lay the foundation for further exploration in nanomaterial synthesis and characterization.
From Electronic Structure to Ion Transport: Photoelectron Spectroscopy and Molecular Dynamics Simulations Reveal the Role of Anions in Lithium Battery Electrolytes
Electrolyte anions are pivotal for lithium battery performance, yet their fundamental electronic structural properties are not well understood. In this work, we employ a combination of negative-ion photoelectron spectroscopy (NIPES), ab initio calculations, and molecular dynamics (MD) simulations to investigate the electronic structures of three representative electrolyte anions. This multiscale approach enables us to elucidate how their intrinsic electronic properties govern anion–solvent interactions in gas-phase clusters, as well as lithium-ion (Li + ) solvation structures and ion transport behavior in the condensed phase. NIPES reveals that difluoro(oxalato)borate (DFOB – ), bis(fluorosulfonyl)imide (FSI – ), and bis(oxalato)borate (BOB – ) all exhibit high electron binding energies, with vertical/adiabatic detachment energies increasing from DFOB – (6.09/5.70 eV) to FSI – (6.80/6.10 eV) to BOB – (6.82/6.40 eV), correlating with enhanced oxidation stability. Ab initio calculations reveal that DFOB – /FSI – –solvent complexes bind Li + ∼ 10 kcal/mol stronger than BOB – series, aligning with the strength of a Li + –anion model. DFOB – exhibits pronounced charge localization on both oxygen and fluorine atoms, enabling their involvement in Li + coordination. In contrast, fluorine atoms in FSI – are largely electron-depleted and remain excluded from direct Li + binding. MD simulations further demonstrate that LiDFOB and LiFSI systems exhibit Li + diffusion coefficients three and five times higher than those of LiBOB across four common solvents. Notably, LiFSI salt in acetonitrile (AN) exhibits the fastest Li + diffusion among 12 electrolyte systems, highlighting the synergistic effect of FSI – and AN in promoting ion mobility. In conclusion, these findings provide a molecular-level understanding of the critical roles of anion and its microsolvation in optimizing Li + diffusion dynamics, once again emphasizing the positioning of FSI – and DFOB – as prime candidates for next-generation electrolytes.
Revealing the structure and electronic characteristics of Te-rich threshold switching materials for high-density integration
Ovonic threshold switching (OTS) selectors play an important role in the integration of advanced three-dimensional memory. Selectors based on tellurium (Te)-containing materials exhibit significant promise due to their low threshold voltages and superior consistency. Here we have theoretically studied the structure and electronic properties of a typical OTS material, amorphous GeTe 6 , to explore the switching mechanisms using ab initio molecular dynamics simulations. The results indicate that Ge atoms tend to bond with Te atoms, forming stable chemical bonds. The Te-centered clusters are predominantly in the form of distorted octahedrons, while the Ge-centered clusters are in the form of both octahedrons and tetrahedrons. Notably, the proportion of tetrahedrons within the 4-coordinated Ge-centered clusters reaches an impressive 66.9%. These tetrahedrons are randomly dispersed throughout the simulated cell, leading to a stable amorphous configuration. The mid-gap state observed in the mobility bandgap originates from the atomic chain composed of both over-coordinated Ge and Te atoms. It is the inherent stability of the chemical environment within amorphous GeTe 6 that enables it to maintain its amorphous phase under a repeated threshold voltage, a characteristic that distinguishes it from non-OTS materials, such as amorphous tellurium. Furthermore, our findings provide an in-depth understanding of the structure and electronic characteristics of amorphous GeTe 6 , which can promote the design and application of the Te-rich threshold switching materials.
Associative polymers with controlled sticker placement: How reversible bond distribution and density govern polymer dynamics
Associative polymers with precisely arranged stickers offer opportunities to program material properties with molecular precision. Yet, it remains unclear how the placement and fraction of stickers dictate structure, dynamics, and macroscopic properties. By developing a model unentangled polymer system with hydrogen-bonding stickers, we show that randomly distributed stickers neither form clusters nor change flow properties, whereas stickers placed at chain ends drive nanocluster formation even at low concentrations. Adding more end stickers produces a rubbery plateau spanning eight decades in frequency with two distinct relaxation timescales, in contrast to the single plateau predicted by the classic sticky Rouse model. These results demonstrate that sticker distribution dictates whether associative polymers undergo nanocluster formation or microphase separation, while substantial alterations in dynamics and viscoelasticity require both sticker aggregation and thermomechanical stability of associated domains. Our findings resolve a longstanding debate on associative polymer dynamics and provide molecular design rules for programmable soft materials.
Using spin alignment of inelastically excited nuclei in fast beams to assign spins: The spectroscopy of 13 O as a test case
Excited states in O 13 were investigated using inelastic scattering of an E / A = 69.5 MeV O 13 beam off of a Be 9 target. The excited states were identified in the invariant-mass spectra of the decay products. Both single-proton and sequential two-proton decays of the excited states were examined. Furthermore, for a number of the excited states, the protons were emitted with strong anisotropy where emissions transverse to the beam axis are favored. The measured proton-decay angular distributions were compared to predictions from distorted-wave Born-approximation calculations of the spin alignment which was shown to be largely independent of the excitation mechanism. The deduced O 13 level scheme is compared to ab initio no-core shell model with continuum predictions. The lowest-energy excited states decay isotropically consistent with predictions of strong proton 1 s 1 / 2 structure. Above these states in the level scheme, we observed a number of higher-spin states not predicted within the model. Possibly these are associated with rotational bands built on deformed cluster configurations predicted by antisymmetrized molecular dynamics calculations. The spin alignment mechanism is shown to be useful for making spin assignments and may have widespread use.
A molecular model for ice nucleation and growth, attachment 2
The central field empirical pair potential model is applied to studying the effects of kinks, ledges, and vacancies on the absorption of water molecules from the vapor. Molecular dynamics simulations indicate that cluster and/or surface modes play a primary role in the absorption process, the flexibility of the hydrogen bond serves to decrease the energy required for structural interconversion, and the rapid distribution of added energy in a hydrogen bonded system lead to aggregate stability which greatly exceeds that predicted by static energy calculations.
The interaction of T-Tauri stars with molecular clouds
Winds from T-Tauri stars may provide an important dynamical input into cold molecular clouds. If the frequency of T-Tauri stars exceeds 20/cu pc, wind-driven shells collide and form ram-pressure-confined clumps. The supersonic clump motions can account for cloud line widths. Clumps collide inelastically, coalescing and eventually becoming Jeans unstable. For characteristic dark cloud temperatures low-mass stars form, and it is speculated that in this manner clouds can be self-sustaining for 10 million to 100 million yr. Only when either the gas supply is exhausted or an external trigger stimulates massive star formation (for example, by heating the cloud or enhancing the clump collision rate), will the cloud eventually be disrupted. A natural consequence of this model is that dark cloud lifetimes are identified with the duration of low-mass star formation, inferred to exceed 10 million yr from studies of nearby star clusters. Other implications include the prediction of the existence of embedded low-mass stars in turbulent cloud cores, the presence of an internal source of radiation in dark clouds, and a clumpy structure for cold molecular clouds.
Structural adaptation of oxygen tolerance in 4-hydroxybutyrl-CoA dehydratase, a key enzyme of archaeal carbon fixation
Abstract Autotrophic microorganisms that convert inorganic carbon into organic matter were key players in the evolution of life on Earth. As the early atmosphere became oxygenated, microorganisms needed to develop mechanisms for oxygen protection, especially those relying on enzymes containing oxygen-sensitive metal clusters (e.g., Fe-S). Here we investigated how 4-hydroxybutyryl-CoA dehydratase (4HBD) - the key enzyme of the 3-hydroxypropionate/4-hydroxybutyrate (HP/HB) cycle for CO 2 -fixation - adapted as conditions shifted from anoxic to oxic. 4HBD is found in both anaerobic bacteria and aerobic ammonia-oxidizing archaea (AOA). The oxygen-sensitive bacterial 4HBD and oxygen-tolerant archaeal 4HBD share 59 % amino acid identity. To examine the structural basis of oxygen tolerance in archaeal 4HBD, we determined the atomic resolution structure of the enzyme. Two tunnels providing access to the canonical [4Fe-4S] cluster in oxygen-sensitive bacterial 4HBD were closed with four conserved mutations found in all aerobic AOA and other archaea. Further biochemical experiments and molecular dynamics simulations support our findings that restricting access to the active site is the key to oxygen tolerance, explaining how active site evolution drove a major evolutionary transition. Significance statement Autotrophy (primary production) was the first life strategy on Earth. Before photosynthesis (using solar energy to fix carbon dioxide), life relied on chemical reactions for energy. These chemosynthetic reactions are present in all domains of life, including archaea possessing the most energy-efficient carbon fixation pathway - the 3-hydroxypropionate/4-hydroxybutyrate cycle. This efficiency results from enzyme modifications, including enhanced enzyme stability and catalysis of multiple reactions. We reveal the first structure of aerobic 4-hydroxybutyryl-CoA dehydratase (4HBD) from ammonia-oxidizing archaea. These archaea are among the most abundant organisms on the planet, and their 4HBD active site evolved oxygen tolerance to support aerobic metabolism. This modification can provide further insight into enzyme evolution on early earth, as photosynthesis developed and began oxygenating the atmosphere.
Speciation and Reactivity Control of Cu-Oxo Clusters via Extraframework Al in Mordenite for Methane Oxidation
The stoichiometric conversion of methane to methanol by Cu-exchanged zeolites can be brought to highest yields by the presence of extraframework Al and high CH 4 chemical potentials. Here, combining theory and experiments, the differences in chemical reactivity of monometallic Cu-oxo and bimetallic Cu-Al-oxo nanoclusters stabilized in zeolite mordenite (MOR) are investigated. Cu-L 3 edge X-ray absorption near-edge structure (XANES), infrared (IR), and ultraviolet–visible (UV–vis) spectroscopies, in combination with CH 4 oxidation activity tests, support the presence of two types of active clusters in MOR and allow quantification of the relative proportions of each type in dependence of the Cu concentration. Ab initio molecular dynamics (MD) calculations and thermodynamic analyses indicate that the superior performance of materials enriched in Cu-Al-oxo clusters is related to the activity of two μ-oxo bridges in the cluster. Replacing H 2 O with ethanol in the product extraction step led to the formation of ethyl methyl ether, expanding this way the applicability of these materials for the activation and functionalization of CH 4 . We show that competition between different ion-exchanged metal-oxo structures during the synthesis of Cu-exchanged zeolites determines the formation of active species, and this provides guidelines for the synthesis of highly active materials for CH 4 activation and functionalization.
From bulk to surface: Structure and dynamics of amorphous alumina from deep potential molecular dynamics
Understanding the atomic-scale structure and dynamics of amorphous oxide surfaces is essential for interpreting their chemical reactivity, mechanical stability, and interfacial behavior, yet direct experimental characterization remains challenging. We employ Deep Potential (DP) molecular dynamics to generate large-scale, ab initio -quality models of amorphous Al 2 O 3 bulk glasses and melt-quenched free surfaces, enabling a quantitative analysis of both structure and relaxation dynamics with statistical confidence inaccessible to direct ab initio simulation. The trained DP model reproduces experimental liquid and glass structure, captures the cooling-rate dependence of the bulk glass transition, and corrects systematic biases in the polyhedral populations predicted by widely used classical force fields. At the free surface, mass density recovers to bulk values over ~10 Å, while local coordination requires a slightly wider subsurface region to fully converge. The outermost layer is oxygen-enriched, exhibits altered polyhedral connectivity with contracted Al–O bonds, and hosts a broad population of under-coordinated motifs (notably AlO 3 and OAl 2 ) whose abundances are governed by glass stability. These under-coordinated surface motifs exhibit distinct vibrational signatures and occur as locally paired Lewis acid and Brønsted base sites consistent with bond-valence compensation, yet remain spatially dispersed rather than aggregating into extended clusters. Despite this pronounced structural heterogeneity, surface relaxation and the glass-transition temperature remain comparable to their bulk counterparts, suggesting that the disordered surface is kinetically stable once formed. Together, these results establish a molecular-level picture of amorphous alumina surfaces and demonstrate the capability of machine-learned potentials to resolve structure–property relationships in disordered oxide interfaces.
Equivariant Neural Networks Utilizing Molecular Clusters for Accurate Molecular Crystal Lattice Energy Predictions
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NWChem: Past, present, and future
Specialized computational chemistry packages have permanently reshaped the landscape of chemical sciences by providing tools to support and guide the experimental effort and for prediction of chemical and materials properties. In this regard, a special role has been played by electronic structure packages where complex chemical and materials processes can be modeled using first-principle-driven methodologies. Over the last few decades, the rapid development of computing technologies and a tremendous increase in computational power has offered a unique chance to study complex chemical transformations using sophisticated and predictive many-body techniques to describe correlated behavior of electrons in molecular and condensed phase systems at different levels of theory. In enabling these simulations, a critical role has been played by novel parallel algorithms capable of taking advantage of computational resources to address polynomial scaling of electronic structure methods. NWChem was among the first electronic structure codes that focused on delivering scalable performance for electronic structure simulations. Herein, we briefly review the NWChem suite of computational codes including its history, design principles, parallel tools, current capabilities, outreach and outlook.
Physics-informed graph neural networks for predicting cetane number with systematic data quality analysis
Designing alternative fuels for advanced compression ignition engines necessitates a predictive model for cetane number (CN). In this study, the physics-informed graph neural networks are introduced for a reliable CN prediction by considering molecular features pertinent to the physical properties of molecules that affect CN. The reliability of measured data is another key factor to consider for improving the predictive model. Various experimental instruments for measuring CN exist, including standard and non-standard methods. In this regard, a systematic data quality analysis was carried out for the total 630 CNs collected from literature and new measurements in this study using Advanced Fuel Ignition Delay Analyzer (AFIDA). The results from this data curation process were reflected in the model by imposing lower sample weights on the data coming from less reliable measurement techniques. This approach effectively maximized the prediction accuracy while incorporating data from all available sources. Using the sample weights decreased the mean absolute error (MAE) up to 0.8 CN units. The accuracy was also improved by introducing the CN-related physical properties (the number of hydrogen bond donors and acceptors); the test set MAE is 5.74 and 7.01 for the model with and without such properties, respectively. Investigating molecular structural effects on CN was also carried out to gain chemical insights into factors used to design new fuel candidates. The dimensionality reduction analysis of feature vectors showed a clear clustering in terms of functional groups and CN and the structural effect derived from the model was consistent with the physicochemical insights. Finally, this physics-informed model and data curation would be helpful for accurate CN prediction and inform rational fuel design.
Tea ( Camellia sinensis ) Extract-Mediated Green Synthesis of Co 3 O 4 and Co 3 O 4 @Graphene Nanocomposites for Multifunctional Applications in Pollutant Degradation, Sensing, and Energy Storage
A novel solution-mixing method was proposed to synthesize Co 3 O 4 /graphene nanocomposites (Co 3 O 4 @Gr) using a green tea leaf (Camellia sinensis) extract as the reducing agent. XRD analysis shows that the as-prepared Co 3 O 4 @Gr exhibits a cubic spinel crystal structure. From morphological analysis, the obtained Co 3 O 4 NS forms spherical clusters that are uniformly distributed on the graphene surface. FT-IR and Raman analyses confirmed the strong molecular and vibrational interactions between the Co 3 O 4 NS and Gr. The suppressed PL intensity peak of the Co 3 O 4 @Gr NCs indicated significant inhibition in the recombination of charge carriers between the hybrid orbitals within the composites. As a result, the catalytic efficiency of Co 3 O 4 @Gr NCs increased to 80% compared to pristine Co 3 O 4 , which exhibited only 45% efficiency against methylene blue (MB) dye. Moreover, the as-prepared NCs exhibited a detection limit of 0.01−224 μM, demonstrating a superior low-DPA detection with high sensitivity. The Co 3 O 4 @Gr/GCE exhibits admirable selectivity for various pesticides, fungicides, and metal ions, with outstanding reproducibility and stability. From electrochemical investigations, the highest specific capacitance values of the as-synthesized Co 3 O 4 @Gr were 349 F/g at a scan rate of 5 mV/s and 158 F/g at a current density of 1 A/g.