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More rational approach offers potential for optimization of design. Improvement in deterministic method of selection of structural-load safety factors makes possible to design structures more nearly optimum with respect to competing demands for both reliability and attributes detracting from reliability (principally lighter weight, smaller size, and lower cost).
Abstract Salt water is ubiquitous, playing crucial roles in geological and physiological processes. Despite centuries of investigations, whether or not water’s structure is drastically changed by dissolved ions is still debated. Based on density functional theory, we employ machine learning based molecular dynamics to model sodium chloride, potassium chloride, and sodium bromide solutions at different concentrations. The resulting reciprocal-space structure factors agree quantitatively with neutron diffraction data. Here we provide clear evidence that the ions in salt water do not distort the structure of water in the same way as neat water responds to elevated pressure. Rather, the computed structural changes are restricted to the ionic first solvation shells intruding into the hydrogen bond network, beyond which the oxygen radial-distribution function does not undergo major change relative to neat water. Our findings suggest that the widely cited pressure-like effect on the solvent in Hofmeister series ionic solutions should be carefully revisited.
Abstract Rare-earth titanates form very fragile liquids that can be made into glasses with useful optical properties. We investigate the atomic structure of 83TiO 2 -17Nd 2 O 3 glass using pair distribution function (PDF) analysis of X-ray and neutron diffraction with double isotope substitutions for both Ti and Nd. Six total structure factors are analyzed (5 neutron + 1 X-ray) to obtain complementary sensitivities to O and Ti/Nd scattering, and an empirical potential structure refinement (EPSR) provides a structural model consistent with the experimental measurements. Glass density is estimated as 4.72(13) g cm −3 , consistent with direct measurements. The EPSR model indicates nearest neighbor interactions for Ti-O at $$\overline{r}_{TiO}$$ r ¯ TiO = 1.984(11) Å with coordination of $$n_{TiO}$$ n TiO = 5.72(6) and for Nd-O at $$\overline{r}_{NdO}$$ r ¯ NdO = 2.598(22) Å with coordination of $$n_{NdO}$$ n NdO = 7.70(26), in reasonable agreement with neutron first order difference functions for Ti and Nd. The titanate glass network comprises a mixture of distorted Ti-O 5 and Ti-O 6 polyhedra connected via 71% corner-sharing and 23% edge-sharing. The O-Ti coordination environments include 15% nonbridging O-Ti 1 , 51% bridging O-Ti 2 , and 32% tricluster O-Ti 3 . This structure is highly unusual for oxide glasses melt-quenched at ambient pressure, as it consists of Ti-O x predominantly in octahedral (with nearly no tetrahedral) coordination.
We used the coherent grazing incidence small angle x-ray scattering technique to study the average kinetics and nanoscale dynamics during early-stage a-WSi 2 sputter deposition. The kinetic and dynamic properties are examined as a function of pressure, which is known to be a critical factor in determining final surface roughness. Surface growth kinetics and dynamics are characterized by time parameters extracted from the height-height structure factor and correlation functions. The roughness at a given length scale reaches a maximum before relaxing down to a steady state. The lateral length scale dependence and pressure dependence are then compared among the measured kinetics and dynamics time parameters. Surfaces grown at lower pressures are smoother, leading to longer correlation times. The time parameters to reach a dynamic steady state and a kinetic steady state show contrasting pressure dependence. A dynamic steady state is reached earlier than the kinetic steady state at high pressure. A more random deposition direction and lower kinetic energy at higher pressures can explain these phenomena, along with the hypothesis that larger nanoclusters form in vapor before arriving at the surface. Here, a continuum model is applied to simulate the overall behavior with mixed success.
Tuning broad emission in 2D Pb–Sn halide perovskites (HPs) is essential for advancing optoelectronic applications, particularly for color-tunable and white-light-emitting devices. This broad emission is linked to structural factors, such as defects and phase segregation of the Pb component within the Pb–Sn system, which are strongly influenced by the molecular structure and chemical properties of spacer cations. Atomic tuning of the spacers via halogenation opens up a new way to fine-tune the molecular properties, enabling further augmentations of HP functionalities. Nevertheless, the distinct broad emission's sensitivity to spacer chemistry remains underexplored. Here, halogenation's influence is systematically investigated on 2D HP emission characteristics using a high-throughput workflow. These findings reveal that the F-containing phenethylammonium (4F-PEA) spacer narrows the broadband PL, whereas Cl broadens it. Through a correlative study, it is found that 4F-PEA reduces not only the local phase segregation but also the defect levels and microstrains in 2D HPs. This is likely attributed to the manifestation of less lattice distortion via stronger surface coordination of the dipole-augmented 4F-PEA. Furthermore, these results highlight halogenation as a key factor in modulating phase segregation and defect density in 2D Pb–Sn HPs, offering a promising pathway to tune the emission for enhanced optoelectronic performance.
Amorphous TiO 2 (a-TiO 2 ) is widely used in many fields, ranging from photo-electrochemistry to bio-engineering, hence detailed knowledge of its atomic structure is of scientific and technological interest. Here we use an ab initio-based deep neural network potential (DP) to simulate large scale atomic models of crystalline and disordered TiO 2 with molecular dynamics. Our DP reproduces the structural properties of all (11) TiO 2 crystalline phases, predicts the densities and structure factors of molten and amorphous TiO 2 with only a few percent deviation from experiments, and describes the pressure dependence of the amorphous structure in agreement with recent observations. Furthermore, it can be extended to model additional structures and compositions and can be thus of great value in the study of TiO 2 -based (nano-)materials.
Many fundamental biological processes, including those in photosynthetic reaction centers and enzyme active sites, involve charge and energy transfer, bond cleavage, protonation and hydrogen bonding. Because H atoms play such central roles in these reactions, accurately determining their positions is essential. Yet, conventional X-ray crystallography primarily resolves the heavy atoms in biological structures and provides limited insight into hydrogen, even at atomic resolution. Neutron macromolecular crystallography (NMC) overcomes this limitation by offering exceptional sensitivity to hydrogen and deuterium. Here, we present a theoretical framework for the development of dynamic nuclear polarization NMC (DNP-NMC) techniques, which exploit the alignment of neutron and proton nuclear spins to enhance and tune the hydrogen signal contribution. The DNP-NMC approach advances the resolution of H atoms within biomolecular crystals, whether bound to protein residues or present in solvent. The method establishes key relationships for the coherent structure factor of polarized neutron scattering from hydrogenous matter. It theoretically achieves full accuracy in phase reconstruction and offers a path to improve neutron structure determination, achieving accuracies exceeding ≳80% by incorporating titration states. Using a variant of the hybrid input/output phase-retrieval algorithm, it allows recovery of the hydrogen density with ≳90% phase accuracy. In conclusion, we further discuss sources of experimental uncertainty for the upcoming DNP-enabled, quasi-Laue IMAGINE-X experiment at Oak Ridge National Laboratory's High Flux Isotope Reactor.
The acquisition of skill in the performance of a three-phase code transformation task (3P-COTRAN) was studied with 20 subjects who solved 27 3P-COTRAN problems during each of 8 successive sessions. The purpose of the study was to determine the changes in the 3P-COTRAN factor structure resulting from practice, the distribution of practice-related gains in performance over the nine measures of the five 3P-COTRAN factors, and the effects of transformation complexities on the 3P-COTRAN performance of subjects. A significant performance gain due to practice was observed, with improvements in speed continuing even when accuracy reached asymptotic levels. Transformation complexity showed no effect on early performances but the 3- and 4-element transformations were solved quicker than the 5-element transformation in the problem-solving Phase III of later skilled performances.
Zn Cl 2 solutions are promising electrolytes for aqueous zinc-ion batteries. Here, we report a joint computational and experimental study of the structural and dynamic properties of aqueous Zn Cl 2 electrolytes with concentrations ranging from salt-in-water to water-in-salt (WIS). By developing a neural network potential (NNP) model, we perform molecular dynamics (MD) simulations with accuracy but at much larger lengths and longer timescales. The NNP predicted structures are validated by the structure factors measured by X-ray total scattering experiments. The MD trajectories provide a comprehensive and quantitative picture of the Zn 2 + solvation shell structures. Additionally, we find that the O − H covalent bonds in water are strengthened with increasing salt concentration, thus expanding the electrochemical stability window of aqueous electrolytes. In terms of dynamic properties, the calculated and experimentally measured conductivities are in good agreement. Through the analysis of the calculated cation transference number, we propose a three-stage charge carrier transport mechanism with increasing concentration: independent ion transport, strongly correlated ion transport, and small positive charge carrier diffusion through negatively charged polymeric clusters. Our study provides fundamental atomic scale insights into the structure and transport properties of the Zn Cl 2 electrolyte that can aid the optimization and development of WIS electrolytes. Published by the American Physical Society 2025
In periodically sheared suspensions there is a dynamical phase transition, characterized by a critical strain amplitude $γ_c$, between an absorbing state where particle trajectories are reversible and an active state where trajectories are chaotic and diffusive. Repulsive nonhydrodynamic interactions between “colliding” particles’ surfaces have been proposed as a source of this broken time reversal symmetry. A simple toy model called random organization qualitatively reproduces the dynamical features of this transition. Random organization and other absorbing state models exhibit hyperuniformity, a strong suppression of density fluctuations on long length scales quantified by a structure factor $S(q → 0) ~q^α$ with $\textit{α}$ > 0, at criticality. In this work, we show experimentally that the particles in periodically sheared suspensions organize into structures with anisotropic short-range order but isotropic, long-range hyperuniform order when oscillatory shear amplitudes approach $γ_c$.
A molecular-level understanding of electrolyte solvation structure and ion–ion correlations is critical to developing next-generation battery chemistries. Atomistic simulation capabilities with sufficient accuracy, speed, and transferability to deliver reliable structural insights while avoiding arduous system-specific reparameterization are thus highly desirable. Machine learning interatomic potentials (MLIPs) trained on large, chemically diverse data sets are revolutionizing computational chemistry, enabling molecular dynamics simulations of battery electrolytes with near-DFT accuracy over 10,000× faster than DFT. While previous MLIP training data sets with suitable elemental coverage for electrolytes have been based on inorganic materials, the Open Molecules 2025 (OMol25) data set provides large-scale molecular DFT MLIP training data with broad elemental coverage and specifically samples tens of millions of electrolyte configurations. Here, we integrate computational modeling with experimental validation to systematically assess the ability of large-scale MLIPs pretrained on materials data or on OMol25 to accurately resolve nanoscale structural organization and ion-solvation characteristics in Na-ion battery electrolytes across diverse physicochemical conditions and compositional regimes. We find that the OMol25-trained Universal Model of Atoms (UMA-OMol) predicts experimentally measured densities and X-ray structure factors in substantially better agreement compared to state-of-the-art models trained only on inorganic materials data. Using UMA-OMol, we further analyze systematic trends in solvation structure as a function of cation identity, anion chemistry, salt concentration, and solvent topology. We observe that increasing system temperature amplifies the heterogeneity within the solvation environment, perturbing cation–solvent interactions and promoting the formation of contact ion pairs (CIPs). Moreover, subtle variations in the solvent topology of glyme-based electrolytes cause pronounced changes in ion correlations and solvation structure. The experimental agreement and microscopic insights shown here position OMol25-trained MLIPs as a practical route to predictive, high-throughput electrolyte simulations beyond the limits of classical force fields and direct DFT molecular dynamics, serving as a powerful tool for accelerating the design of next-generation Na-ion battery electrolytes and beyond.
BACKGROUND The Human Factors and Behavioral Performance Exploration Measures (HFBP-EM) suite is a set of standardized measures used to assess behavioral health and performance risks related to future exploration-class space missions. During the HFBP-EM suite development, the importance of assessing unique contextual factors to understand the drivers of team dynamics was identified. Group living skills are a unique workplace skill which applies to those coworkers who live and work together. As mission lengths become longer, the line between work and non-work life may blur. Extreme living conditions such as spaceflight can result in increased stress over time, negatively impact mood and well-being, decrease team cohesion and increase conflict, deteriorate task performance, and potentially reduce mission success [1]. With no breaks in their isolated and confined environment possible, living with a messy, inconsiderate crewmember can add to the stress. Alternatively, crews with good group living skills may support one another, mitigating the negative effects of the extreme environment. There was no direct measure of group living skills. This work sought to fill this measurement gap and collect data related to group living in isolated, confined, extreme (ICE) environments. METHODS Group living skills as an astronaut competency area were developed with the input of experts familiar with ICE environments. Distinct aspects of this competency were reviewed and discussed by a NASA-invited group of spaceflight experts in 2015 to identify individual and team behavioral health and performance measures for operational environments. This work resulted in a 5-item measure focused on group living experiences with each crewmember (or the crew as a whole). A 6th item asks whether an individual would go on another mission with a particular crewmember or crew as a measure of future-oriented group living, or team viability. The measure was deployed in 24 teams living and working together in isolated and confined environments (e.g., International Space Station, space mission simulation analogs). RESULTS & DISCUSSION In this presentation, we will summarize results which indicate the Group Living Skills (GLS) Survey is a reliable, valid, and operationally feasible measure. Reliability was evaluated in several ways. Two-way multilevel mixed models revealed strong repeated measures reliability (ICC2 = .902, Omega between = .954). Reliability of change within teams was strong (Rc = .81). Factor analysis showed a consistent two-factor structure when individuals rated either the whole crew, all individuals, just peers, or a focal roommate. The latter used a sociometric approach to rating the GLS of the roommates. The two factors were tidiness and being considerate of others. We assessed the criterion-related validity of GLS, by examining GLS operationalized as the team-level aggregated GLS Survey scores as a predictor of team viability, team cohesion, and team performance. We used generalized mixed models to account for the repeated measures and longitudinal data. The marginal R2 change was used to determine the extent to which GLS were related to the team outcomes while controlling for mission day and campaign. Results suggested GLS was strongly related to team viability (marginal R2 change = .40), team cohesion (marginal R2 change = 0.28), social cohesion (marginal R2 change = 0.25), and moderately related to task cohesion (marginal R2 change = 0.18). GLS scores had a small relationship with team performance (marginal R2 change = .08). Results support GLS as a measure that can be used to capture group living skills of crews who live and work together in ICE. Because the items were written to be broadly applicable, less extreme environments with teams living and working together for some length of time also benefit from this measure (e.g., college roommates, camps). See Landon et al. (2024) for full results [2]. SUMMARY We report reliability and validity evidence for a new measure that assesses the Group Living Skills for teams that live and work in operational environments such as spaceflight.
Cerium-based metallic glasses are prototype polyamorphous systems with pressure-induced polyamorphic transitions extensively reported. Cooling typically has a similar effect on materials as compression with regard to reducing volume. However, previous studies show dramatically different behavior of Ce-based metallic glasses between cooling and compression, whose origin remains unclear. Here, using in situ low-temperature synchrotron high-energy x-ray diffraction, the structural evolution of a Ce68Al10Cu20Co2 metallic glass is accurately determined and analyzed by a structure factor and a reduced pair distribution function (PDF) during cooling from 298 to 83 K. An unusually large linear thermal expansion coefficient is revealed, which is associated with both continuous but inconsistent structural changes between the two subpeaks of the first atomic shell in terms of average bond lengths and coordination numbers. These phenomena are suggested to be attributed to a gradual 4f electron delocalization of only a minimal amount (∼2.6% at 83 K) of Ce atoms by quantitative analysis of the PDF data. However, a previously expected global polymorphic transition from a low-density amorphous state to a high-density amorphous state with an abrupt volume collapse is not observed. Moreover, electrical resistivity also shows a continuous increase during cooling without any sharp change. It is clarified that cryogenic temperatures could facilitate but are not powerful enough alone to trigger a global polymorphic transition in the Ce68Al10Cu20Co2 metallic glass, suggesting a wide distribution of its local atomic environment.
Palladium-silver based alloy catalysts have a great potential for CO-free hydrogen production from formic acid for fuel cell applications. However, the structural factors affecting the selectivity of formic acid decomposition is still debated. Herein, the decomposition pathways of formic acid on Pd-Ag alloys with different atomic configurations have been investigated to identify the alloy structures yielding high H 2 selectively. Several Pd x Ag 1-x surface alloys with various compositions were generated on a Pd(111) single crystal; their atomic distribution and electronic structure were determined by a combination of infrared reflection absorption spectroscopy (IRAS), X-ray photoelectron spectroscopy (XPS), and density functional theory (DFT). It was established that the Ag atoms with Pd neighbors are electronically altered, and the degree of alteration correlates with the number of nearest Pd. Temperature programmed reaction spectroscopy (TPRS) and DFT demonstrated that the electronically altered Ag domains create a new reaction pathway that selectively dehydrogenates formic acid. In contrast, Pd monomers surrounded by Ag are demonstrated to have a similar reactivity compared to pristine Pd(111), yielding CO and H 2 O in addition to the dehydrogenation products. Furthermore, they bind to the produced CO weaker than pristine Pd, demonstrating an enhancement in resistance to CO poisoning. This work therefore shows that surface Ag domains modified by interaction with subsurface Pd are the key active sites for selective decomposition of formic acid, while surface Pd atoms are detrimental for selectivity. Hence the decomposition pathways can be tailored for CO-free H 2 production on Pd-Ag alloy systems.
Using small-angle neutron scattering, we studied the nanostructure of a prototypical D(H)-bonded network electrolyte, alkaline sodium aluminate bisalt, at concentrations up to solute volume fraction of ~0.5. Analysis of the structure factor prepeak at 0.1 < Q < 1.0 Å-1 showed that its evolution is associated with nanoscopic species distribution in water-anion network., with differences in characteristic distance d between OD- and Al(OD)4- anions related to their distinct sizes and interactions. When the solute volume fraction approached 0.5, a common/maximum value of ~4.5 Å was found for the correlation length ? that characterizes the electrostatic force in concentrated electrolyte solution before precipitation occurred. This implies that the solutions’ morphology and behavior at high concentrations may be governed by geometric factors, rather than the chemistry of the specific anion. Furthermore, the scaling of ? with concentration yielded an exponent of 1.25(1), suggesting that ? is limited to a few Å. By combining the current observations of structural heterogeneity at the nanoscale, with dynamic heterogeneity at the microscopic scale from our previous quasi-elastic neutron scattering study, we have established a structural origin of local “caging” and restricted structural relaxation processes. These local solvent-solute interactions not only control dynamics heterogeneity in concentrated electrolytes but also are responsible for crystallization processes in industrial setting, such as aluminum production and radioactive waste treatment.
Ionic assemblies, or clusters, determine the structure and dynamics of ionizable polymers and enable their many applications. Fundamental to attaining well-defined materials is controlling the balance between van der Waals interactions that govern the backbone behavior and the forces that drive the formation of ionic clusters. Here, using small angle neutron scattering and fully atomistic molecular dynamics simulations, the structure of a model ionomer, sulfonated polystyrene in toluene solutions, was investigated as the cluster cohesion was tweaked by the addition of ethanol. The static structure factor was measured by both techniques and correlated with the size of the ionic clusters as the polymer concentration was varied. The conjunction of SANS results and molecular insight from MD simulations enabled the determination of the structure in these inhomogeneous networks on multiple length scales. Additionally, we find that across the entire concentration range studied, a network driven by the formation of ionic clusters was formed, where the size of the clusters drives the inhomogeneity of these systems. Tweaking the ionic clusters through the addition of ethanol impacts the packing of the sulfonated groups, their shape, and their size distribution, which in turn, affects the structure of these networks.
Background: Amorphous drug formulations are commonly used to improve the solubility and bioavailability of poorly soluble molecular pharmaceuticals, yet less is known about their molecular conformations and local bonding interactions than their crystalline phases. Methods: High-energy X-ray diffraction structure factor measurements have been made on liquid and glassy nifedipine (NIF), felodipine (FEL), NIF 1:3 polyvinylpyrrolidone (PVP), and FEL 1:3 PVP wt.% mixtures. The corresponding X-ray pair distribution functions have been interpreted using empirical potential structure refinement using different models and density functional theory conformer calculations. Results: In both NIF and FEL, the NH···O inter-molecular hydrogen bonds between the pyridyl nitrogen and ester carbonyls are found to be considerably weaker than those observed in the crystalline polymorphs. For nifedipine, it is proposed that either inter-molecular NH…ON nitro bonds are present and/or a fraction (<20%) of conformational changes, with the aryl ring flipped, occur in the liquid state. For felodipine, the models indicate significant disorder associated with the methyl and ethyl side chains in the liquid state, with the main peak intensity at 3.0 Å arising from intra-molecular Cl-Cl atom pairs. When nifedipine molecules are incorporated into PVP, our models show they possess stronger NH···O bonds to the PVP polymer than felodipine molecules, which have stronger affinity for bonding to the polymer than to other felodipine molecules. Conclusions: The amorphous forms of both NIF and FEL show much weaker hydrogen bonding than found in their crystalline phases. Liquid NIF also exhibits configurations which are not observed in the crystal phases.
Motion organization has 2 aspects: the extraction of a (moving) frame of reference and the hierarchical organization of moving elements within the reference frame. Using a discrimination of relative motions task, the authors found large differences between different types of motion (translation, divergence, and rotation) in the degree to which each can serve as a moving frame of reference. Translation and divergence are superior to rotation. There are, however, situations in which rotation can serve as a reference frame. This is due to the presence of a second factor, structural invariants (SIs). SIs are spatial relationships persisting among the elements within a configuration such as a collinearity among points or one point coinciding with the center of rotation for another (invariant radius). The combined effect of these 2 factors--motion type and SIs-influences perceptual motion organization.