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This article serves as the introduction to a special issue focusing on plasticity and fracture at the nanoscales - advances in in situ experimentation techniques enabling novel and extreme materials/nanocomposite design.
Here, the oxidation of boride and carbide-based ultra-high-temperature ceramics is the primary limiting factor for their use as aerodynamic surfaces. Understanding the behaviour of the oxides that can result from oxidation of metal borides and carbides at very high temperatures is essential to optimise and tailor the performance of these materials; yet experimental thermodynamic and structural data for refractory oxides above 2000°C are mostly absent. The following techniques that can be applied to fill this gap are discussed: (i) commercial ultra-high-temperature differential thermal analysis for investigation of phase transformations and melting in inert environments to 2500°C, (ii) a combination of laser heating with a splittable nozzle aerodynamic levitator for splat quenching and drop calorimetry from temperatures limited only by sample evaporation, (iii) synchrotron X-ray and neutron diffraction on laser-heated aerodynamically levitated oxide samples for in situ observation of phase transformations in variable atmospheres, refinement of high-temperature structures and thermal expansion. Recent experimental findings include anomalous thermal expansion of the defect fluorite phase of YSZ, thermodynamics of pyrochlore–fluorite transformation from high-temperature structure refinements, and measurement of thermal expansion to the melting temperatures and fusion enthalpies of Zr, Hf, La, Yb and Lu oxides. These methods provide temperatures, enthalpies and volume change for phase transformations above 2000°C, which are required for thermodynamic assessments and calculation of phase diagrams of multicomponent systems.
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While iodine speciation is important for a wide range of nuclear activities, understanding the mechanisms of the transformations of iodine between chemical forms and the sensitivity of these transitions to solution conditions and exposure to radiation remains an active area of research. This work curates spectroscopic data from several experimental techniques and establishes their sensitivity and limitations in detecting changes in iodine speciation in both neutral and acidic regimes. The techniques include Raman spectroscopy, Fourier Transform Infrared (FTIR) spectroscopy, 127 I NMR spectroscopy, and ultraviolet-visible (UV-Vis) spectroscopy. Analysis of these data indicates that these commonly accessible spectroscopies often have dynamic ranges of measurable concentrations that do not always overlap between all techniques. The experimental techniques are disparately sensitive to iodide (I - ), molecular iodine (I 2 ), iodate (IO 3 - ), and periodate (IO 4 - ) species. Raman, FTIR, and NMR spectra were subsequentially analyzed using two-dimensional correlation analyses to generate high-resolution autocorrelation spectra. Here, the use of these spectroscopies is then extended to tracking acidification-induced and gamma irradiation-induced transformations of dissolved sodium iodate in deionized water and concentrated nitric acid. Both dissolution into nitric acid and irradiation with a gamma source are demonstrated to perturb the iodine speciation promoting their assembly into molecular iodine (I 2 ) and/or triiodide (I 3 - ). While I 2 and I 3 - species are undetectable with FTIR spectroscopy and 127 I NMR spectroscopy, the species can be detected with UV-Vis spectroscopy, and in some instances, I 3 - can be detected with Raman spectroscopy in the low wavenumber region. Ultimately, the results of this work provide a path to designing optimal combinations of techniques to detect forms of iodine across a wide range of concentrations and conditions.
The implementation is proposed of image inpainting techniques for the reconstruction of gaps in experimental X-ray scattering data. The proposed methods use deep learning neural network architectures, such as convolutional autoencoders, tunable U-Nets, partial convolution neural networks and mixed-scale dense networks, to reconstruct the missing information in experimental scattering images. In particular, the recovered pixel intensities are evaluated against their corresponding ground-truth values using the mean absolute error and the correlation coefficient metrics. The results demonstrate that the proposed methods achieve better performance than traditional inpainting algorithms such as biharmonic functions. Overall, tunable U-Net and mixed-scale dense network architectures achieved the best reconstruction performance among all the tested algorithms, with correlation coefficient scores greater than 0.9980.
The intermetallic compound ZnPd has been found to have desirable characteristics as a catalyst for the steam reforming of methanol. The understanding of the surface structure of ZnPd is important to optimize its catalytic behavior. However, due to the lack of bulk single-crystal samples and the complexity of characterizing surface properties in the available polycrystalline samples using common experimental techniques, all previous surface science studies of this compound have been performed on surface alloy samples formed through thin-film deposition. In this study, we present findings on the chemical and atomic structure of the surfaces of bulk polycrystalline ZnPd studied by a variety of complementary experimental techniques, including scanning tunneling microscopy (STM), x-ray photoelectron spectroscopy (XPS), low energy electron microscopy (LEEM), photoemission electron microscopy (PEEM), and microspot low-energy electron diffraction ( μ -LEED). These experimental techniques, combined with density functional theory (DFT)-based thermodynamic calculations of surface free energy and detachment kinetics at the step edges, confirm that surfaces terminated by atomic layers composed of both Zn and Pd atoms are more stable than those terminated by only Zn or Pd layers. DFT calculations also demonstrate that the primary contribution to the tunneling current arises from Pd atoms, in agreement with the STM results. The formation of intermetallics at surfaces may contribute to the superior catalyst properties of ZnPd over Zn or Pd elemental counterparts. Published by the American Physical Society 2024
Here, we outline recent developments in artificial intelligence (AI) and machine learning (ML) techniques for integrative structural biology of intrinsically disordered proteins (IDP) ensembles. IDPs challenge the traditional protein structure-function paradigm by adapting their conformations in response to specific binding partners leading them to mediate diverse, and often complex cellular functions such as biological signaling, self-organization and compartmentalization. Obtaining mechanistic insights into their function can therefore be challenging for traditional structural determination techniques. Often, scientists have to rely on piecemeal evidence drawn from diverse experimental techniques to characterize their functional mechanisms. Multiscale simulations can help bridge critical knowledge gaps about IDP structure-function relationships - however, these techniques also face challenges in resolving emergent phenomena within IDP conformational ensembles. We posit that scalable statistical inference techniques can effectively integrate information gleaned from multiple experimental techniques as well as from simulations, thus providing access to atomistic details of these emergent phenomena.
Novel experimental techniques are required to make the next big leap in neutron electric dipole moment experimental sensitivity, both in terms of statistics and systematic error control. The nEDM experiment at the Spallation Neutron Source (nEDM@SNS) will implement the scheme of Golub & Lamoreaux [Phys. Rep., 237, 1 (1994)]. The unique properties of combining polarized ultracold neutrons, polarized 3 He, and superfluid 4He will be exploited to provide a sensitivity to ~ 10-28 e · cm. Our cryogenic apparatus will deploy two small (3 L) measurement cells with a high density of ultracold neutrons produced and spin analyzed in situ. The electric field strength, precession time, magnetic shielding, and detected UCN number will all be enhanced compared to previous room temperature Ramsey measurements. Our 3 He co-magnetometer offers unique control of systematic effects, in particular the Bloch-Siegert induced false EDM. Furthermore, there will be two distinct measurement modes: free precession and dressed spin. This will provide an important self-check of our results. Following five years of “critical component demonstration,” our collaboration transitioned to a “large scale integration” phase in 2018. An overview of our measurement techniques, experimental design, and brief updates are described in these proceedings.
Water/oxide interfaces are ubiquitous on earth and show significant influence on many chemical processes. For example, understanding water and solute adsorption as well as catalytic water splitting can help build better fuel cells and solar cells to overcome our looming energy crisis; the interaction between biomolecules and water/oxide interfaces is one hypothesis to explain the origin of life. However, knowledge in this area is still limited due to the difficulty of studying water/solid interfaces. As a result, research using increasingly sophisticated experimental techniques and computational simulations has been carried out in recent years. Although it is difficult for experimental techniques to provide detailed microscopic structural information, molecular dynamics (MD) simulations have satisfactory performance. In this report, we discuss classical and ab initio MD simulations of water/oxide interfaces. Generally, we are interested in the following questions: How do solid surfaces perturb interfacial water structure? How do interfacial water molecules and adsorbed solutes affect solid surfaces and how do interfacial environments affect solvent and solute behavior? Finally, we discuss progress in the application of neural network potential based MD simulations, which offer a promising future because this approach has already enabled ab initio level accuracy for very large systems and long trajectories.
According to the article, core–shell nanoparticles find applications in catalysts, sensors, and theranostics. The full internal 3D atomic structure, however, cannot be resolved by current imaging and diffraction techniques. We analyzed the atomic positions and stress-release mechanism in a cubic Au–Pd core–shell nanoparticle in approximately 1000 times higher resolution than current experimental techniques using large-scale molecular dynamics simulation to overcome these limitations. The core–shell nanocube of 73 nm size was modeled similarly to solution synthesis by random epitaxial deposition of a 4 nm thick shell of Pd atoms onto a Au core of 65 nm side length using reliable interatomic potentials. The internal structure reveals specific deformations and stress relaxation mechanisms that are caused by the +4.8% lattice mismatch of gold relative to palladium and differential confinement of extended particle facets, edges, and corners by one, two, or three Au–Pd interfaces, respectively. The three-dimensional lattice strain causes long-range, arc-like bending of atomic rows along the faces and edges of the particle, especially near the Au–Pd interface, a bulging deformation of the Pd shell, and stacking faults in the Pd shell at the corners of the particle. The strain pattern and mechanism of stress release were further characterized by profiles of the atomic layer spacing in the principal crystallographic directions. Accordingly, strain in the Pd shell is several times larger in the extended facets than near the edges and corners of the nanoparticle, which likely affects adsorption, optical, and electrochemical properties. The findings are consistent with available experimental data, including 3D reconstructions of the same cubic nanoparticle by coherent diffractive imaging (CDI) and may be verified by more powerful experimental techniques in the future. The stress release mechanisms are representative for cubic core–shell nanoparticles with fcc structure and can be explored for different shapes by the same methods.
This special issue is designed to honour the contributions of our colleague Neville Greaves who was among the first to apply newly-available synchrotron x-ray techniques to study the synthesis, structures and properties of advanced materials [1, 2]. His wide ranging work on ceramics, glasses and nanomaterials was celebrated in a recent issue of the J. Non-Cryst. Solids [3]. Neville's contributions to synchrotron research, highlighted here, focussed on design and construction of new beamline capabilities and sample environments to probe materials under different physical and chemical conditions, integrating various techniques to obtain complementary data on structure and bonding. The innovative nature of his work is illustrated by his studies of liquids and glasses, where he incorporated aerodynamic levitation into these experimental techniques, using both synchrotron x-ray and neutron beams to probe the structural transformations and dynamics combined with molecular dynamics simulations to study atomic scale organisation. His work has had a major impact on fundamental condensed matter physics and chemistry as well as applied materials science; and in this issue, we present contributions from colleagues using and developing new experimental techniques at current and next-generation synchrotron, neutron and free-electron laser sources and in their own laboratories, that probe the fundamental physics, chemistry and functional properties of novel materials and processes.
The reduction of rotational symmetry in a crystalline solid driven by an electronic mechanism is referred to as electronic nematicity. This phenomenon – initially thought to be rare – has by now been observed in an increasing number of systems. Here, the iron-based superconductors present an ideal material platform to study nematicity in crystalline solids. Their nematic transition is pronounced, it can be studied with a wide range of experimental techniques; it is easily tunable; and high-quality samples are widely available. As research on nematicity in iron-based materials is now in its second decade, it builds on tremendous progress in theoretical concepts and experimental techniques. Thus, a stage has been reached at which the nematic phase can be addressed with confidence in its full complexity, including momentum-, time- and material- dependence of the order parameter. Important open questions concern the mechanism by which nematicity affects superconducting pairing and normal-state properties, with a central role for the challenging issue of nematic quantum criticality.
Gaining a thorough understanding of biological systems requires building our knowledge about biological processes from the level of atoms and electrons, and up to whole organisms. Such comprehensive knowledge will allow for a predictive understanding of complex biological systems behavior. It will guide us in the design and development of novel therapeutics and vaccines to tackle existing health threats and to prepare for future pandemics, and it will provide information necessary to create new biomaterials and bio-inspired technologies through manipulation of biological macromolecules, their assemblies, single cells and even microorganisms. Reaching these goals will require a synergistic combination of multiple experimental techniques with molecular calculations and predictive simulations, and the design and development of new techniques and capabilities that bridge current knowledge and technology gaps. Neutron scattering provides unique information about the biomacromolecular structure and function and can play a major role in achieving these goals. A workshop was held to engage the scientific community in identifying pressing challenges in biochemistry, structural biology, enzymology and structure-guided drug design not solved with the current neutron scattering technologies or utilizing other structural biology techniques such as X-ray crystallography, NMR, and cryo-EM. The workshop brought together structural biology, biochemistry and computational experts, as well as early career researchers and students, creating a forum for discussing scientific advancement and collaboration. The workshop included a one-day satellite training workshop where graduate students and postdoctoral researchers were educated in the application of neutron crystallography and small-angle scattering in structural biology. Furthermore, the Instrument Scientific Advisory Board (ISAB) for the development of a macromolecular neutron diffractometer at ORNL’s Second Target Station was introduced at the workshop. The major outcome was that neutrons can provide atomic-level understanding of biomacromolecular structure, function and dynamics which is of paramount importance for addressing the identified challenges. Neutron crystallography, in particular, can resolve long-standing biochemical issues regarding enzyme function by delineating the underlying chemistry and can have a major impact on the design of small-molecule therapeutics, especially in combination with molecular computation (quantum chemistry and molecular dynamics simulations) and the emerging artificial intelligence (AI)-assisted drug design technologies. The unique properties of neutrons, including their high sensitivity to hydrogen and their non-destructive nature, make them ideal probes of biological matter. There is a palpable need in the scientific community to expand and enhance the impact of neutron sciences on biology. Neutron crystallography is the only structural biology method capable of determining positions of all hydrogen atoms in proteins, nucleic acids and their complexes at near-physiological temperatures and of unstable species at cryogenic temperatures. Moreover, neutron analysis is non-ionizing, non-destructive and does not perturb the structure or redox chemistry of active site metal centers and clusters in proteins, which can be invaluable for studying radiation-sensitive metalloprotein complexes. Further, neutron energies used in scattering applications are similar to atomic motions, permitting neutron spectroscopies to characterize the dynamics of biomacromolecules on the picosecond to microsecond timescales. The different sensitivities of neutrons to protium (H) and deuterium (D) isotopes of hydrogen allow enhanced visibility of specific parts of biological complexes through isotopic labeling. The impact of neutrons will be most powerful when neutron scattering is combined with complementary experimental techniques that use photons and electrons, and with high-performance computing. The interconnection and mutuality of the experimental and theoretical capabilities will drive discoveries in biological and health sciences to generate more complete picture of complex biological systems. The major limitation in the field of biological neutron crystallography has been signal-to-noise, demanding large samples that are difficult to produce for the majority of biomacromolecules and limiting the applicability of this technique in biological sciences. A neutron crystallography instrument at the Second Target Station will revolutionize biological science with neutrons by engaging a large scientific community of structural biologists, enabling successful neutron diffraction experiments from radically smaller biomacromolecular crystals, resolving unanswered biochemical questions, and meaningfully contributing to rational drug design. The meeting highlighted 10 grand challenges that will be addressed with this advanced capability over the next decade and beyond, and the recommendations required to help address them are given below.
The effects of indoor environmental conditions on human health, satisfaction, and performance have been the focal point of research for decades. This paper reviews and summarizes the impact of lighting environment on task performance, specifically for the built environment audience. Existing studies included a variety of performance tests on cognitive performance and perception, visual acuity and reaction, memory, reasoning, and labor productivity. Illuminance, luminance ratio and correlated color temperature were found to affect performance in different ways, reflecting the impact of experimental techniques, conditions, performance evaluation methods used and data analysis methods. These were reviewed and categorized, with discussion on limitations related to sample size, modeling approach, carryover effects and other factors affecting individual differences in performance, with recommendations for future improvement. Although no universal conclusions can be made, in general, task performance seems to improve with higher illuminances, contrast ratios in the range of 7–11:1 (while always making sure that glare will not occur in the space) and higher correlated color temperature, while spectral tuning in the red or blue wavelengths has also shown positive effects. To obtain more generic evidence, future studies should be more consistent in terms of experimental procedures and overall light conditions, and also consider the effects of vertical illuminance, daylight provision/control, and outside views on task performance. Finally, studying performance with multi-factorial designs in a human-centered optimized manner (such as deploying variable lighting scenarios optimized for various tasks) can lead to deeper understanding of lighting effects on task performance, and ultimately to improved lighting design and operation in buildings overall.
Mechanical integrity of the solid electrolyte interphase (SEI) plays an essential role in determining the life and performance of lithium-ion batteries. Fracture and continued formation of the SEI contribute to consumption of lithium, drying of electrolyte, increase in impedance, and growth of dendrites resulting in capacity fade and premature failure. Electrolyte additives such as fluoroethylene carbonate (FEC) have been known to improve performance, but the underlying reasons have been elusive. Despite its importance, reliable methods for mechanical characterization of SEI have been lacking. In this paper, we present a new experimental technique that combines atomic force microscopy and membrane-bulge configuration to accurately measure the stress-strain behavior of SEI, including the onset of inelastic response and evolution of fracture. We characterize the SEI formed with two ethylene carbonate-based electrolytes, without and with fluoroethylene carbonate (FEC) additive. The measurements show a striking contrast; SEI with FEC additive has 80% higher elastic modulus and a vastly higher resistance to fracture. These findings offer a mechanical-behavior based rationale to understand how SEI controls battery performance. Moreover, the experimental technique offers a robust diagnostic tool to design electrolytes that can form SEI with the desired mechanical properties for optimal battery performance.