Results for “FUNDAMENTAL INTERACTIONS” — Page 45

DOE OSTI2026

Two-tooth bosonic quantum comb for temporal-correlation sensing

We introduce a two-tooth bosonic quantum comb that captures the sequential interactions between a thermal absorber and a long-lived coherent probe. The comb provides a causal, multi-time description of coherence transport, tracking how the probe records both instantaneous fluctuations and their temporal correlations. Using a process-tensor formulation, we derive closed form expressions showing that interference between the two interaction windows generates a non-monotonic memory response that reflects a fundamental competition between the absorbers thermal population and its dynamical correlations. By sweeping the temporal separation between the interaction windows, the probe directly samples the absorbers population correlator, enabling bosonic noise spectroscopy that discriminates Markovian temperature noise from slow or spectrally structured fluctuations. The approach is readily compatible with circuit-QED platforms and offers a general method for probing fluctuating bosonic environments.

Zhu, Shaojiang [Fermilab]↗

DOE OSTI2023

More is definitely different: the zebrafish as witness: Comment on ”Structure and function in artificial, zebrafish and human neural networks” by Peng Ji et al.

We report half a century ago, in his foundation paper More is different, Anderson stated the relevance of including multiple scales of interaction, instead of trying to reduce everything to fundamental principles. By doing so, one may witness phenomena that were not expected by looking at each individual components separately. This idea finds indeed numerous realizations such as the synchronization phenomenon, where a multitude of dynamical systems suddenly start to behave coherently together, or the spreading of diseases over entire populations, to name only two examples. But if one would have to give a single example of a system where the multiplicity of interaction scales is of utmost importance, it would probably be the brain. In their review, Ji et al. give a comprehensive overview of the multiple scales of science required in the investigation of structural and functional brain networks, as well as their interplay.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

Ferromagnetic superexchange in insulating Cr 2 MoO 6 by controlling orbital hybridization

We report the magnetic and electronic structures of the newly synthesized inverse-trirutile compound Cr 2 MoO 6 . Despite the same crystal symmetry and similar bond-lengths and bond-angles to Cr 2 TeO 6 , Cr 2 MoO 6 possesses a magnetic structure of the Cr 2 MoO 6 type, different from that seen in Cr 2 TeO 6 . Ab-initio electronic structure calculations show that the sign and strength of the Cr-O-Cr exchange coupling is strongly influenced by the hybridization between Mo 4d and O 2p orbitals. This result further substantiates our recently proposed mechanism for tuning the exchange interaction between two magnetic atoms by modifying the electronic states of the non-magnetic atoms in the exchange path through orbital hybridization. This approach is fundamentally different from the conventional methods of controlling the exchange interaction by either carrier injection or through structural distortions.

36 MATERIALS SCIENCE↗

DOE OSTI2023

High-Throughput Automated Exploration of Phase Growth Behaviors in Quasi-2D Formamidinium Metal Halide Perovskites

Quasi-2D metal halide perovskites (MHPs) are an emerging material platform for sustainable functional optoelectronics, but the uncontrollable, broad phase distribution remains a critical challenge for applications. Nevertheless, the basic principles for controlling phases in quasi-2D MHPs remain poorly understood, due to the rapid crystallization kinetics during the conventional thin-film fabrication process. In this work, a high-throughput automated synthesis-characterization-analysis workflow is implemented to accelerate material exploration in formamidinium (FA)-based quasi-2D MHP compositional space, revealing the early-stage phase growth behaviors fundamentally determining the phase distributions. Upon comprehensive exploration with varying synthesis conditions including 2D:3D composition ratios, antisolvent injection rates, and temperatures in an automated synthesis-characterization platform, it is observed that the prominent n = 2 2D phase restricts the growth kinetics of 3D-like phases—α-FAPbI 3 MHPs with spacer-coordinated surface—across the MHP compositions. Thermal annealing is a critical step for proper phase growth, although it can lead to the emergence of unwanted local PbI 2 crystallites. Additionally, fundamental insights into the precursor chemistry associated with spacer-solvent interaction determining the quasi-2D MHP morphologies and microstructures are demonstrated. The high-throughput study provides comprehensive insights into the fundamental principles in quasi-2D MHP phase control, enabling new control of the functionalities in complex materials systems for sustainable device applications.

2D perovskites↗

DOE OSTI2017

Toward a systematic exploration of nano-bio interactions

Many studies of nanomaterials make non-systematic alterations of nanoparticle physicochemical properties. Given the immense size of the property space for nanomaterials, such approaches are not very useful in elucidating fundamental relationships between inherent physicochemical properties of these materials and their interactions with, and effects on, biological systems. Data driven artificial intelligence methods such as machine learning algorithms have proven highly effective in generating models with good predictivity and some degree of interpretability. They can provide a viable method of reducing or eliminating animal testing. However, careful experimental design with the modelling of the results in mind is a proven and efficient way of exploring large materials spaces. This approach, coupled with high speed automated experimental synthesis and characterization technologies now appearing, is the fastest route to developing models that regulatory bodies may find useful. We advocate greatly increased focus on systematic modification of physicochemical properties of nanoparticles combined with comprehensive biological evaluation and computational analysis. This is essential to obtain better mechanistic understanding of nano-bio interactions, and to derive quantitatively predictive and robust models for the properties of nanomaterials that have useful domains of applicability. - Highlights: • Nanomaterials studies make non-systematic alterations to nanoparticle properties. • Vast nanomaterials property spaces require systematic studies of nano-bio interactions. • Experimental design and modelling are efficient ways of exploring materials spaces. • We advocate systematic modification and computational analysis to probe nano-bio interactions.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Experimental assessment of fuel-cladding interactions

A range of fuel concepts designed to better tolerate accident scenarios and reactor transients are currently undergoing fundamental development at national laboratories as well as university and industrial partners. Pellet-clad mechanical and chemical interaction can be expected to affect fuel failure rates experienced during steady state operation, as well as dramatically impact the response of the fuel form under loss of coolant and other accident scenarios. The importance of this aspect of fuel design prompted research initiated by AFC in FY14 to begin exploratory efforts to characterize this phenomenon for candidate fuelcladding systems of immediate interest. Continued efforts in FY15 and FY17 aimed to better understand and simulate initial pellet-clad interaction with little-to-no pressure on the pellet-clad interface. Reported here are the results from 1000 h heat treatments at 400, 500, and 600°C of diffusion couples pairing UN with a FeCrAl alloy, SiC, and Zr-based cladding candidate sealed in evacuated quartz ampoules. No gross reactions were observed, though trace elemental contaminants were identified.

36 MATERIALS SCIENCE↗

DOE OSTI2021

The Search for Feebly Interacting Particles

At the dawn of a new decade, particle physics faces the challenge of explaining the mystery of dark matter, the origin of matter over antimatter in the Universe, the apparent fine-tuning of the electroweak scale, and many other aspects of fundamental physics. Perhaps the most striking frontier to emerge in the search for answers involves New Physics at mass scales comparable to that of familiar matter—below the GeV scale but with very feeble interaction strength. New theoretical ideas to address dark matter and other fundamental questions predict such feebly interacting particles (FIPs) at these scales, and existing data may even provide hints of this possibility. Emboldened by the lessons of the LHC, a vibrant experimental program to discover such physics is underway, guided by a systematic theoretical approach that is firmly grounded in the underlying principles of the Standard Model. We give an overview of these efforts, their motivations, and the decadal goals that animate the community involved in the search for FIPs, and we focus in particular on accelerator-based experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2016

Laser-material interaction during atom probe tomography of oxides with embedded metal nanoparticles

Here, oxide-supported metal nano-particles are of great interest in catalysis but also in the development of new large-spectrum-absorption materials. The design of such nano materials requires three-dimensional characterization with a high spatial resolution and elemental selectivity. The laser assisted Atom Probe Tomography (La-APT) presents both these capacities if an accurate understanding of laser-material interaction is developed. In this paper, we focus on the fundamental physics of field evaporation as a function of sample geometry, laser power, and DC electric field for Au nanoparticles embedded in MgO. By understanding the laser-material interaction through experiments and a theoretical model of heat diffusion inside the sample after the interaction with laser pulse, we point out the physical origin of the noise and determine the conditions to reduce it by more than one order of magnitude, improving the sensitivity of the La-APT for metal-dielectric composites.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Surface-Templated Assembly of Molecular Methanol on the Thin Film “29” Cu(111) Surface Oxide

Identifying and characterizing the atomic-scale interaction of methanol with oxidized Cu surfaces is of fundamental relevance to industrial reactions, such as methanol steam reforming and methanol synthesis. Here, we investigate the adsorption of methanol on the well-defined “29” Cu oxide surface, using a combination of experimental and theoretical techniques, and elucidate the atomic-scale interactions that lead to a unique spatial ordering of methanol on the oxide thin film. We determine that the methanol chain structures form first due to epitaxy with the underlying “29” oxide surface. Specifically, the geometry of the “29” oxide is such that there are spatially adjacent O δ – sites, in the form of O adatoms, and Cu δ+ species, within the Cu 2 O-like rings, which allow for methanol to simultaneously bond to the surface via an O methanol –Cu δ+ dative bond and an OH methanol –O δ – hydrogen bond. The methanol–oxide bond strength outweighs the strength of methanol–methanol hydrogen bonds on the “29” Cu oxide, unlike methanol assembly on bare coinage metal surfaces on which hydrogen bonding between adjacent molecules leads to ordered arrays. Weak, long-range interactions lead to the formation of chains of only even numbers of methanol molecules. Together, this work reveals that, unlike that on metal surfaces, the corrugation of the oxide surface drives methanol adsorption to preferred binding sites, preventing intermolecular hydrogen bonding and dictating the adsorption geometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

DFT study of Fe-Ni core-shell nanoparticles: Stability, catalytic activity, and interaction with carbon atom for single-walled carbon nanotube growth

Metal catalysts play an important role in the nucleation and growth of single-walled carbon nanotubes (SWCNTs). It is essential for probing the nucleation and growth mechanism of SWCNTs to fundamentally understand the properties of the metal catalysts and their interaction with carbon species. In this study, we systematically studied the stability of 13- and 55-atom Fe and Fe-Ni core-shell particles as well as these particles interaction with the carbon atoms using the density functional theory calculations. Icosahedral 13- and 55-atom Fe-Ni core-shell bimetallic particles have higher stability than the corresponding monometallic Fe and Ni particles. Opposite charge transfer (or distribution) in these particles leads to the Fe surface-shell displays a positive charge, while the Ni surface-shell exhibits a negative charge. The opposite charge transfer would induce different chemical activities. Compared with the monometallic Fe and Ni particles, the core-shell bimetallic particles have weaker interaction with C atoms. More importantly, C atoms only prefer staying on the surface of the bimetallic particles. In contrast, C atoms prefer locating into the subsurface of the monometallic particles, which is more likely to form stable metal carbides. The difference of the mono- and bimetallic particles on this issue may result in different nucleation and growth mechanism of SWCNTs. Our findings provide useful insights for the design of bimetallic catalysts and a better understanding nucleation and growth mechanism of SWCNTs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Effect of calcite filler on carbonation behavior in a synthesized C‐S‐H binder

Widespread implementation of portland limestone cements (PLC) in industry has raised new questions about their carbonation resistance due to higher initial limestone content than ordinary portland cement. While carbonation of portland cement and each of its hydrate phases has been studied at a fundamental level, the integral role of how limestone fillers interact chemically or physically during carbonation necessitates further study. In this study, a C-S-H binder comprised of a highly reactive zeolite pozzolan and lime was used to evaluate the effect of varying calcite additions on carbonation behavior at a microstructural level. Fundamental insight into hydration kinetics and carbonation mechanisms of hydraulic binders was obtained via analysis of the C-S-H and calcite microstructure. X-ray microcomputed tomography (X-ray CT) was used to quantify microstructural changes, and the results showed a decrease in shrinkage for increased calcite dosages, with a ∼50% reduction observed for a 45% wt. calcite replacement level. Crystallographic and thermal analyses measured compositional changes in the binder and confirmed that shrinkage was related to the decalcification of C-S-H. Furthermore, the addition of calcite to the C-S-H binder effectively reduced the liquid-to-solid ratio, porosity, and amount of C-S-H present in these binders. Ultimately, these results help elucidate how the carbonation risks of PLC can be mitigated by proportioning the mixture water only to the reactive component of the binder.

C-S-H↗

DOE OSTI2023

Pattern of global spin alignment of ϕ and K*0 mesons in heavy-ion collisions

The strong force, as one of the four fundamental forces at work in the universe, governs interactions of quarks and gluons, and binds together the atomic nucleus. Notwithstanding decades of progress since Yukawa first developed a description of the force between nucleons in terms of meson exchange 1 , a full understanding of the strong interaction remains a major challenge in modern science. One remaining difficulty arises from the non-perturbative nature of the strong force, which leads to the phenomenon of quark confinement at distance scales on the order of the size of the proton. Here we show that in relativistic heavy-ion collisions, where quarks and gluons are set free over an extended volume, two species of produced vector (spin-1) mesons, namely φ and K∗0 , emerge with a surprising pattern of global spin alignment. In particular, the global spin alignment for φ is unexpectedly large, while that for K∗0 is consistent with zero. The observed spin-alignment pattern and magnitude for the φ cannot be explained by conventional mechanisms, while a model with strong force fields2, 3 accommodates the current data. This is the first time that the strong force field is experimentally supported as a key mechanism that leads to global spin alignment. We extract a quantity proportional to the intensity of the field of the strong force. Within the framework of the Standard Model, where the strong force is typically described in the quark and gluon language of Quantum Chromodynamics, the field being considered here is an effective proxy description. This is a qualitatively new class of measurement, which opens a new avenue for studying the behaviour of strong force fields via their imprint on spin alignment.

Abdallah, M. S.↗

DOE OSTI2015

Stable large-scale solver for Ginzburg–Landau equations for superconductors

Understanding the interaction of vortices with inclusions in type-II superconductors is a major outstanding challenge both for fundamental science and energy applications. At application-relevant scales, the long-range interactions between a dense configuration of vortices and the dependence of their behavior on external parameters, such as temperature and an applied magnetic field, are all important to the net response of the superconductor. Capturing these features, in general, precludes analytical description of vortex dynamics and has also made numerical simulation prohibitively expensive. Here we report on a highly optimized iterative implicit solver for the time-dependent Ginzburg-Landau equations suitable for investigations of type-II superconductors on massively parallel architectures. Its main purpose is to study vortex dynamics in disordered or geometrically confined mesoscopic systems. In this work, we present the discretization and time integration scheme in detail for two types of boundary conditions. We describe the necessary conditions for a stable and physically accurate integration of the equations of motion. Using an inclusion pattern generator, we can simulate complex pinning landscapes and the effect of geometric confinement. We show that our algorithm, implemented on a GPU, can provide static and dynamic solutions of the Ginzburg-Landau equations for mesoscopically large systems over thousands of time steps in a matter of hours. Using our formulation, studying scientifically-relevant problems is a computationally reasonable task.

Sadovskyy, I. A.↗

DOE OSTI2017

Dynamics of water bound to crystalline cellulose

Interactions of water with cellulose are of both fundamental and technological importance. Here, we characterize the properties of water associated with cellulose using deuterium labeling, neutron scattering and molecular dynamics simulation. Quasi-elastic neutron scattering provided quantitative details about the dynamical relaxation processes that occur and was supported by structural characterization using small-angle neutron scattering and X-ray diffraction. We can unambiguously detect two populations of water associated with cellulose. The first is “non-freezing bound” water that gradually becomes mobile with increasing temperature and can be related to surface water. The second population is consistent with confined water that abruptly becomes mobile at ~260 K, and can be attributed to water that accumulates in the narrow spaces between the microfibrils. Quantitative analysis of the QENS data showed that, at 250 K, the water diffusion coefficient was 0.85 ± 0.04 × 10-10 m2sec-1 and increased to 1.77 ± 0.09 × 10-10 m2sec-1 at 265 K. MD simulations are in excellent agreement with the experiments and support the interpretation that water associated with cellulose exists in two dynamical populations. Our results provide clarity to previous work investigating the states of bound water and provide a new approach for probing water interactions with lignocellulose materials.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2014

Covering complete proteomes with X-ray structures: a current snapshot

The current and the attainable coverage by X-ray structures of proteins and their functions on the scale of the ‘protein universe’ are estimated. A detailed analysis of the coverage across nearly 2000 proteomes from all superkingdoms of life and functional annotations is performed, with particular focus on the human proteome and the family of GPCR proteins. Structural genomics programs have developed and applied structure-determination pipelines to a wide range of protein targets, facilitating the visualization of macromolecular interactions and the understanding of their molecular and biochemical functions. The fundamental question of whether three-dimensional structures of all proteins and all functional annotations can be determined using X-ray crystallography is investigated. A first-of-its-kind large-scale analysis of crystallization propensity for all proteins encoded in 1953 fully sequenced genomes was performed. It is shown that current X-ray crystallographic knowhow combined with homology modeling can provide structures for 25% of modeling families (protein clusters for which structural models can be obtained through homology modeling), with at least one structural model produced for each Gene Ontology functional annotation. The coverage varies between superkingdoms, with 19% for eukaryotes, 35% for bacteria and 49% for archaea, and with those of viruses following the coverage values of their hosts. It is shown that the crystallization propensities of proteomes from the taxonomic superkingdoms are distinct. The use of knowledge-based target selection is shown to substantially increase the ability to produce X-ray structures. It is demonstrated that the human proteome has one of the highest attainable coverage values among eukaryotes, and GPCR membrane proteins suitable for X-ray structure determination were determined.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Department of Energy’s Atmospheric System Research (ASR) Program’s Workshop on the Future of Atmospheric Large Eddy Simulation (LES): Workshop Report

Large-eddy simulation (LES) is used as a tool to understand physical processes such as turbulence, aerosols, clouds, precipitation, radiation, the interactions among all these, and their interactions with the underlying surface. Over the next 10 years, LES will drive fundamental progress in open scientific questions in these areas as LES is increasingly used to gain understanding of complex interacting physical processes involving atmospheric turbulence. This growth will be driven both by scientific demand and the expansion of computational resources needed to conduct LES, and the form that the growth takes will largely be determined by how computational resources are leveraged for scientific gain. In particular, we suggest that computational resources are likely to be leveraged in two separate but not necessarily distinct ways. On one hand, growth in computational resources will allow LES to be made more routine, that is, performed more frequently, while on the other hand, the computational expense (measured in total floating point operations) afforded to individual LES will expand dramatically, allowing simulations to increase in both domain size and resolution as well as physical detail. Current U.S. Department of Energy (DOE) projects such as LES ARM Symbiotic Simulation and Observation Activity (LASSO) are leading the way in conducting routine LES, building large, public databases that are accessible for data science, sensitivity studies, and training for machine learning. LES will also become more routine as it becomes more accessible for individual researchers to address their scientific questions of interest. Scientific questions addressed by LES over the next 10 years are likely to include cloud organization and aggregation; aerosol cloud interactions and atmospheric chemistry (including geo-engineering); urban-scale LES; atmospheric extreme events, ranging from small-scale severe weather to wildfires; and ocean-wave-atmosphere interactions. Further LES-related research will likely grow significantly in areas related to societal impact studies of air quality and extreme weather events, applications to renewable energy forecasting and resource assessment, and aid in decision-making processes. The growth in the use of LES in atmospheric science research will drive the need for better physical process representations (e.g., cloud aerosol microphysics, radiation, and atmospheric chemistry) at the scales resolved by LES. To date, many of the process representations used by LES have been taken directly from coarser-resolution models. Promising methods for LES process representations include superdroplet and quadrature methods for microphysics, 3D approaches for radiation, and better representation of chemistry and aerosol processes. At LES resolution, land-atmosphere interactions for complex terrains, land cover/types, biogeochemistry, and plant canopy models are needed as an improvement beyond traditional and widely used Monin-Obuhkov similarity theory.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Department of Energy’s Atmospheric System Research (ASR) Program’s Workshop on the Future of Atmospheric Large Eddy Simulation (LES) (Workshop Report)

Large-eddy simulation (LES) is used as a tool to understand physical processes such as turbulence, aerosols, clouds, precipitation, radiation, the interactions among all these, and their interactions with the underlying surface. Over the next 10 years, LES will drive fundamental progress in open scientific questions in these areas as LES is increasingly used to gain understanding of complex interacting physical processes involving atmospheric turbulence. This growth will be driven both by scientific demand and the expansion of computational resources needed to conduct LES, and the form that the growth takes will largely be determined by how computational resources are leveraged for scientific gain. In particular, we suggest that computational resources are likely to be leveraged in two separate but not necessarily distinct ways. On one hand, growth in computational resources will allow LES to be made more routine, that is, performed more frequently, while on the other hand, the computational expense (measured in total floating point operations) afforded to individual LES will expand dramatically, allowing simulations to increase in both domain size and resolution as well as physical detail.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Department of Energy’s Atmospheric System Research (ASR) Program’s Workshop on the Future of Atmospheric Large Eddy Simulation (LES) (Workshop Report)

Large-eddy simulation (LES) is used as a tool to understand physical processes such as turbulence, aerosols, clouds, precipitation, radiation, the interactions among all these, and their interactions with the underlying surface. Over the next 10 years, LES will drive fundamental progress in open scientific questions in these areas as LES is increasingly used to gain understanding of complex interacting physical processes involving atmospheric turbulence. This growth will be driven both by scientific demand and the expansion of computational resources needed to conduct LES, and the form that the growth takes will largely be determined by how computational resources are leveraged for scientific gain. In particular, we suggest that computational resources are likely to be leveraged in two separate but not necessarily distinct ways. On one hand, growth in computational resources will allow LES to be made more routine, that is, performed more frequently, while on the other hand, the computational expense (measured in total floating point operations) afforded to individual LES will expand dramatically, allowing simulations to increase in both domain size and resolution as well as physical detail. Current U.S. Department of Energy (DOE) projects such as LES ARM Symbiotic Simulation and Observation Activity (LASSO) are leading the way in conducting routine LES, building large, public databases that are accessible for data science, sensitivity studies, and training for machine learning. LES will also become more routine as it becomes more accessible for individual researchers to address their scientific questions of interest. Scientific questions addressed by LES over the next 10 years are likely to include cloud organization and aggregation; aerosol cloud interactions and atmospheric chemistry (including geo-engineering); urban-scale LES; atmospheric extreme events, ranging from small-scale severe weather to wildfires; and ocean-wave-atmosphere interactions. Further LES-related research will likely grow significantly in areas related to societal impact studies of air quality and extreme weather events, applications to renewable energy forecasting and resource assessment, and aid in decision-making processes.

54 ENVIRONMENTAL SCIENCES↗