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At least 271 records · Page 15

[2 + 2] Cycloaddition Produces Divalent Organic Color-Centers with Reduced Heterogeneity in Single-Walled Carbon Nanotubes

Organic color centers (OCCs), generated by the covalent functionalization of single-walled carbon nanotubes, have been exploited for chemical sensing, bioimaging, and quantum technologies. However, monovalent OCCs can assume at least 6 different bonding configurations on the sp 2 carbon lattice of a chiral nanotube, resulting in heterogeneous OCC photoluminescence emissions. Herein, we show that a heat-activated [2 + 2] cycloaddition reaction enables the synthesis of divalent OCCs with a reduced number of atomic bonding configurations. The chemistry occurs by simply mixing enophile molecules (e.g., methylmaleimide, maleic anhydride, and 4-cyclopentene-1,3-dione) with an ethylene glycol suspension of SWCNTs at elevated temperature (70–140 °C). Unlike monovalent OCC chemistries, we observe just three OCC emission peaks that can be assigned to the three possible bonding configurations of the divalent OCCs based on density functional theory calculations. Notably, these OCC photoluminescence peaks can be controlled by temperature to decrease the emission heterogeneity even further. Furthermore, this divalent chemistry provides a scalable way to synthesize OCCs with tightly controlled emissions for emerging applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Automated Construction of Artificial Lattice Structures with Designer Electronic States

Manipulating matter with a scanning tunneling microscope (STM) enables the creation of atomically defined artificial structures that host designer quantum states. However, the time-consuming nature of the manipulation process, coupled with the sensitivity of the STM tip, constrains the exploration of diverse configurations and limits the size of the designed features. In this study, we present a reinforcement learning (RL)-based framework for creating artificial structures by spatially manipulating carbon monoxide (CO) molecules on a copper substrate by using the STM tip. The automated workflow combines molecule detection and manipulation, employing deep-learning-based object detection to locate CO molecules and linear assignment algorithms to allocate these molecules to designated target sites. We initially perform molecule maneuvering based on randomized parameter sampling for sample bias, tunneling current set point, and manipulation speed. This data set is then structured into an action trajectory used to train an RL agent. The model is subsequently deployed on the STM for real-time fine-tuning of the manipulation parameters during structure construction. Our approach incorporates path-planning protocols coupled with active drift compensation to enable atomically precise fabrication of structures with significantly reduced human input while realizing larger-scale artificial lattices with the desired electronic properties. Furthermore, using our approach, we demonstrate the automated construction of an extended artificial graphene lattice and confirm the existence of a characteristic Dirac point in its electronic structure. Further challenges regarding the RL-based structural assembly scalability are discussed.

Algorithms↗

Physical origins of the varying performance and unusual transport behaviors among thermoelectric A Mg 2 Sb 2 materials ( A = Ca, Sr, Sm, Yb, and Mg)

Contrary to the similar thermoelectric performance among both AZn 2 Sb 2 and AMg 2 Bi 2 compounds, their isostructural counterparts, AMg 2 Sb 2 , can exhibit thermoelectric figure of merit values that vary by orders of magnitude with different A elements. Here, we reveal physical origins accounting for the significantly differing performance among AMg 2 Sb 2 -based compounds (A = Ca, Sr, Sm, Yb, and Mg) through comprehensive analyses, where it is shown that the dispar- ities in performance at the macroscale essentially originate from the widely varying activation energies that equal amounts of dopant can induce. Meanwhile, a few unusual transport behaviors regarding electrical conductivity, carrier concentration, or lattice thermal con- ductivity among these compounds have been identified, and we also present their rationales in depth. Furthermore, this mechanism-focused study can not only promote further understanding of the complex transport behaviors in condensed matter but be instrumental in rationally tun- ing the physical properties of materials as well.

36 MATERIALS SCIENCE↗

Elucidating the reversible exsolution–dissolution behaviour of high-entropy oxides in crystalline and amorphous phases

High-entropy oxides (HEOs), as a subclass of high-entropy materials (HEMs), offer a versatile platform for catalysis by leveraging entropy-stabilized solid solutions with tunable compositions, lattice structures, and electronic properties. While exsolution–dissolution of metal species in crystalline HEOs has emerged as a promising strategy for reversible active sites regeneration, the dynamic behaviour of HEOs possessing amorphous nature remains under-explored, particularly the difference with crystalline counterparts. In this work, we systematically investigate the architecture-dependent exsolution–dissolution behavior of HEOs by comparing a crystalline-phase HEO (c-HEO) and an amorphous-phase HEO (a-HEO), both comprising Ni, Mg, Cu, Zn, and Co as principal metal elements. Using a combination of in situ variable-temperature X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), electron microscopy, and in situ CO diffuse reflectance infrared Fourier transform spectroscopy (CO-DRIFTS), the structural evolution of the two HEO phases under redox conditions was elucidated. Both materials exhibit reversible exsolution of metallic species or alloys in reducing environments, followed by re-incorporation into the host lattice upon oxidation. Remarkably, the a-HEO demonstrates more facile and dynamic self-healing behavior, with alloy exsolution and dissolution occurring under milder conditions because of its enhanced reducibility and structural disorder. This study provides critical insights into the design of next-generation regenerable catalysts based on amorphous HEOs, highlighting the role of phase structure in governing reversible metal-site formation dynamics and catalytic performance.

Wang, Qingju [Univ. of Tennessee, Knoxville, TN (U↗

Lattice-Nitrogen-Mediated Chemistry Suppresses Hydrogen Evolution for Record Faradaic Efficiency in Ammonia Synthesis

Ammonia (NH 3 ) production using air, water, and electricity offers a transformative route to carbon-free chemical synthesis, addressing global sustainability challenges. However, the hydrogen evolution reaction (HER) in aqueous systems significantly hinders NH 3 selectivity, limiting Faradaic efficiency (FE) to below ~15%. Here, we report an FE of approximately 48%, the highest recorded for aqueous NH 3 synthesis, using two-dimensional (2D) nitride catalysts. These catalysts enable lattice nitrogen protonation through the Mars-van Krevelen (MvK) mechanism, effectively suppressing HER. Using operando spectroelectrochemistry, we identified active sites and tracked nitrogen vacancy cycles, providing unprecedented insights into the reaction pathways. Our findings, supported by advanced computational techniques and complementary spectroscopic analyses, highlight the stability and efficiency of the MvK cycle, setting a new benchmark for sustainable NH 3 production.

catalysts↗

Range and strength of mechanical interactions of force dipoles in elastic fiber networks

Mechanical forces generated by myosin II molecular motors drive diverse cellular processes, most notably shape change, division and locomotion. These forces may be transmitted over long range through the cytoskeletal medium – a disordered, viscoelastic network of biopolymers. The resulting cell size scale force chains can in principle mediate mechanical interactions between distant actomyosin units, leading to self-organized structural order in the cell cytoskeleton. Inspired by such force transmission through elastic structures in the cytoskeleton, we consider a percolated fiber lattice network, where fibers are represented as linear elastic elements that can both bend and stretch, and the contractile activity of myosin motors is represented by force dipoles. Then, by using a variety of metrics, we show how two such contractile force dipoles interact with each other through their mutual mechanical deformations of the elastic fiber network. As a prelude to two-dipole interactions, we quantify how forces propagate through the network from a single anisotropic force dipole by analyzing clusters of nodes connected by highly strained bonds, as well as through the decay rate of strain energy with distance from a force dipole. We show that predominant fiber bending screens out force propagation, resulting in reduced and strongly network configuration-dependent dipole interactions. On the other hand, stretching-dominated networks support longer-ranged inter-dipole interactions that recapitulate the predictions of linear elasticity theory. By characterizing the differences between tensile and compressive force propagation in the fiber network, we show how inter-dipole interaction depends on the dipoles’ mutual separation and orientation. The resulting elastic interaction energy may mediate a force between multiple distant dipoles, leading to their self-organization into ordered configurations. In conclusion, this provides a potential pathway for active mechanical force-driven structural order in elastic biopolymer networks.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Quantum simulations in effective model spaces: Hamiltonian-learning variational quantum eigensolver using digital quantum computers and application to the Lipkin-Meshkov-Glick model

Quantum simulations offer the potential to predict the structure and dynamics of nuclear many-body systems that are beyond the capabilities of classical computing. Generally, preparing the ground state of strongly-interacting many-body systems relevant to nuclear physics is however inefficient, even using ideal quantum computers. In addition, currently available NISQ-era quantum devices possess modest numbers of qubits, limiting the size of quantum many-body systems that can be simulated. In this context, a reformulation of the quantum many-body problems using truncated model spaces and Hamiltonians is desirable to make them more amenable to near-term quantum computers. The importance of symmetries in low-energy theories, including effective field theories (EFTs), lattice quantum chromodynamics (QCD), and effective model spaces for nuclear systems, in particular their interplay with the reduction of active Hilbert spaces, is well known. Lesser known is the fact that the non-commutivity of some symmetries and truncations of the model space can be profitably combined with variational calculations to rearrange the entanglement into localized structures and enable more efficient simulations. Here, the goal of the present study is to explore and utilize the non-commutivity of symmetries and model-space truncations of quantum many-body systems important to nuclear physics, particularly in combination with variational algorithms for quantum simulations and effective Hamiltonian learning. We introduce an iterative hybrid classical-quantum algorithm, Hamiltonian learning variational quantum eigensolver (HL-VQE), that simultaneously optimizes an effective Hamiltonian, thereby rearranging entanglement into the effective model space, and the associated ground-state wavefunction. Quantum simulations, using classical computers and IBM's superconducting-qubit quantum computers, are performed to demonstrate the HL-VQE algorithm, in the context of the Lipkin-Meshkov-Glick (LMG) model of interacting fermions, where the Hamiltonian transformation corresponds to an orbital rotation. We use a mapping where the number of qubits scales with the $\log$ of the size of the effective model space, rather than the particle number. HL-VQE is found to provide an exponential improvement in LMG-model calculations of the ground-state energy and wavefunction, compared to naive truncations without Hamiltonian learning, throughout a significant fraction of the Hilbert space. In the context of EFT, this corresponds to counterterms scaling exponentially with the cut-off as opposed to power law. Implementations on IBM's QExperience quantum computers and simulators for 1- and 2-qubit effective model spaces are shown to provide accurate and precise results, reproducing classical predictions. For a range of parameters defining the LMG model, the HL-VQE algorithm is found to have better scaling of quantum resources requirements than previously explored algorithms. In particular, the HL-VQE scales efficiently over a large fraction of the model space, in contrast to VQE alone. This work constitutes a step in the development of entanglement-driven quantum algorithms for descriptions of nuclear many-body systems. This, in part, leverages the potential of noisy intermediate-scale quantum (NISQ) devices. The exponential scaling of counterterms observed in this study suggests the possibility of more general applicability to other non-perturbative EFTs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Strong Proton‐Phonon Coupling Drives Fast Ion Transport in Perovskites

Conduction of protons in solids is a cooperative process propelled by phonons, with molecular details obscured by the irregular movements in the thermal bath. It is shown that substitution with Y forms an imaginary phonon mode, instrumental for the function as proton conductor and effectively lowering the activation barrier for proton transport. To untangle the interplay in the exemplary proton conductor BaSn 0.9 Y 0.1 O 3 , its crystallographic structure is determined with high resolution neutron diffractometry and its phonon density of states with density functional theory calculations, experimentally validated by element specific nuclear resonant vibration spectroscopy. Based on phonon analysis, a quantitative transport model is present, which predicts the activation energy and performance by the ratio of ionic radii. Rather than individual vibrational modes, it is the oxygen sub-lattice which exerts its momentum on the protons. The extent of this momentum transfer is governed by the ratio of ionic radii. This model extends the transition state theory by the phonon-phonon interaction and complements the previously proposed idea that lattice dynamics is decisive for proton transport and specifies which properties of the material exactly define the vibration properties.

activation barriers↗

Multiple Synchrotron Light Monitors for Transverse Matching and Monitoring at CEBAF

Beam setup at the Continuous Electron Beam Accelerator Facility (CEBAF) involves threading beam through the machine and monitoring global transfer functions to identify and address cumulative lattice errors. Transverse beam emittance may grow by as much as two orders of magnitude, mediated by synchrotron radiation. Re-matching the enlarged beam phase space into successive re-circulation arcs minimizes this emittance growth but requires knowledge of the actual beam distribution. This is now accomplished through quadrupole scans using wire profile monitors, the most time-consuming activity in our setup process. We propose to use Synchrotron Light Monitors (SLMs) to image the beam at homologous points in the four super-period recirculation arc lattices. Benefits include real-time monitoring of beam parameters and reduced elapsed time for initial setup.These SLMs will be installed in Arc 7 of the CEBAF machine, where Synchrotron Radiation contributes moderately to emittance growth. One of four required SLMs will be installed and commissioned this year, with the rest being installed next year.

Freeman, B.↗

Role of Electron Correlation beyond the Active Space in Achieving Quantitative Predictions of Spin-Phonon Relaxation

Single-molecule magnets (SMMs) are promising candidates for molecular-scale data storage and processing due to their strong magnetic anisotropy and long spin relaxation times. However, as temperature rises, interactions between electronic states and lattice vibrations accelerate spin relaxation, significantly limiting their practical applications. Recently, ab initio simulations have made it possible to advance our understanding of phonon-induced magnetic relaxation, but significant deviations from experiments have often been observed. The description of molecules’ electronic structure has been mostly based on complete active space self-consistent field (CASSCF) calculations, and the impact of electron correlation beyond the active space remains largely unexplored. In this study, we provide the first systematic investigation of spin-phonon relaxation in SMMs with post-CASSCF multiconfigurational methods, specifically CAS followed by second-order perturbation theory and multiconfiguration pair-density functional theory. Taking Co(II)- and Dy(III)-based SMMs as case studies, we analyze how electron correlation influences spin-phonon relaxation rates across a range of temperatures, comparing theoretical predictions with experimental observations. Our findings demonstrate that post-CASSCF treatments make it possible to achieve quantitative predictions for Co(II)-based SMMs. For Dy(III)-based systems, however, accurate predictions require consideration of additional effects, underscoring the urgent necessity of further advancing the study of the effects of electronic correlation in these complex systems.

Energy↗

Tensile creep properties of a CrMnFeCoNi high-entropy alloy

Tensile creep tests were performed on a CrMnFeCoNi high-entropy alloy at temperatures from 1023 K to 1173 K. A uniform stress exponent 3.7 ± 0.1 was found across all temperatures. The apparent activation energies of creep under various applied stresses were determined to be around 230 kJ/mol and decrease with increasing stress, indicating a stress-assisted, thermally activated behavior. Steady-state creep microstructures feature no subgrain formation and high dislocation density within grains. Based on our results, the creep rate of CrMnFeCoNi is believed to be controlled by both dislocation-dislocation interactions and dislocation-lattice interactions.

36 MATERIALS SCIENCE↗

Surface Lattice-Embedded Pt Single-Atom Catalyst on Ceria-Zirconia with Superior Catalytic Performance for Propane Oxidation

Tuning the metal–support interaction and coordination environment of single-atom catalysts can help achieve satisfactory catalytic performance for targeted reactions. Herein, via the facile control of calcination temperatures for Pt catalysts on pre-stabilized Ce 0.9 Zr 0.1 O 2 (CZO) support, Pt single atoms (Pt 1 ) with different strengths of Pt–CeO 2 interaction and coordination environment were successfully constructed. With the increase in calcination temperature from 350 to 750 °C, a stronger Pt–CeO 2 interaction and higher Pt-O-Ce coordination number were achieved due to the reaction between PtO x and surface Ce 3+ species as well as the migration of Pt 1 into the surface lattice of CZO. The Pt/CZO catalyst calcined at 750 °C (Pt/CZO-750) exhibited a surprisingly higher C 3 H 8 oxidation activity than that calcined at 550 °C (Pt/CZO-550). Here, through systematic characterizations and reaction mechanism study, it was revealed that the higher concentration of surface Ce 3+ species/oxygen vacancies and the stronger Pt–CeO 2 interaction on Pt/CZO-750 could better facilitate the activation of oxygen to oxidize C 3 H 8 into reactive carbonate/carboxyl species and further promote the transformation of these intermediates into gaseous CO 2 . The Pt/CZO-750 catalyst can be a potential candidate for the catalytic removal of hydrocarbons from vehicle exhaust.

36 MATERIALS SCIENCE↗

Million-scale data integrated deep neural network for phonon properties of heuslers spanning the periodic table

Existing machine learning potentials for predicting phonon properties of crystals are typically limited on a material-to-material basis, primarily due to the exponential scaling of model complexity with the number of atomic species. We address this bottleneck with the developed Elemental Spatial Density Neural Network Force Field, namely Elemental-SDNNFF. The effectiveness and precision of our Elemental-SDNNFF approach are demonstrated on 11,866 full, half, and quaternary Heusler structures spanning 55 elements in the periodic table by prediction of complete phonon properties. Self-improvement schemes including active learning and data augmentation techniques provide an abundant 9.4 million atomic data for training. Deep insight into predicted ultralow lattice thermal conductivity (<1 Wm –1 K –1 ) of 774 Heusler structures is gained by p–d orbital hybridization analysis. Additionally, a class of two-band charge-2 Weyl points, referred to as “double Weyl points”, are found in 68% and 87% of 1662 half and 1550 quaternary Heuslers, respectively.

36 MATERIALS SCIENCE↗

Accelerator physics at NSLS-II: research accomplishments in 2020

NSLS-II accelerator physicists provide scientific support for user operations, as well as for improvements and developments of the accelerator systems. This work includes optimization of the NSLS-II performance with high beam current and low vertical emittance, improvement of the beam stability, development of new software tools for operations and beam studies. The accelerator physicists productively worked on a number of research activities such as the conceptual design of NSLS-II accelerator upgrade; design and optimization of advanced low-emittance lattices; development of novel methods to study nonlinear beam dynamics; ultrafast electron diffraction and microscopy. The physicists also contributed to the BNL electron-ion collider project, to the APS and ALS upgrade projects. Research accomplishments achieved in 2020, are summarized in this report.

43 PARTICLE ACCELERATORS↗

Electron Energy-Loss Spectroscopy and Differential Phase Contrast Imaging with Active Decision in Multimodal Electron Microscopy: Isotopic detection at the atomic scale

Isotopic engineering provides a powerful route to control phonon behavior in crystalline solids, enabling fundamental studies of lattice dynamics and heat transport at the atomic scale. Here, we directly visualize isotope-dependent phonon propagation in epitaxial Cr 2 O 3 using aberration-corrected scanning transmission electron microscopy (STEM) combined with monochromated, high-energy-resolution electron energy-loss spectroscopy (EELS). Guided by ab initio phonon calculations, we demonstrate that optical phonon modes above 70 meV are predominantly oxygen-derived and exhibit measurable redshifts upon substitution of natural 16 O by enriched 18 O. Spatially resolved vibrational spectrum imaging reveals isotope-enriched tracer layers within Cr 2 O 3 thin films, correlating isotope concentration with phonon intensity variations and vibrational energy shifts. At the nanometer and atomic scales, vibrational EELS mapping uncovers coherent phonon propagation across isotopic interfaces, consistent with theoretical phonon density of states and dispersion relations. These results establish vibrational EELS as a quantitative probe for isotope-dependent phonon transport in materials, opening new possibilities for studying energy dissipation and lattice dynamics.

36 MATERIALS SCIENCE↗

Pattern formation in odd viscoelastic fluids

Nonreciprocal interactions fueled by local energy consumption can be found in biological and synthetic active matter at scales where viscoelastic forces are important. Such systems can be described by “odd” viscoelasticity, which assumes fewer material symmetries than traditional theories. Here we study odd viscoelasticity analytically and using lattice Boltzmann simulations. We identify a pattern-forming instability which produces an oscillating array of fluid vortices, and we elucidate which features govern the growth rate, wavelength, and saturation of the vortices. Our observation of pattern formation through odd mechanical response can inform models of biological patterning and guide engineering of odd dynamics in soft active matter systems. Published by the American Physical Society 2024

Floyd, Carlos (ORCID:0000000262707250)↗

Solution-Phase Synthesis of PdH 0.706 Nanocubes with Enhanced Stability and Activity toward Formic Acid Oxidation

We report palladium is one of the few metals capable of forming hydrides, with the catalytic properties being dependent on the elemental composition and spatial distribution of H atoms in the lattice. Herein, we report a facile method for the complete transformation of Pd nanocubes into a stable phase made of PdH 0.706 by treating them with aqueous hydrazine at a concentration as low as 9.2 mM. Using formic acid oxidation (FAO) as a model reaction, we systematically investigated the structure–catalytic property relationship of the resultant nanocubes with different degrees of hydride formation. The current density at 0.4 V was enhanced by four times when the nanocubes were completely converted from Pd to PdH 0.706 . On the basis of a set of slab models with PdH(100) overlayers on Pd(100), we conducted density functional theory calculations to demonstrate that the degree of hybrid formation could influence both the activity and selectivity toward FAO by modulating the relative stability of formate (HCOO) and carboxyl (COOH) intermediates. Furthermore, this work provides a viable strategy for augmenting the performance of Pd-based catalysts toward various reactions without altering the loading of this scarce metal.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synthesis of Core@Shell Cu-Ni@Pt-Cu Nano-Octahedra and Their Improved MOR Activity

Fabrication of 3d metal-based core@shell nanocatalysts with engineered Pt-surfaces provides an effective approach for improving the catalytic performance. The challenges in such preparation include shape control of the 3d metallic cores and thickness control of the Pt-based shells. Herein, we report a colloidal seed-mediated method to prepare octahedral CuNi@Pt-Cu core@shell nanocrystals using CuNi octahedral cores as the template. By precisely controlling the synthesis conditions including the deposition rate and diffusion rate of the shell-formation through tuning the capping ligand, reaction temperature, and heating rate, uniform Pt-based shells can be achieved with a thickness of < 1 nm. Furthermore, the resultant carbon-supported CuNi@Pt-Cu core@shell nano-octahedra showed superior activity in electrochemical methanol oxidation reaction (MOR) compared with the commercial Pt/C catalysts and carbon-supported CuNi@Pt-Cu nano-polyhedron counterparts, demonstrating that both the lattice strain and shape effects arising from the as-prepared CuNi@Pt-Cu octahedral nanocatalysts play a crucial role in MOR performance.

36 MATERIALS SCIENCE↗