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At least 451 records · Page 25

Roadmap on multiscale materials modeling

Modeling and simulation is transforming modern materials science, becoming an important tool for the discovery of new materials and material phenomena, for gaining insight into the processes that govern materials behavior, and, increasingly, for quantitative predictions that can be used as part of a design tool in full partnership with experimental synthesis and characterization. Modeling and simulation is the essential bridge from good science to good engineering, spanning from fundamental understanding of materials behavior to deliberate design of new materials technologies leveraging new properties and processes. This Roadmap presents a broad overview of the extensive impact computational modeling has had in materials science in the past few decades, and offers focused perspectives on where the path forward lies as this rapidly expanding field evolves to meet the challenges of the next few decades. The Roadmap offers perspectives on advances within disciplines as diverse as phase field methods to model mesoscale behavior and molecular dynamics methods to deduce the fundamental atomic-scale dynamical processes governing materials response, to the challenges involved in the interdisciplinary research that tackles complex materials problems where the governing phenomena span different scales of materials behavior requiring multiscale approaches. The shift from understanding fundamental materials behavior to development of quantitative approaches to explain and predict experimental observations requires advances in the methods and practice in simulations for reproducibility and reliability, and interacting with a computational ecosystem that integrates new theory development, innovative applications, and an increasingly integrated software and computational infrastructure that takes advantage of the increasingly powerful computational methods and computing hardware.

36 MATERIALS SCIENCE↗

Combining Experimental and Theoretical Techniques to Gain an Atomic Level Understanding of the Defect Binding Mechanism in Hard Carbon Anodes for Sodium Ion Batteries

Sodium ion batteries (NIBs) are an attractive alternative to lithium–ion batteries in applications that require large–scale energy storage due to sodium's high natural abundance and low cost. Hard carbon (HC) is the most promising anode material for NIBs; however, there is a knowledge gap in the understanding of the sodium binding mechanism that prevents a rational design of HC. This study tunes sucrose–derived HC via synthesis temperature then evaluates the structural, physical, and electrochemical properties. Neutron total scattering is used to generate structural models by fitting pair distribution functions (PDF) with a combination of molecular dynamics and reverse Monte Carlo methods. From this model, the number and type of structural features are identified, quantified, and correlated to the galvanostatic charge/discharge. A method of PDF “fingerprinting” binding sites using Na probe atoms is developed and analyzing these PDFs reveals an atomistic view of ion binding sites responsible for “defect” storage mechanisms. Combining these techniques results in an atomic–level study that provides a big picture of the Na–binding mechanism in NIBs, which allows for more precise tuning of the structure–property relationships in the future. Finally, the methodologies developed will also enable new strategies for the analysis of amorphous functional materials.

25 ENERGY STORAGE↗

A heat flux sensor leveraging the transverse Seebeck effect in elemental antimony

Certain configurations of anisotropic single crystal materials can generate a thermoelectric voltage orthogonal to an induced temperature gradient. This phenomenon is known as the Transverse Seebeck Effect (TSE) and can be leveraged to fabricate simple and robust heat flux sensors. Only a small number of materials have been considered as TSE-based transducers and, among these, few have been developed into sensors with ruggedization against chemical and mechanical degradation. Here, we report on the fabrication and characterization of a rugged TSE-based heat flux sensor using prismatic antimony single crystals. The heat flux sensor was tested under static and dynamic heating scenarios. The sensor has a linear responsivity of 16.8 µV/(W/cm2) to heat fluxes spanning more than two orders of magnitude and a time constant of 4.4 s. The sensor’s response to localized heating, probed with a laser scanning technique, validated that the transduction mechanism is primarily the TSE by ruling out a sizable contribution from the conventional Seebeck effect. Finite element analysis corroborated that components used in the sensor package are the primary determinants of the time constant and the decrement of the responsivity from its theoretical maximum. Design principles that may be applied to elicit a faster transient response or higher responsivity are proposed. Furthermore, the results establish single crystal antimony as a promising transducer material for heat flux measurement systems and demonstrate potential effects of ruggedization on sensor performance.

36 MATERIALS SCIENCE↗

Polarization control in spin-transparent hadron colliders by weak-field navigators involving lattice enhancement effect

Hadron polarization control schemes for Spin Transparent (ST) synchrotrons are analyzed. The spin dynamics and beam polarization in such synchrotrons are controlled by spin navigators (SN) which are special small insertions of weak magnetic fields. An SN stabilizes the beam polarization and allows for setting any desirable spin orientation at an interaction point in the operational regime, including a frequent spin flip. We present a general approach to design of SNs. We distinguish different types of SNs, namely, those not causing closed orbit perturbation as well as those producing local and global orbit distortions. In the second case, the concept of the spin response function in an ST synchrotron is applied and expanded to reveal the effect of the SN strength enhancement by magnetic lattice of the synchrotron. We provide conceptual schemes for SN designs using longitudinal and transverse magnetic fields allowing for polarization control at low as well as high energies. We also develop the ST concept for ultra-high energies. This development may enable and stimulate interest in polarized beam experiments in possible polarized collider projects such as Large Hadron Collider (LHC), Future Circular Collider (FCC) and Super Proton Proton Collider (SPPC).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Virtual prototyping of liquid metal blanket performance in fusion pilot plant

Liquid metal blanket is a dominant design option for the next step fusion devices responsible for harvesting energy from fusion reaction, and simultaneously producing fuel for the same reaction through tritium breeding. Liquid metal blankets introduce additional complexity to the design due to fluid motion, fluid structure interaction, and magnetohydrodynamic (MHD) effects arising from the motion of the conducting fluid through the magnetic field. They are also directly affected by the plasma heat flux and neutronic fluence. PPPL is currently developing a virtual prototyping system for numerical analysis of the liquid metal blankets for future fusion devices. The system has a customized 3D computational fluid dynamics (CFD) code in its core, allowing MHD flow and conjugate heat transfer analysis in blankets fluids and solids. The code was successfully used before for dual coolant blanket analysis [A. Khodak et al., Fusion Eng. and Des. 137 (2018)]. Recently the same code was modified to allow verified simulation of MHD flows at high Hartmann numbers of several thousand typical for blanket applications. CFD code receives volumetric heat source distribution from the neutronic analysis based on MCNP code. In addition, direct tritium breeding simulation will be performed allowing optimization of the blanket performance. 2D axisymmetric version of neutronics code will be used for rapid optimization, with 3D version employed for detailed analysis. The surface heat distribution on the plasma facing wall will be defined by the software HEAT allowing 3D modeling of the heat flux based on the magnetic field distribution including gyro-orbit effects. Results of thermal analysis are imported into structural analysis code also included in the system. Finally, direct import of CAD geometry will be used for analyzing all components and as a result design option can be efficiently optimized.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Simulation of ultrafast transient absorption spectra of a perylene-based light harvesting antenna

Atomistic simulations of photo-induced responses in artificial light-harvesting molecular systems help to reveal the mechanisms of ultrafast intramolecular energy transfer between individual chromophores. These light-induced processes mimic the primary events occurring in natural photosynthesis. Modeling studies contribute to the design of more efficient molecular architectures enabling performance optimization for applications in light harvesting, energy conversion, and optoelectronics. Within this context, the direct comparison between simulated and experimental transient absorption pump–probe (TA-PP) spectra are especially valuable for validating theoretical approaches and deepening mechanistic understanding. Herein, we investigate the photoinduced dynamics of an antenna system composed of two naphthalene monoimides donor units covalently linked to a perylene derived acceptor. Following photoexcitation, the exciton rapidly self-traps on one of the donor units. Thereafter, efficient ultrafast energy transfer to the acceptor unit takes place via two possible pathways: either through transient exciton localization on the second donor unit or by direct transfer to the acceptor. The simulated TA-PP spectra clearly capture these distinct energy transfer pathways and enable a detailed comparison of their relative efficiencies. This highlights the system's potential for tunable exciton dynamics towards advancing light-harvesting and optoelectronic molecular materials.

36 MATERIALS SCIENCE↗

Hierarchical Materials from High Information Content Macromolecular Building Blocks: Construction, Dynamic Interventions, and Prediction

Hierarchical materials that exhibit order over multiple length scales are ubiquitous in nature. Because hierarchy gives rise to unique properties and functions, many have sought inspiration from nature when designing and fabricating hierarchical matter. More and more, however, nature’s own high-information content building blocks, proteins, peptides, and peptidomimetics, are being coopted to build hierarchy because the information that determines structure, function, and interfacial interactions can be readily encoded in these versatile macromolecules. Here, we take stock of recent progress in the rational design and characterization of hierarchical materials produced from high-information content blocks with a focus on stimuli-responsive and “smart” architectures. We also review advances in the use of computational simulations and data-driven predictions to shed light on how the side chain chemistry and conformational flexibility of macromolecular blocks drive the emergence of order and the acquisition of hierarchy and also on how ionic, solvent, and surface effects influence the outcomes of assembly. Furthermore, continued progress in the above areas will ultimately usher in an era where an understanding of designed interactions, surface effects, and solution conditions can be harnessed to achieve predictive materials synthesis across scale and drive emergent phenomena in the self-assembly and reconfiguration of high-information content building blocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

STFM: Accurate Spatio-Temporal Fusion Model for Weather Forecasting

Meteorological prediction is crucial for various sectors, including agriculture, navigation, daily life, disaster prevention, and scientific research. However, traditional numerical weather prediction (NWP) models are constrained by their high computational resource requirements, while the accuracy of deep learning models remains suboptimal. In response to these challenges, we propose a novel deep learning-based model, the Spatiotemporal Fusion Model (STFM), designed to enhance the accuracy of meteorological predictions. Our model leverages Fifth-Generation ECMWF Reanalysis (ERA5) data and introduces two key components: a spatiotemporal encoder module and a spatiotemporal fusion module. The spatiotemporal encoder integrates the strengths of convolutional neural networks (CNNs) and recurrent neural networks (RNNs), effectively capturing both spatial and temporal dependencies. Meanwhile, the spatiotemporal fusion module employs a dual attention mechanism, decomposing spatial attention into global static attention and channel dynamic attention. This approach ensures comprehensive extraction of spatial features from meteorological data. The combination of these modules significantly improves prediction performance. Experimental results demonstrate that STFM excels in extracting spatiotemporal features from reanalysis data, yielding predictions that closely align with observed values. In comparative studies, STFM outperformed other models, achieving a 7% improvement in ground and high-altitude temperature predictions, a 5% enhancement in the prediction of the u/v components of 10 m wind speed, and an increase in the accuracy of potential height and relative humidity predictions by 3% and 1%, respectively. This enhanced performance highlights STFM’s potential to advance the accuracy and reliability of meteorological forecasting.

54 ENVIRONMENTAL SCIENCES↗

Dual roles of stepped surfaces: Catalytic initiators and stabilizers of oxygen-induced reconstructions

Understanding surface restructuring under reactive conditions is crucial for designing next-generation catalysts with enhanced activity and selectivity. Here, we employ in situ transmission electron microscopy to directly observe the dynamic behavior of Cu(100) and Cu(410) surfaces under both oxidizing and vacuum annealing conditions, revealing a complex interplay among surface crystallography, local oxygen coverage, Cu atom mobility, and step-edge reactivity. The stepped Cu(410) surface acts as an active site for O 2 dissociation, triggering the oscillatory transformation of the c(2 × 2)–O phase into the more stable (2$\sqrt2$ ×$\sqrt2$)R45°–O missing-row (MR) structure on the adjacent flat Cu(100) terrace. Under subsequent vacuum annealing, this same Cu(410) facet exhibits remarkable structural resilience, preserving the MR reconstruction and chemisorbed oxygen. In contrast, the Cu(100) surface undergoes reversible transitions from the MR structure back to the c(2 × 2)–O phase. These results highlight the critical role of surface morphology in directing both the formation and stability of oxygen-induced reconstructions, demonstrating that stepped surfaces serve dual roles as both catalytic initiators and structural stabilizers. Furthermore, this work offers atomic-level insights into the environment-responsive behavior of copper surfaces, establishing a mechanistic basis for designing Cu-based catalysts through facet-specific control of surface reactivity.

36 MATERIALS SCIENCE↗

Field-Coupled Water Splitting with Metal-Free Donor–Acceptor Covalent Organic-Framework Junctions

Advancing metal-free electrocatalysts for hydrogen and oxygen evolution reactions (HER/OER) across acidic and alkaline media requires coordinated control of intermediate binding thermodynamics, interfacial charge delivery, and near-electrode transport dynamics. Here, we design amide-linked benzene–triazine covalent organic frameworks (BTA/TzTA-Hz COFs) and integrate them with carbon nanotubes (CNTs) to form COF–CNT junctions that establish a built-in interfacial electric field. Density functional theory (DFT) and electrostatic potential maps indicate complementary active motifs, with benzene-proximal fragments associated with HER and triazine-proximal motifs associated with OER. CNT integration shifts the contact-potential difference by ≈0.20 V, while operando electrochemical impedance spectroscopy suggests partially separable high-frequency junction-charging and lower-frequency Faradaic/transport responses. A 300 mT static magnetic field lowers the HER and OER overpotentials by tens of millivolts. Under anodic bias, the effective interfacial charging capacitance increases, and Mott–Schottky analysis shows an apparent ∼0.15 V flat-band shift with an essentially unchanged slope. Together, these observations are consistent with field-perturbed interfacial charging and altered bias partitioning. Field-dependent impedance and bubble imaging are consistent with magnetohydrodynamic convection that promotes bubble detachment and near-electrode mass transport for both half-reactions, and they reveal an OER-specific high-frequency perturbation under anodic bias. Under field, the heterostructure reaches an OER onset overpotential of ∼261 mV and requires an overpotential of 366 mV at 10 mA cm –2 in alkaline electrolyte. These results illustrate how reticular-framework chemistry, junction engineering, and both built-in and applied fields can program reactivity through interfacial electrostatics and near-electrode transport in organic-framework electrocatalysts.

Garcia-Enriquez, Lissette [Univ. of Texas at El Pa↗

A Simplified Numerical Approach to Characterize the Thermal Response of a Moving Bed Solar Reactor

Abstract Concentrated solar thermochemical storage in the form of a zero-emission fuel is a promising option to produce long-duration energy storage. Solar fuel is produced using a cavity reactor that captures concentrated solar radiation from a solar field of heliostats. In this paper, heat transfer model of a tubular plug-flow reactor designed and manufactured for a solar fuel production is presented. Experimental data collected from a fixed bed tubular reactor testing are used for model comparison. The system consists of an externally heated tube with counter-current flowing gas and moving solid particles as the heated media. The proposed model simulates the dynamic behavior of temperature profiles of the tube wall, gas, and particles under various gas flowrates and residence times. The heat transfer between gas–wall, solid particle–wall, and gas–solid particle is numerically studied. The model results are compared with the results of experiments done using a 4 kW furnace with a 150 mm heating zone surrounding a horizontal alumina tube (reactor) with 50.8 mm outer diameter and thickness of 3.175 mm. Solid fixed particles of magnesium manganese oxide (MgMn2O4) with the size of 1 mm are packed within the length of 250 mm at the center of the tube length. Simulation results are assessed with respect to fixed bed experimental data for four different gas flowrates, namely, 5, 10, 15, and 20 standard liters per minute of air, and furnace temperatures in the range of 200–1200 °C. The simulation results showed good agreement with maximum steady state error that is less than 6% of those obtained from the experiments for all runs. The proposed model can be implemented as a low-order physical model for the control of temperature inside plug-flow reactors for thermochemical energy storage applications.

Engineering↗

New principles of self‐organization created through the interplay of DNA condensates, microtubules, and motors

Bioinspired design—which holds great promise for a new generation of materials that are robust to defects, scalable under green manufacture, environmentally responsive, and programmably reconfigurable—requires mastery over molecular self-organization. Yet, from its specific mechanisms to most general architectures, the principles governing self-organization remain poorly understood and not even fully enumerated. For living systems, one obvious architectural principle is the modular reuse of a few simple molecular components in myriad combinations to achieve more complex phenomena. For example, the mechanical tasks of a cell are driven by the nonequilibrium dynamics of cytoskeletal filaments and molecular motors—the same filaments and motors, reprogrammed by a variety of modulators, perform tasks ranging from cell movement to division. Similarly, many compartmentalization tasks are performed by liquid-like condensates of simple components, which act as membraneless organelles to localize particular molecules in space and time (e.g. for gene regulation or RNA processing). In a few cases, condensates combine and interact with the cytoskeleton to create still more complex phenomena, e.g. the nucleation of microtubule asters from the centrosome (a protein condensate) to form the mitotic spindle during cell division. Very little is known about the fundamental mechanisms of such filament-plus-condensate phenomena. Despite few examples, the landscape of behaviors that can be achieved through the combination of condensates, filaments, and motors appears vast. However, exploration has been hindered by a lack of systems that have sufficiently programmable and dynamically tunable interactions between component condensates, filaments, and motors. We proposed to combine programmable DNA condensates, filamentous microtubules, and light-controlled motors into self-organizing systems whose principles go beyond those that have been observed in nature. In one limit, our systems will use microtubules and motors to create the molecular analog of a network of roads, which will organize droplets of DNA condensates capable of carrying molecular cargo. DNA condensates coupled to motors will flow from one microtubule aster hub to another, with their direction and timing controlled by DNA circuits. In another limit, microtubules will swim through bulk DNA condensates and exhibit strong interactions with boundaries between different types of condensates. Microtubule swimmers will reflect, get trapped, or refract at boundaries, under a mechanical analog of the classical optical index of refraction. DNA condensates having different mechanical indexes of refraction will be used to construct the analog of optical lenses, so that microtubule swimmers can be manipulated like light—collimated, diffracted, focused, and sorted based on properties analogous to wavelength. These two limits define two new architectures, within which multiple new mechanistic principles for self-organization will be discovered and explored. To explore these architectures, the motor-based coupling between DNA condensates and filaments will be controlled in time and space through the use of opto-proteins that create reversible links between DNA condensates and motors upon illumination. For each principle of interest, patterns of light will create virtual experiments by defining patterns of activity where DNA condensates walk along filaments, or filaments swim through condensates, and patterns of inactivity which will serve either as controls, or as boundary conditions vital to create the desired phenomena. This research serves the goals of Basic Energy Sciences Biomolecular Material Program by elucidating the principles by which the emergent, nonequilibrium behavior of collections of DNA condensates, motors, and microtubules can be programmed by environmental light patterns to create complex motion and materials transport. Because DNA condensates can be readily coupled to virtually any high performance nanomaterial, from carbon nanotubes, to metal nanoparticles, to light harvesting systems, this work provides a path to the construction, self-maintenance and reconfiguration of materials relevant to the Department of Energy.

60 APPLIED LIFE SCIENCES↗

Ultrafast terahertz emission from emerging symmetry-broken materials

Abstract Nonlinear optical spectroscopies are powerful tools for investigating both static material properties and light-induced dynamics. Terahertz (THz) emission spectroscopy has emerged in the past several decades as a versatile method for directly tracking the ultrafast evolution of physical properties, quasiparticle distributions, and order parameters within bulk materials and nanoscale interfaces. Ultrafast optically-induced THz radiation is often analyzed mechanistically in terms of relative contributions from nonlinear polarization, magnetization, and various transient free charge currents. While this offers material-specific insights, more fundamental symmetry considerations enable the generalization of measured nonlinear tensors to much broader classes of systems. We thus frame the present discussion in terms of underlying broken symmetries, which enable THz emission by defining a system directionality in space and/or time, as well as more detailed point group symmetries that determine the nonlinear response tensors. Within this framework, we survey a selection of recent studies that utilize THz emission spectroscopy to uncover basic properties and complex behaviors of emerging materials, including strongly correlated, magnetic, multiferroic, and topological systems. We then turn to low-dimensional systems to explore the role of designer nanoscale structuring and corresponding symmetries that enable or enhance THz emission. This serves as a promising route for probing nanoscale physics and ultrafast light-matter interactions, as well as facilitating advances in integrated THz systems. Furthermore, the interplay between intrinsic and extrinsic material symmetries, in addition to hybrid structuring, may stimulate the discovery of exotic properties and phenomena beyond existing material paradigms.

36 MATERIALS SCIENCE↗

Hydrogen station in situ back-to-back fueling data for design and modeling

Hydrogen technologies are rapidly spreading, with significant attention to the mobility sector requiring a robust and widespread fueling infrastructure. Hydrogen stations are indeed fundamental to transitioning from pilot projects towards large-scale implementation in many countries. Operating under extreme conditions, the new stations need more informed designs and equipment to meet the growing demand and their more frequent utilization. Via a set of experimental research activities and investigated scenarios carried out at the Cal State LA Hydrogen Research and Fueling Facility, here this paper shares a novel and comprehensive set of data collected over a period of one year on fueling events frequency and refueling process station behaviors. A performance evaluation of the station is presented under different load scenarios in severe conditions during "back-to-back fuelings", with monitoring of fundamental parameters for infrastructure sizing, including dynamic cooling response, pressure levels, thermodynamics, and the state of charge of the vehicle. The presented data analysis could surely contribute as closer-to-reality inputs for a variety of station performance modeling tools.

08 HYDROGEN↗

Seismic Performance of Deeply Embedded Conceptual Advanced Reactors: Three-Dimensional Nonlinear Soil-Structure Interaction Analyses

The U.S. Nuclear Regulatory Commission’s functional containment concept provides advanced nuclear power plant designers with more flexibility in terms of the civil/structural design if the appropriate set of barriers for prevention of radioactive material release exist. Some of the conceptual advanced reactor structures, without the traditional pressure boundaries of large containment structures, are proposed to be deeply embedded or buried into soil. This approach is expected to provide (1) lesser seismic demands on the structures and safety-critical structures, (2) eased regulatory efforts and overall design against other external hazards such as aircraft impact, and (3) overall cost savings. Further, one of the important aspects of assessing the technical and economic viability of deeply embedding advanced reactor buildings is to assess the seismic performance with the understanding of effects with material and geometric nonlinearities. This study investigates the seismic response of deeply embedded or buried advanced reactors by conducting three-dimensional nonlinear soil-structure interaction analyses. Although the results indicate that there is a general trend of decreased seismic response with increased embedment depths, the change in the dynamic environment with different embedment depths and the nonlinear environment under high-intensity seismic inputs may result in increased peak response at increased embedment depths.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Glancing Angle Deposition in Gas Sensing: Bridging Morphological Innovations and Sensor Performances

Glancing Angle Deposition (GLAD) has emerged as a versatile and powerful nanofabrication technique for developing next-generation gas sensors by enabling precise control over nanostructure geometry, porosity, and material composition. Through dynamic substrate tilting and rotation, GLAD facilitates the fabrication of highly porous, anisotropic nanostructures, such as aligned, tilted, zigzag, helical, and multilayered nanorods, with tunable surface area and diffusion pathways optimized for gas detection. This review provides a comprehensive synthesis of recent advances in GLAD-based gas sensor design, focusing on how structural engineering and material integration converge to enhance sensor performance. Key materials strategies include the construction of heterojunctions and core–shell architectures, controlled doping, and nanoparticle decoration using noble metals or metal oxides to amplify charge transfer, catalytic activity, and redox responsiveness. GLAD-fabricated nanostructures have been effectively deployed across multiple gas sensing modalities, including resistive, capacitive, piezoelectric, and optical platforms, where their high aspect ratios, tailored porosity, and defect-rich surfaces facilitate enhanced gas adsorption kinetics and efficient signal transduction. These devices exhibit high sensitivity and selectivity toward a range of analytes, including NO2, CO, H2S, and volatile organic compounds (VOCs), with detection limits often reaching the parts-per-billion level. Emerging innovations, such as photo-assisted sensing and integration with artificial intelligence for data analysis and pattern recognition, further extend the capabilities of GLAD-based systems for multifunctional, real-time, and adaptive sensing. Finally, current challenges and future research directions are discussed, emphasizing the promise of GLAD as a scalable platform for next-generation gas sensing technologies.

Chemistry↗

Breaking the Brønsted–Evans–Polanyi Relation with Dual-Metal Sites

Linear scaling relationships impose inherent limitations on catalyst activity; the Brønsted−Evans−Polanyi (BEP) relation, which correlates activation and reaction energies, is a prominent example. Here we report a dual-metal site catalyst (DMSC) on ceria that breaks the BEP relation for C−C coupling of methyl intermediates an elementary step in methane coupling to form ethane. The DMSC structure on CeO 2 (111) was discovered by density-functional theory (DFT) structural exploration and confirmed to be stable via ab initio thermodynamics and ab initio molecular dynamics. Homonuclear and heteronuclear DMSCs of Ni, Pd, Pt, Fe, Ru, Os, Co, Rh, and Ir (45 pairs in total) were examined for methyl affinity and methyl−methyl coupling activation energy. We found that many heteronuclear DMSCs break the BEP linear scaling due to a mixed low-affinity/high-affinity coadsorption of the two methyl groups, decoupling the step responsible for the activation energy (E a ) at the low-affinity site from the overall reaction energy (ΔE) determined by both sites. This mechanism of breaking the BEP relationship via the DMSCs offers a catalyst design principle for C−C coupling reactions.

Chen, Yiming [Vanderbilt Univ., Nashville, TN (Uni↗