Cubes on a string: a series of linear coordination polymers with cubane-like nodes and dicarboxylate
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Water resources model development and simulation efforts have seen rapid growth in recent decades to aid evaluations and planning around water scarcity and allocation. Models are typically developed by two distinct communities: (1) large-scale hydrologic modelers emphasizing hydroclimatological processes, and (2) water systems modelers emphasizing environmental, infrastructural, and institutional features that shape water scarcity at the local basin level. This study assesses whether two representative models from these communities produce consistent insights when evaluating the water scarcity vulnerabilities in the Upper Colorado River Basin within the state of Colorado. Results showed that although the regional-scale model [model for scale adaptive river transport (MOSART)—water management (WM)] can capture the aggregate effect of all water operations in the basin, it underestimates the subbasin-scale variability in specific user’s vulnerabilities. The basin-scale water systems model [State of Colorado’s Stream Simulation Model (StateMod)] suggests a larger variance of scarcity across the basin’s water users due to its more detailed accounting of local water allocation infrastructure and institutional processes. This model intercomparison highlights potentially significant limitations of large-scale studies in seeking to evaluate water scarcity and actionable adaptation strategies, as well as ways in which basin-scale water systems model’s information can be used to better inform water allocation and shortage when used in tandem with larger-scale hydrological modeling studies.
Quantum Monte Carlo (QMC) methods are some of the most accurate methods for simulating correlated electronic systems. Here, we investigate the compatibility, strengths, and weaknesses of two such methods, namely, diffusion Monte Carlo (DMC) and auxiliary-field quantum Monte Carlo (AFQMC). The multideterminant trial wave functions employed in both approaches are generated using the configuration interaction using a perturbative selection made iteratively (CIPSI) technique. Complete basis-set full configuration interaction energies estimated with CIPSI are used as a reference in this comparative study between DMC and AFQMC. By focusing on a set of canonical finite–size solid-state systems, we show that both QMC methods can be made to systematically converge towards the same energy once basis-set effects and systematic biases have been removed. AFQMC shows a much smaller dependence on the trial wave function than DMC while simultaneously exhibiting a much larger basis-set dependence. We outline some of the remaining challenges and opportunities for improving these approaches.
We report time reversal symmetry breaking Weyl semimetals are unique among Weyl materials in allowing the minimal number of Weyl points, thus offering the clearest signatures of the associated physics. Here we present neutron diffraction, density-functional theory, and transport measurement results which indicate that EuCd 2 As 2 , under ambient field, strain, and pressure, is such a material with a single pair of Weyl points. Our work reveals a magnetic structure (magnetic space group C2'/m') with Eu moments pointing along the [210] direction in plane and canted ~ 30° out of plane. Density functional theory calculations using this structure show that the observed canting drastically alters the relevant electronic bands, relative to the in-plane order, leading to a single set of well-defined Weyl points. Furthermore, we find the canting angle can tune the distance of the Weyl points above the Fermi level, with the smallest distance at low canting angles. Finally, transport measurements of the anomalous Hall effect and longitudinal magnetoresistance exhibit properties indicative of a chiral anomaly, thus supporting the neutron scattering and DFT results suggesting EuCd 2 As 2 is close to the ideal situation of the Weyl hydrogen atom.
The topological singularity of the Bloch states close to the Fermi level significantly enhances nonlinear electric responses in topological semimetals. Here, we systematically characterize this enhancement for a large class of topological nodal-point fermions, including those with linear, linear-quadratic, and quadratic dispersions. Specifically, we determine the leading power-law dependence of the nonlinear response functions on the chemical potential μ defined relative to the nodal point. We identify two characteristics that qualitatively improve nonlinear transports compared to those of conventional Dirac and Weyl fermions. First, the type-II (overtilted) spectrum leads to the log μ enhancement of nonlinear response functions having zero scaling dimension with respect to μ, which is not seen in a type-I (moderately or not tilted) spectrum. Second, the anisotropic linear-quadratic dispersion increases the power of small-μ divergence for the nonlinear response tensors along the linearly dispersing direction. Furthermore, our work reveals new experimental signatures of unconventional nodal points in topological semimetals as well as provides a guiding principle for giant nonlinear electric responses.
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Weyl semimetal (WSM), a novel state of quantum matter, hosts Weyl fermions as emergent quasiparticles resulting from the breaking of either inversion or time-reversal symmetry. Magnetic WSMs that arise from broken time-reversal symmetry provide an exceptional platform to understand the interplay between magnetic order and Weyl physics, but only a few WSMs have been realized. Here, in this study, we identify CeAlSi as a new noncentrosymmetric magnetic WSM via angle-resolved photoemission spectroscopy (ARPES) and first-principles, density-functional theory based calculations. Our surface-sensitive vacuum ultraviolet ARPES data confirm the presence of surface Fermi arcs as the conclusive evidence for the existence of the Weyl semimetallic state in CeAlSi. We also observe bulk Weyl cones at the Fermi arc terminations in CeAlSi using bulk-sensitive soft-x-ray ARPES measurements. These results implicate CeAlSi as a unique platform for investigating exotic quantum phenomena resulting from the interaction of topology and magnetism.
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High integration rates of new loads and distributed generation at the edge of the grid are posing new challenges. However, existing smart power electronic systems are not designed to coordinate and maximize grid support or provide multiple grid services simultaneously. This work presents the application of a solid-state power substation (SSPS) to residential systems to increase this coordination and reduce future challenges. The proposed residential SSPS is validated in simulation including power electronic converter models, feeder models, and optimization.
Graphene-based interconnects are considered promising replacements for traditional copper (Cu) interconnect due to their great electric properties. In this article, an interconnect-memory co- design framework is developed to efficiently optimize various graphene-based interconnect technologies. Four interconnect materials and heterogeneous design schemes are benchmarked against their traditional Cu counterparts to optimize large cache-level SRAM performance in terms of delay and energy per access, energy-delay product (EDP), and energy-delay-area product (EDAP). Here, a large design space exploration is performed based on realistic subarray design and device technology. Various interconnect- and array-level design parameters are studied to quantify the true potential of graphene-based wires for optimal memory performance.
Integration-technology feature shrink increases computing-system susceptibility to single-event effects (SEE). While modeling SEE faults will be critical, an integrated processor’s scope makes physically correct modeling computationally intractable. Without useful models, presilicon evaluation of fault-tolerance approaches becomes impossible. To incorporate accurate transistor-level effects at a system scope, we present a multiscale simulation framework. Charge collection at the 1) device level determines 2) circuit-level transient duration and state-upset likelihood. Circuit effects, in turn, impact 3) register-transfer-level architecture-state corruption visible at 4) the system level. Furthermore, the physically accurate effects of SEEs in large-scale systems, executed on a high-performance computing (HPC) simulator, could be used to drive cross-layer radiation hardening by design. We demonstrate the capabilities of this model with two case studies. First, we determine a D flip-flop’s sensitivity at the transistor level on 14-nm FinFet technology, validating the model against published cross sections. Second, we track and estimate faults in a microprocessor without interlocked pipelined stages (MIPS) processor for Adams 90% worst case environment in an isotropic space environment.
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