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Prediction of thermal conductivity in CALF-20 with first-principles accuracy via machine learning interatomic potentials

Understanding the thermal transport properties of CALF-20, a recent addition to the metal-organic framework family, is crucial for its effective utilization in greenhouse gas capture. Here, we report the thermal transport study of CALF-20 using artificial neural network-based machine learning potentials. We use the Green-Kubo approach based on equilibrium molecular dynamics, with a heat-flux renormalization technique, to determine the thermal conductivity (κ) of CALF-20. We predict that the anisotropic thermal transport in CALF-20, with κ below 1 Wm−1K−1 at 300 K, is ideal for thermoelectric applications. Our analysis reveals a weak temperature dependence (κ ~ 1/T0.56) and near invariance with pressure in κ value of CALF-20, which stands out from the typical trend observed in crystalline materials. The outcome of the study, leveraging advanced computational techniques for predictive modeling, offers valuable insights into more suitable applications of CALF-20 with tailored thermal properties.

First-principles study of the magneto-Raman effect in van der Waals layered magnets

Magneto-Raman spectroscopy has been used to study spin-phonon coupling in two-dimensional (2D) magnets. Raman spectra of CrI3 show a strong dependence on the magnetic order within a layer and between the layers. Here we carry out the first systematic theoretical investigation of the magneto-Raman effect in 2D magnets by performing density functional theory calculations and developing a generalized polarizability model. Our first-principles simulations well reproduce experimental Raman spectra of CrI3 with different magnetic states. The model reveals how the change of spin orientation in each layer is coupled to the layer’s vibration to induce or eliminate the spin-dependent anti-symmetric off-diagonal terms in the Raman tensor for altering the selection rules. We also uncover that the correlation between phonon modes and magnetic orders is a universal phenomenon, which should exist in other phonon modes and 2D magnets. Our predictive simulations and modeling are expected to guide the research in 2D magnets.

Suppressed ballistic transport of dislocations at strain rates up to 109 s–1 in a stable nanocrystalline alloy

Dislocations are crucial to plastic deformation in crystals. At extreme strain rates, their motion shifts from thermally activated glide to ballistic transport, causing significant drag due to interactions with phonons, which can lead to embrittlement and failure in metals. The concept of dislons, quantized dislocations, has emerged to better understand these types of interactions. Similar to quantum treatment of dislocation-electron interactions, confining dislocations to nanometer scales, especially in nanocrystalline metals, could also yield unique mechanical behaviors different from bulk materials. Here, we present evidence showing that in Cu-3Ta, a thermo-mechanically stable nanocrystalline alloy, the phonon drag effect is entirely suppressed even at ultra-high strain rates (109 s−1). This is due to the stable confinement of dislocations within several-nanometer range, limiting their velocity and interaction with phonons. Our study indicates that in confined environments, the dislocation-phonon drag effect is minimal, potentially improving material performance under extreme conditions.

Ultrafast pump-probe phase-randomized tomography

Measuring fluctuations in matter’s low-energy excitations is the key to unveiling the nature of the non-equilibrium response of materials. A promising outlook in this respect is offered by spectroscopic methods that address matter fluctuations by exploiting the statistical nature of light-matter interactions with weak few-photon probes. Here we report the first implementation of ultrafast phase randomized tomography, combining pump-probe experiments with quantum optical state tomography, to measure the ultrafast non-equilibrium dynamics in complex materials. Our approach utilizes a time-resolved multimode heterodyne detection scheme with phase-randomized coherent ultrashort laser pulses, overcoming the limitations of phase-stable configurations and enabling a robust reconstruction of the statistical distribution of phase-averaged optical observables. This methodology is validated by measuring the coherent phonon response in α-quartz. By tracking the dynamics of the shot-noise limited photon number distribution of few-photon probes with ultrafast resolution, our results set an upper limit to the non-classical features of phononic state in α-quartz and provide a pathway to access non-equilibrium quantum fluctuations in more complex quantum materials.

Solution-processable 2D materials for monolithic 3D memory-sensing-computing platforms: opportunities and challenges

Solution-processable 2D materials (2DMs) are gaining attention for applications in logic, memory, and sensing devices. This review surveys recent advancements in memristors, transistors, and sensors using 2DMs, focusing on their charge transport mechanisms and integration into silicon CMOS platforms. We highlight key challenges posed by the material’s nanosheet morphology and defect dynamics and discuss future potential for monolithic 3D integration with CMOS technology.

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