Towards Nanoscale and Element-Specific Lattice Temperature Measurements using Core-Loss Electron Energy-Loss Spectroscopy

Posted by dbos Caltech

Kavli Affiliate: Scott K. Cushing | First 5 Authors: Levi D. Palmer, Wonseok Lee, Javier Fajardo, Jr., A. Alec Talin, Thomas E. Gage | Summary: Measuring nanoscale local temperatures, particularly in vertically integrated and multi-component systems, remains challenging. Spectroscopic techniques like X-ray absorption and core-loss electron energy-loss spectroscopy (EELS) are sensitive to lattice temperature, but […]


Continue.. Towards Nanoscale and Element-Specific Lattice Temperature Measurements using Core-Loss Electron Energy-Loss Spectroscopy

Nanoscale and Element-Specific Lattice Temperature Measurements using Core-Loss Electron Energy-Loss Spectroscopy

Posted by dbos Caltech

Kavli Affiliate: Scott K. Cushing | First 5 Authors: Levi D. Palmer, Wonseok Lee, Daniel B. Durham, Javier Fajardo, Jr., Yuzi Liu | Summary: Measuring nanoscale local temperatures, particularly in vertically integrated and multi-component systems, remains challenging. Spectroscopic techniques like X-ray absorption and core-loss electron energy-loss spectroscopy (EELS) are sensitive to lattice temperature, but understanding […]


Continue.. Nanoscale and Element-Specific Lattice Temperature Measurements using Core-Loss Electron Energy-Loss Spectroscopy

Artificial Intelligence End-to-End Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Posted by dbos Delft

Kavli Affiliate: Giordano Scappucci | First 5 Authors: Marc Botifoll, Ivan Pinto-Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll | Summary: This article introduces a groundbreaking analytical workflow designed for the holistic characterisation, modelling and physical simulation of device heterostructures. Our innovative workflow autonomously, comprehensively and locally characterises the crystallographic information and 3D orientation of the […]


Continue.. Artificial Intelligence End-to-End Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Artificial Intelligence-Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Posted by dbos Delft

Kavli Affiliate: Giordano Scappucci | First 5 Authors: Marc Botifoll, Ivan Pinto-Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll | Summary: (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of devices due to its time-intensive nature. To address this, we introduce […]


Continue.. Artificial Intelligence-Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Artificial Intelligence-Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Posted by dbos Delft

Kavli Affiliate: Giordano Scappucci | First 5 Authors: Marc Botifoll, Ivan Pinto-Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll | Summary: (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of devices due to its time-intensive nature. To address this, we introduce […]


Continue.. Artificial Intelligence-Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Dynamic Competition Between Orbital and Exchange Interactions Selectively Localizes Electrons and Holes Through Polarons

Posted by dbos Caltech

Kavli Affiliate: Scott K. Cushing | First 5 Authors: Jocelyn L. Mendes, Hyun Jun Shin, Jae Yeon Seo, Nara Lee, Young Jai Choi | Summary: Controlling the effects of photoexcited polarons in transition metal oxides can enable the long timescale charge separation necessary for renewable energy applications as well as controlling new quantum phases through […]


Continue.. Dynamic Competition Between Orbital and Exchange Interactions Selectively Localizes Electrons and Holes Through Polarons

Transition Path and Interface Sampling of Stochastic Schrödinger Dynamics

Posted by dbos Berkeley

Kavli Affiliate: David T. Limmer | First 5 Authors: Robson Christie, Peter G. Bolhuis, David T. Limmer, , | Summary: We study rare transitions in Markovian open quantum systems driven with Gaussian noise, applying transition path and interface sampling methods to trajectories generated by stochastic Schr"odinger dynamics. Interface and path sampling offer insights into rare […]


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Orbital-spin Locking and its Optical Signatures in Altermagnets

Posted by dbos Berkeley

Kavli Affiliate: Joel E. Moore | First 5 Authors: Marc Vila, Veronika Sunko, Joel E. Moore, , | Summary: Altermagnets, magnetic materials with zero magnetization and spin-split band structure, have gained tremendous attention recently for their rich physics and potential applications. Here, we report on a microscopic tight-binding model that unveils a unique coupling between […]


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Hybrid cat-transmon architecture for scalable, hardware-efficient quantum error correction

Posted by dbos Caltech

Kavli Affiliate: Oskar Painter | First 5 Authors: Connor T. Hann, Kyungjoo Noh, Harald Putterman, Matthew H. Matheny, Joseph K. Iverson | Summary: Dissipative cat qubits are a promising physical platform for quantum computing, since their large noise bias can enable more hardware-efficient quantum error correction. In this work we theoretically study the long-term prospects […]


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Quantum optimal control of superconducting qubits based on machine-learning characterization

Posted by dbos Berkeley

Kavli Affiliate: Irfan Siddiqi | First 5 Authors: Elie Genois, Noah J. Stevenson, Noah Goss, Irfan Siddiqi, Alexandre Blais | Summary: Implementing fast and high-fidelity quantum operations using open-loop quantum optimal control relies on having an accurate model of the quantum dynamics. Any deviations between this model and the complete dynamics of the device, such […]


Continue.. Quantum optimal control of superconducting qubits based on machine-learning characterization