Rewritable Complementary Nanoelectronics Enabled by Electron-Beam Programmable Ambipolar Doping

Kavli Affiliate: Alex Zettl | Summary:The ability to reversibly and site-selectively tune ambipolar doping in a single semiconductor is crucial for reconfigurable electronics beyond silicon, but remains highly challenging. Here, we present a rewritable architecture based on electron-beam programmable field-effect transistors (FETs). Using WSe$_2$ as a model system, we demonstrate electron-beam-induced doping that enables reversible, […]


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Spin Polarization from Circularly Polarized Light Induced Charge Transfer

Kavli Affiliate: David T. Limmer | Summary:We show how a spin polarization can be generated through the photo-induced electron transfer of an achiral donor-acceptor complex following chiral light excitation. In particular, we illustrate the basic energetic and symmetry requirements for chirality induced spin selectivity where the chirality emerges from the electronic degrees of freedom following […]


Continue.. Spin Polarization from Circularly Polarized Light Induced Charge Transfer

Spin Polarization from Circularly Polarized Light Induced Charge Transfer

Kavli Affiliate: David T. Limmer | Summary:We show how a spin polarization can be generated through the photo-induced electron transfer of an achiral donor-acceptor complex following chiral light excitation. In particular, we illustrate the basic energetic and symmetry requirements for chirality induced spin selectivity where the chirality emerges from the electronic degrees of freedom following […]


Continue.. Spin Polarization from Circularly Polarized Light Induced Charge Transfer

Uncovering Students’ Inquiry Patterns in GenAI-Supported Clinical Practice: An Integration of Epistemic Network Analysis and Sequential Pattern Mining

Kavli Affiliate: Joel Moore | Summary:Assessment of medication history-taking has traditionally relied on human observation, limiting scalability and detailed performance data. While Generative AI (GenAI) platforms enable extensive data collection and learning analytics provide powerful methods for analyzing educational traces, these approaches remain largely underexplored in pharmacy clinical training. This study addresses this gap by […]


Continue.. Uncovering Students’ Inquiry Patterns in GenAI-Supported Clinical Practice: An Integration of Epistemic Network Analysis and Sequential Pattern Mining

Generative Models for Crystalline Materials

Kavli Affiliate: Gerbrand Ceder| Summary:Understanding structure-property relationships in materials is fundamental in condensed matter physics and materials science. Over the past few years, machine learning (ML) has emerged as a powerful tool for advancing this understanding and accelerating materials discovery. Early ML approaches primarily focused on constructing and screening large material spaces to identify promising […]


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AI4X Roadmap: Artificial Intelligence for the advancement of scientific pursuit and its future directions

Kavli Affiliate: Kristin Persson | Summary:Artificial intelligence and machine learning are reshaping how we approach scientific discovery, not by replacing established methods but by extending what researchers can probe, predict, and design. In this roadmap we provide a forward-looking view of AI-enabled science across biology, chemistry, climate science, mathematics, materials science, physics, self-driving laboratories and […]


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Hierarchical high-throughput screening of alkaline-stable lithium-ion conductors combining machine learning and first-principles calculations

Kavli Affiliate: Gerbrand Ceder| Summary:The advancement of solid-state batteries depends on the development of lithium-ion conductors that exhibit both high ionic conductivity and stability across a wide range of electrochemical and chemical conditions. In this paper, we investigate the chemical factors that control the stability of Li-NASICONs and garnets in highly alkaline aqueous environment. While […]


Continue.. Hierarchical high-throughput screening of alkaline-stable lithium-ion conductors combining machine learning and first-principles calculations

Hierarchical high-throughput screening of alkaline-stable lithium-ion conductors combining machine learning and first-principles calculations

Kavli Affiliate: Gerbrand Ceder| Summary:Solid-state batteries require lithium-ion conductors that combine high ionic conductivity with stability under harsh electrochemical and chemical conditions. Here, we investigate the chemical factors governing the stability of NASICON-type and garnet-type Li-ion conductors in highly alkaline environments. This is particularly relevant to solid-state Li-air cells operated under humidified air where alkaline […]


Continue.. Hierarchical high-throughput screening of alkaline-stable lithium-ion conductors combining machine learning and first-principles calculations

Topological BF Theory construction of twisted dihedral quantum double phases from spontaneous symmetry breaking

Kavli Affiliate: Joel Moore | Summary:Nonabelian topological orders host exotic anyons central to quantum computing, yet established realizations rely on case-by-case constructions that are often conceptually involved. In this work, we present a systematic construction of nonabelian dihedral quantum double phases based on a continuous $O(2)$ gauge field. We first formulate a topological $S[O(2)times O(2)]$ […]


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High-throughput computation of electric polarization in solids via Berry flux diagonalization

Kavli Affiliate: Jeffrey Neaton | Summary:Electric polarization in the absence of an externally applied electric field is a key property of polar materials, but the standard interpolation-based ab initio approach to compute polarization differences within the modern theory of polarization presents challenges for automated high-throughput calculations. Berry flux diagonalization [J. Bonini et. al, Phys. Rev. […]


Continue.. High-throughput computation of electric polarization in solids via Berry flux diagonalization