Author: Patricia DeLacey
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Organic glass scintillators: A Q&A with Sara Pozzi
The radiation detection material stands to improve nuclear security by clearly distinguishing radiation types from a safe distance.
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Better helium reporting to improve fission and fusion materials modeling
Helium generation predictions vary by as much as 200%, a new standardized reporting method can help move the field forward.
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Key structures to metallic glass stability revealed with machine learning
Using the second-nearest neighboring atoms to predict metallic glass stability can help researchers more accurately model the disordered solid with strong, elastic properties.
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Modeling particles reveals soil density impact on surface fault ruptures
The discrete element method models tens of millions of distinct particles to help understand this rare earthquake hazard and inform resilient civil engineering design.
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Ultrashort laser pulses achieve stronger photoemission
A new theoretical study finds shorter laser pulses achieve higher quantum efficiency for photoemission from a solid surface without increasing power or intensity.
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A hardware-software co-design to efficiently run AI on edge devices
Adjusting state space models to work with a compute-in-memory architecture demonstrated energy-efficient processing of continuous event sequences.
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Fine-tuning nanoscale heat flows in molecular materials
Researchers demonstrate how swapping out a single atom can cut the thermal conductance in half without changing electrical properties.
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A color-changing phosphor for encoding information
Applying heat or a solvent makes a new purely organic phosphor reversibly switch between glowing green and blue at room temperature.
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Memristor demonstrates use in fully analog hardware-based neural network
The crossbar array memristor made of bismuth selenide (Bi2Se3) sandwiched between gold and titanium electrodes is analog tunable, retention stable and regulator-free in circuit
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Model incorporates anisotropic conductivity to improve thin film devices
The new framework replaces approximations, accurately modeling current crowding and spreading resistance in 2D materials to improve high-performance semiconductor devices.
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Letting atomic simulations learn from phase diagrams
Ten times more efficient than previous methods, a new machine learning method builds a two-way connection between atomic simulation and experimental data.
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A manual for efficient wave energy converter prototyping
An open-source, standardized methodology aims to streamline efforts to design small-scale wave energy converters, moving closer to harnessing offshore renewables.