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Researchers from the Low Energy Electronic Systems (LEES) interdisciplinary research group at Singapore-MIT Alliance for Research and Technology (SMART), MIT’s research enterprise in Singapore, together with MIT and National University of Singapore (NUS), have found a method to quantify the distribution of compositional fluctuations in the indium gallium nitride (InGaN) quantum wells at different indium concentrations.
InGaN light emitting diodes (LEDs) have revolutionized the field of solid-state lighting due to their high efficiencies and durability, and low costs. The color of the LED emission can be changed by varying the indium concentration in the InGaN compound, giving InGaN LEDs the potential to cover the entire visible spectrum. InGaN LEDs with relatively low amounts of indium compared to gallium, such as the blue, green, and c
Study finds ride-sharing intensifies urban road congestion
April 26, 2021MIT
Transport network companies (TNCs), or ride-sharing companies, have gained widespread popularity across much of the world, with more and more cities adopting the phenomenon. While ride-sharing has been credited with being more environmentally friendly than taxis and private vehicles, is that really the case today, or do they rather contribute to urban congestion?
Researchers at the Future Urban Mobility (FM) Interdisciplinary Research Group (IRG) at Singapore-MIT Alliance for Research and Technology (SMART), MIT, and Tongji University conducted a study to find out.
Nature Sustainability, the first-of-its-kind study assessed three aspects of how ride-sharing (more accurately called ride-hailing) impacts urban mobility in the United States road congestion, public transport ridership, and private vehicle ownership and how they have evolved over time.
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SMART breakthrough in materials discovery enables twistronics for bulk systems
The findings allow manipulation of materials for the first time by stacking films at a twist angle, allowing a new way to control light emitting from materials
Recent discoveries focused on manipulation of atomically-thin 2D materials, while the new breakthrough can be used to stack technologically-relevant 3D materials at a twist angle
Method allows continuous, systematic control of optical emission intensity and energy, and can produce ultraviolet emissions at room temperature for bulk systems
The discovery can be significant for applications in medicine, environmental or information technologies.
Researchers from the Low Energy Electronic Systems (LEES) Interdisciplinary Research Group (IRG) at Singapore-MIT Alliance for Research and Technology (SMART), MIT’s research enterprise in Singapore together with Massachusetts Institute of Technology (MIT) and National University of Singap
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IMAGE: A comparison summary of deep neural networks (DNNs) and discrete choice models (DCMs) characteristics view more
Credit: Singapore-MIT Alliance for Research and Technology (SMART)
Singapore, 19 April, 2021 - Researchers at the Future Urban Mobility (FM) Interdisciplinary Research Group (IRG) at Singapore-MIT Alliance for Research and Technology (SMART), MIT s research enterprise in Singapore, have created a synthetic framework known as theory-based residual neural network (TB-ResNet), which combines discrete choice models (DCMs) and deep neural networks (DNNs), also known as deep learning, to improve individual decision-making analysis used in travel behaviour research.
In this research paper, Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks, recently published in established transportation science journal