Aurelia Butler

As electronic, thermoelectric and computer technologies have been miniaturized to nanometer scale, engineers have faced a challenge studying fundamental properties of the materials involved; in many cases, targets are too small to be observed with optical instruments.
Using cutting-edge electron microscopes and novel techniques, a team of researchers at the University of California, Irvine, the Massachusetts Institute of Technology and other institutions has found a way to map phonons — vibrations in crystal lattices — in atomic resolution, enabling deeper understanding of the way heat travels through quantum dots, engineered nanostructures in electronic components.
To investigate how phonons are scattered by flaws and interfaces in crystals, the researchers probed the dynamic behavior of phonons near a single quantum dot of silicon-germanium using vibrational electron energy loss spectroscopy in a transmission electron microscope, equipment housed in the Irvine Materials Research Institute on the UCI campus. The results of the project are the subject of a paper published today in Nature.
“We developed a novel technique to differentially map phonon momenta with atomic resolution, which enables us to observe nonequilibrium phonons that only exist near the interface,” said co-author Xiaoqing Pan, UCI professor of materials science and engineering and physics, Henry Samueli Endowed Chair in Engineering, and IMRI director. “This work marks a major advance in the field because it’s the first time we have been able to provide direct evidence that the interplay between diffusive and specular reflection largely depends on the detailed atomistic structure.”
According to Pan, at the atomic scale, heat is transported in solid materials as a wave of atoms displaced from their equilibrium position as heat moves away from the thermal source. In crystals, which possess an ordered atomic structure, these waves are called phonons: wave packets of atomic displacements that carry thermal energy equal to their frequency of vibration.
Using an alloy of silicon and germanium, the team was able to study how phonons behave in the disordered environment of the quantum dot, in the interface between the quantum dot and the surrounding silicon, and around the dome-shaped surface of the quantum dot nanostructure itself. More

What’s the relationship between people’s perception of beauty and animals’ conservation needs? According to a machine-learning study by Nicolas Mouquet at the University of Montpellier, France, and colleagues, publishing June 7thin the open-access journal PLOS Biology, the reef fishes that people find most beautiful tend to be the lowest priority for conservation support.
The researchers asked 13,000 members of the public to rate the aesthetic attractiveness of 481 photographs of ray-finned reef fishes in an online survey and used this data to train a convolutional neural network. They then used the trained neural network to generate predictions for additional 4,400 photographs featuring 2,417 of the most encountered reef fish species.
Combining the public’s ratings with the neural network’s predictions, they found that bright, colorful fish species with rounder bodies tended to be rated as the most beautiful. However, the species that were ranked as more attractive tended to be less distinctive in terms of their ecological traits and evolutionary history. Furthermore, species listed on the IUCN Red List as “Threatened” or whose conservation status has not yet been evaluated had lower aesthetic value on average than species categorized as “Least Concern.” Unattractive species were also of greater commercial interest, whereas aesthetic value was not correlated with a species’ importance for subsistence fisheries.
Our innate preferences for shape and color are probably a consequence of the way the human brain processes colors and patterns, the authors say, but mismatches between aesthetic value, ecological function, and extinction vulnerability may mean that the species most in need of public support are the least likely to receive it. The ecological and evolutionary distinctiveness of unattractive fishes makes them important for the functioning of the whole reef, and their loss could have a disproportionate impact on these high-biodiversity ecosystems.
Mouquet adds, “Our study provides, for the first time, the aesthetic value of 2,417 reef fish species. We found that less beautiful fishes are the most ecologically and evolutionary distinct species and those recognized as threatened. Our study highlights likely important mismatches between potential public support for conservation and the species most in need of this support.”
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Electro-optic modulators, which control aspects of light in response to electrical signals, are essential for everything from sensing to metrology and telecommunications. Today, most research into these modulators is focused on applications that take place on chips or within fiber optic systems. But what about optical applications outside the wire and off the chip, like distance sensing in vehicles?
Current technologies to modulate light in free space are bulky, slow, static, or inefficient. Now, researchers at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), in collaboration with researchers at the department of Chemistry at the University of Washington, have developed a compact and tunable electro-optic modulator for free space applications that can modulate light at gigahertz speed.
“Our work is the first step toward a class of free-space electro-optic modulators that provide compact and efficient intensity modulation at gigahertz speed of free-space beams at telecom wavelengths,” said Federico Capasso, Robert L. Wallace Professor of Applied Physics and Vinton Hayes Senior Research Fellow in Electrical Engineering, senior author of the paper.
The research is published in Nature Communications.
Flat, compact metasurfaces are ideal platforms for controlling light in free space but most are static, meaning they can’t switch on and off — a key functionality for modulators. Some active metasurfaces can effectively modulate light, but only at low speeds, just a few megahertz.
For applications such as sensing or free-space communications, you need short, fast bursts of light, on the scale of gigahertz.
The high-speed modulator developed by Capasso and his team brings together metasurface resonators with high-performance organic electro-optical materials and high-frequency electronic design to efficiently modulate the intensity of light in free space.
The modulator consists of a thin layer of an organic electro-optic material deposited on top of a metasurface etched with sub-wavelength resonators integrated with microwave electronics. When a microwave field is applied to the electro-optical material, its refractive index changes, changing the intensity of light that is being transmitted by the metasurface in mere nanoseconds.
“With this design, we now can modulate light 100 to 1,000 times faster than previously,” said Ileana-Cristina Benea-Chelmus, a research associate in the Capasso Lab and first author of the paper. “This speed advance opens new possibilities in computing or communications and the tunability of the metasurface opens up a vast application space for custom-tailored, ultracompact photonics that may in the future be deposited onto any nanoscale free-space optical product.”
Next, the researchers aim to see if they can modulate light even faster and, by changing the design of the metasurface, modulate other aspects of light such as phase or polarization.
The Harvard Office of Technology Development has protected the intellectual property associated with this project.
The research was co-authored by Sydney Mason, Maryna L. Meretska, Dmitry Kazakov, Amirhassan Shams-Ansari from SEAS, and Larry R. Dalton and Delwin Elder of the University of Washington. It was supported in part by the Air Force Office of Scientific Research under award numbers FA9550-19-1-0352 and FA9550-19-1-0069 and the Office of Naval Research (ONR) MURI program, under grant number N00014-20-1-2450. This work was performed in part at the Harvard University Center for Nanoscale Systems (CNS), a member of the National Nanotechnology Coordinated Infrastructure Network (NNCI), which is supported by the National Science Foundation under NSF award no. ECCS-2025158. More

A new theory of economic decision-making from Mina Mahmoudi, a lecturer in the Department of Economics at Rensselaer Polytechnic Institute, offers an explanation as to why humans, in general, make decisions that are simply adequate, not optimal.
In research published today in the Review of Behavioral Economics, Dr. Mahmoudi theorizes an aspect of relative thinking explaining people may use ratios in their decision-making when they should only use absolute differences. The inverse is also possible.
To explain this behavioral anomaly, Dr. Mahmoudi has developed a ratio-difference theory that gives weight to both ratio and difference comparisons. This theory seeks to more accurately capture the manner by which a boundedly rational decision-maker might operationally distinguish whether one alternative is better than another.
“Effectively solving some economic problems requires one to think in terms of differences while others require one to think in terms of ratios,” Dr. Mahmoudi said. “Because both types of thinking are necessary, it is reasonable to think people develop and apply both types. However, it is also reasonable to expect that people misapply the two types of thinking, especially when less experienced with the context.”
Past studies have shown that when given the opportunity to save, for example, $5 on a $25 item or a $500 item, people in general would put in more effort to save the money on the lower-cost product than the more expensive item. They believe they are getting a better deal because the ratio of cost to savings is higher. In fact, the $5 saved is the same for both items and the perfect, or optimal choice, would be to look at the absolute savings and work equally hard to save each $5. People should use differences to solve this problem, but many seem to make unreasonable decisions because they apply ratio thinking.
“Understanding how the cognitive and motivational characteristics of human beings and the operating procedures of organizations influence the working of economic systems is of critical importance,” Dr. Mahmoudi said. “Many economic behaviors such as imitation occur and many economic institutions like inventories exist because people cannot maximize or because markets are not in equilibrium. Our model provides an example of a behavior that occurs because people cannot maximize.”
This model can be applied to a variety of behavioral economic experiments in the gambling industry and financial markets among others.
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Recently, electric vehicles (EVs) are seen everywhere, from passenger cars, buses, to taxis. EVs have the advantage of being eco-friendly and having low maintenance costs; but their owners must remain wary of fatal accidents in case the battery runs out or reaches the end of its life. Therefore, precise capacity and lifespan predictions for the lithium-ion batteries — commonly used in EVs — are vital.
A POSTECH research team led by Professor Seungchul Lee, and Ph.D. candidate Sung Wook Kim (Department of Mechanical Engineering) collaborated with Professor Ki-Yong Oh of Hanyang University to develop a novel artificial intelligence (AI) technology that can accurately predict the capacity and lifespan of lithium-ion batteries. This research breakthrough, which considerably improved the prediction accuracy by merging physical domain knowledge with AI, has recently been published in Applied Energy, an international academic journal in the energy field.
There are two methods of predicting the battery capacity: a physics-based model, which simplifies the intricate internal structure of batteries, and an AI model, which uses the electrical and mechanical responses of batteries. However, the conventional AI model required large amounts of data for training. In addition, when applied to untrained data, its prediction accuracy was very low, which desperately called for the emergence of a next-generation AI technology.
To effectively predict battery capacity with less training data, the research team combined a feature extraction strategy that differs from conventional methods with physical domain knowledge-based neural networks. As a result, the battery prediction accuracy for testing batteries with various capacities and lifespan distributions improved by up to 20%. Its reliability was ensured by confirming the consistency of the results. These outcomes are anticipated to lay the foundation for applying highly dependable physical domain knowledge-based AI to various industries.
Professor Lee of POSTECH remarked, “The limitations of data-based AI have been overcome using physics knowledge. The difficulty of building big data has also been alleviated thanks to the development of the differentiated feature extraction technique.”
Professor Oh of Hanyang University added, “Our research is significant in that it will contribute in propagating EVs to the public by enabling accurate predictions of remaining lifespan of batteries in next-generational EVs.”
This study was supported by the Institute of Civil Military Technology Cooperation and the National Research Foundation of Korea.
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Sensors are a constant feature of our everyday lives. Although they often go unperceived, sensors provide critical information essential to modern healthcare, security, and environmental monitoring. Modern cars alone contain over 100 sensors and this number will only increase.
Quantum sensing is poised to revolutionise today’s sensors, significantly boosting the performance they can achieve. More precise, faster, and reliable measurements of physical quantities can have a transformative effect on every area of science and technology, including our daily lives.
However, the majority of quantum sensing schemes rely on special entangled or squeezed states of light or matter that are hard to generate and detect. This is a major obstacle to harnessing the full power of quantum-limited sensors and deploying them in real-world scenarios.
In a paper published today, a team of physicists at the Universities of Bristol, Bath and Warwick have shown it is possible to perform high precision measurements of important physical properties without the need for sophisticated quantum states of light and detection schemes.
The key to this breakthrough is the use of ring resonators — tiny racetrack structures that guide light in a loop and maximize its interaction with the sample under study. Importantly, ring resonators can be mass manufactured using the same processes as the chips in our computers and smartphones.
Alex Belsley, Quantum Engineering Technology Labs (QET Labs) PhD student and lead author of the work, said: “We are one step closer to all integrated photonic sensors operating at the limits of detection imposed by quantum mechanics.”
Employing this technology to sense absorption or refractive index changes can be used to identify and characterise a wide range of materials and biochemical samples, with topical applications from monitoring greenhouse gases to cancer detection.
Associate Professor Jonathan Matthews, co-Director of QET Labs and co-author of the work, stated: “We are really excited by the opportunities this result enables: we now know how to use mass manufacturable processes to engineer chip scale photonic sensors that operate at the quantum limit.”
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Researchers at the Niels Bohr Institute, University of Copenhagen, have improved the coherence time of a previously developed quantum membrane dramatically. The improvement will expand the usability of the membrane for a variety of different purposes. With a coherence time of one hundred milliseconds, the membrane can for example store sensitive quantum information for further processing in a quantum computer or network. The result has now been published in Nature Communications.
The quantum drum is now connected to a read-out unit
As a first step, the team of researchers has combined the membrane with a superconducting microwave circuit, which enables precise readouts from the membrane. That is, it has become “plugged in,” as required for virtually any application. With this development, the membrane can be connected to various other devices that process or transmit quantum information.
Cooling the quantum drum system to reach quantum ground state
Since the temperature of the environment determines the level of random forces disturbing the membrane, it is imperative to reach a sufficiently low temperature to prevent the quantum state of motion from being washed out. The researchers achieve this by means of a helium-based refrigerator. With the help of the microwave circuit, they can then control the quantum state of the membrane motion. In their recent work, the researchers could prepare the membrane in the quantum ground state, meaning that its motion is dominated by quantum fluctuations. The quantum ground state corresponds to an effective temperature of 0,00005 degrees above the absolute zero, which is −273.15 °C.
Applications for the plugged in quantum membrane are many
One could use a slightly modified version of this system that can feel forces from both microwave and optical signals to build a quantum transducer from microwave to optics. Quantum information can be transported at room temperature in optical fibers on kilometers without perturbations. On the other hand, the information is typically processed inside a cooling unit, capable of reaching sufficiently low temperatures for superconducting circuits like the membrane to operate. Connecting these two systems — superconducting circuits to optical fibers — could therefore enable the construction of a quantum internet: several quantum computers linked together with optical fibers. No computers have infinite space, so the possibility of distributing computational capabilities to connected quantum computers, would greatly enhance the capacity to solve complicated problems.
Gravity — not well understood in quantum mechanics, but crucial — can now be explored
The role of gravity in the quantum regime is a yet unanswered, fundamental question in physics. This is yet another place where the high coherence time of the membranes demonstrated here may be applied for study. One hypothesis in this area is that gravity has the potential to destroy some quantum states with time. With a device as big as the membrane, such hypotheses may be tested in the future.
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Photonics researchers have introduced a novel method to control a light beam with another beam through a unique plasmonic metasurface in a linear medium at ultra-low power. This simple linear switching method makes nanophotonic devices such as optical computing and communication systems more sustainable requiring low intensity of light.
All-optical switching is the modulation of signal light due to control light in such a way that it possesses the ON/OFF conversion function. In general, a light beam can be modulated with another intense laser beam in the presence of a nonlinear medium.
The switching method developed by the researchers is fundamentally based on the quantum optical phenomenon known as Enhancementof Index of Refraction (EIR).
“Our work is the first experimental demonstration of this effect on the optical system and its utilization for linear all-optical switching. The research also enlightens the scientific community to achieve loss-compensated plasmonic devices operating at resonance frequencies through extraordinary enhancement of refractive index without using any gain media or nonlinear processes,” says Humeyra Caglayan, Associate Professor (tenure track) in Photonics at Tampere University.
Optical switching enabled with ultrafast speed
High-speed switching and low-loss medium to avoid the strong dissipation of signal during propagation are the basis to develop integrated photonic technology where photons are utilized as information carriers instead of electrons. To realize on-chip ultrafast all-optical switch networks and photonic central processing units, all-optical switching must have ultrafast switching time, ultralow threshold control power, ultrahigh switching efficiency, and nanoscale feature size. More