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Revolutionizing Electronics: The 2D Twist That Defied Scientific Predictions

Scientists are exploring 2D materials — sheets just one atom thick — with unique and promising electronic properties.

When two of these sheets are layered at specific angles, they can exhibit remarkable behaviors, such as superconductivity. Antonija Grubišić-Čabo, a materials scientist at the University of Groningen, and her colleagues investigated one such “twisted” material and found that it behaved in ways that defied existing theoretical predictions.

2D Materials and Superconductivity.

Scientists Warn Against Creation of Mirror Life That May Cause an Extinction

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Hello and welcome! My name is Anton and in this video, we will talk about the potential dangers of mirror life.
Links:

https://theconversation.com/mirror-life-forms-may-sound-like…ent-246013
https://www.nature.com/articles/s41565-024-01627-z.
https://www.nature.com/articles/s41557-023-01411-x.
Previous videos:


https://youtu.be/0MRGJNKACYs.
https://youtu.be/L1wkR-92Rys.
#chirality #biology #mirrorlife.

0:00 Mirror life?
0:40 Chirality and handedness of molecules and why it’s important.
2:40 Recent advances in biochemistry.
3:45 New technical report warns science.
4:50 All life is handed.
6:00 What this could do in theory.
7:45 Conclusions and additional propositions.

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Some doctors increasingly using artificial intelligence to take notes during appointments

It was easy to miss Dr. Robert Gray’s quick movements, tapping the screen of his smartphone at the beginning and end of patient visits on a recent day.

But Gray said those fast finger taps have changed his life. He was tapping an app that records discussions during his appointments and then uses to find the relevant information, summarize it and zap it, within seconds, into each patient’s electronic medical record.

The technology was meticulously documenting each visit so Gray didn’t have to.

Hydrogels for active photonics

Conventional photonic devices exhibit static optical properties that are design-dependent, including the material’s refractive index and geometrical parameters. However, they still possess attractive optical responses for applications and are already exploited in devices across various fields. Hydrogel photonics has emerged as a promising solution in the field of active photonics by providing primarily deformable geometric parameters in response to external stimuli. Over the past few years, various studies have been undertaken to attain stimuli-responsive photonic devices with tunable optical properties. Herein, we focus on the recent advancements in hydrogel-based photonics and micro/nanofabrication techniques for hydrogels. In particular, fabrication techniques for hydrogel photonic devices are categorized into film growth, photolithography (PL), electron-beam lithography (EBL), and nanoimprint lithography (NIL). Furthermore, we provide insights into future directions and prospects for deformable hydrogel photonics, along with their potential practical applications.


Microsystems & Nanoengineering volume 10, Article number: 1 (2024) Cite this article.

Achieving bone regeneration and adhesion with harmless visible light

Oregon State University researchers have found luminescent nanocrystals with fast light-dark switching capabilities.

“The extraordinary switching and memory capabilities of these nanocrystals may one day become integral to optical computing – a way to rapidly process and store information using light particles, which travel faster than anything in the universe,” said Artiom Skripka, assistant professor in the OSU College of Science.


The race for faster, more efficient computing is on. And now, scientists have taken a significant leap forward with the discovery of a unique type of nanocrystal.

This has the potential to accelerate artificial intelligence and data processing speed, while also enhancing energy efficiency.

Integrated spin wave storage advances quantum networks

The University of Science and Technology of China has achieved a significant milestone in quantum memory research, addressing a long-standing challenge in integrated solid-state devices. The team, led by Chuan-Feng Li and Zong-Quan Zhou, has demonstrated an integrated spin-wave quantum memory capable of extended storage times and on-demand retrieval. This development marks a critical step toward scalable quantum networks.

Quantum memories play a pivotal role in enabling long-distance entanglement by linking short-distance connections, overcoming photon transmission losses. Rare-earth ions doped crystals have emerged as promising systems for quantum memory, with integrated solid-state devices showing particular potential. However, prior implementations were limited to optically excited states, which inherently restrict storage time and retrieval flexibility due to the short lifetime of these states.

The breakthrough lies in the implementation of spin-wave storage. This approach encodes photons into spin-wave excitations in ground states, vastly extending storage times to the spin coherence lifetime and enabling on-demand retrieval. Nevertheless, the challenge of separating single-photon signals from noise caused by strong control pulses has hindered progress in integrated structures — until now.

A quantum walk simulation of extra dimensions with warped geometry

We investigate the properties of a quantum walk which can simulate the behavior of a spin 1/2 particle in a model with an ordinary spatial dimension, and one extra dimension with warped geometry between two branes. Such a setup constitutes a \(1+1\) dimensional version of the Randall–Sundrum model, which plays an important role in high energy physics. In the continuum spacetime limit, the quantum walk reproduces the Dirac equation corresponding to the model, which allows to anticipate some of the properties that can be reproduced by the quantum walk. In particular, we observe that the probability distribution becomes, at large time steps, concentrated near the “low energy” brane, and can be approximated as the lowest eigenstate of the continuum Hamiltonian that is compatible with the symmetries of the model. In this way, we obtain a localization effect whose strength is controlled by a warp coefficient. In other words, here localization arises from the geometry of the model, at variance with the usual effect that is originated from random irregularities, as in Anderson localization. In summary, we establish an interesting correspondence between a high energy physics model and localization in quantum walks.


Anglés-Castillo, A., Pérez, A. A quantum walk simulation of extra dimensions with warped geometry. Sci Rep 12, 1926 (2022). https://doi.org/10.1038/s41598-022-05673-2

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A3ML: Anticipatory and Adaptive Anti-Money Laundering

DARPA seeks to revolutionize the practice of anti-money laundering through its A3ML program. A3ML aims to develop algorithms to sift through financial transactions graphs for suspicious patterns, learn new patterns to anticipate future activities, and develop techniques to represent patterns of illicit financial behavior in a concise, machine-readable format that is also easily understood by human analysts. The program’s success hinges on algorithms’ ability to learn a precise representation of how bad actors move money around the world without sharing sensitive data.


DARPA wants to eliminate global money laundering by replacing the current manual, reactive, and expensive analytic practices with agile, algorithmic methods.

Money laundering directly harms American citizens and global interests. Half of North Korea’s nuclear program is funded by laundered funds, according to statements by the White House1, while a federal indictment alleges that money launderers tied to Chinese underground banking are a primary source of financial services for Mexico’s Sinaloa cartel 2.

Despite recent anti-money laundering efforts, the United States (U.S.) still faces challenges in countering money laundering effectively for several reasons. According to Congressional research, money laundering schemes often evade detection and disruption, as anti-money laundering (AML) efforts today rely on manual analysis of large amounts of data and are limited by finite resources and human cognitive processing speed3.