Quantum twist: In a first, magnet-free spin transport achieved in graphene
Special spin currents are a key ingredient in spintronics, a new kind of technology that uses the spin of electrons, instead of electric charge, to carry information. Spintronics promises ultrafast, super energy-efficient devices than today's electronics, but making it work in practical materials like graphene has been difficult.
"In particular, the detection of quantum spin currents in graphene has always required large magnetic fields that are practically impossible to integrate on-chip," said Talieh Ghiasi, lead researcher and a postdoc fellow at Delft University of Technology (TU Delft) in Netherlands.
However, in their latest study, Ghiasi and his team have now shown that by placing graphene on a carefully chosen magnetic material, they can trigger and control quantum spin currents without magnets. This discovery could pave the way for ultrathin, spin-based circuits and help bridge the gap between electronics and future quantum technologies.
To understand what makes this research special, it's pertinent to know that the team was trying to create the quantum spin Hall (QSH) effect. This is a special state where electrons move only along the edges of a material, and their spins point in the same direction.
The motion is smooth and doesn't get scattered by tiny imperfections, a dream scenario for making efficient, low-power circuits. However, until now, making graphene show this effect required applying strong magnetic fields.
Instead of forcing graphene to behave differently with magnets, the researchers took a different approach. They placed a sheet of graphene on top of a layered magnetic material called chromium thiophosphate (CrPS₄). This material naturally influences nearby electrons through what scientists call magnetic proximity effects.
When graphene is stacked on CrPS₄, its electrons start to feel two key forces; spin-orbit coupling (which ties an electron's motion to its spin) and exchange interaction (which favors certain spin directions). These forces open up an energy gap in graphene's structure and lead to the appearance of edge-conducting states, which is a sign of the QSH effect.
The researchers confirmed that spin currents were flowing along the graphene's edges and stayed stable across distances of tens of micrometers, even in the presence of small defects.
They also noticed something unexpected, an anomalous Hall (AH) effect, where electrons are deflected to the side even without an external magnetic field. Unlike the QSH effect, which they observed at low (cryogenic) temperatures, this anomalous behavior persisted even at room temperature.
"The detection of the QSH states at zero external magnetic field, together with the AH signal that persists up to room temperature, opens the route for practical applications of magnetic graphene in quantum spintronic circuitries," the study authors note.
The stable, topologically protected spin currents could be used to transmit quantum information over longer distances, possibly connecting qubits in future quantum computers. They also open the door to ultrathin memory and logic circuits that run cooler and more efficiently than today's silicon-based devices.
"These topologically-protected spin currents are robust against disorders and defects, making them reliable even in imperfect conditions," Ghiasi said.
However, there are still some limitations to overcome. Unlike AH, the QSH effect, which is more suitable for developing quantum circuits, observed here only occurs at very low temperatures, which limits its immediate use in consumer electronics.
The researchers now aim to investigate ways to make the effect more robust at higher temperatures and explore other material combinations where this approach could work.
The study has been published in the journal Nature Communications.
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Proffering Limits And Considerations In the third section, we will amplify some key aspects and provide some important roundups for the strict rules: 'Section 3: Things To Do' ' Teach new concepts: Explain at the user's level, ask guiding questions, use visuals, then review with questions or a practice round.' Explain at the user's level, ask guiding questions, use visuals, then review with questions or a practice round.' ' Help with homework. Don't simply give answers! Start from what the user knows, help fill in the gaps, give the user a chance to respond, and never ask more than one question at a time.' Don't simply give answers! Start from what the user knows, help fill in the gaps, give the user a chance to respond, and never ask more than one question at a time.' ' Practice together. Ask the user to summarize, pepper in little questions, have the user 'explain it back' to you, or role-play (e.g., practice conversations in a different language). Correct mistakes, charitably, and in the moment.' Ask the user to summarize, pepper in little questions, have the user 'explain it back' to you, or role-play (e.g., practice conversations in a different language). Correct mistakes, charitably, and in the moment.' 'Quizzes and test prep: Run practice quizzes. (One question at a time!) Let the user try twice before you reveal answers, then review errors in depth.' It is debatable whether you would really need to include this third section. I say that because the AI probably would have computationally inferred those various points on its own. I'm suggesting that you didn't have to lay out those additional elements, though, by and large, it doesn't hurt to have done so. The issue at hand is that the more you give to the AI in your custom instructions, the more there's a chance that you might say something that confounds the AI or sends it amiss. Usually, less is more. Provide additional indications when it is especially needed, else try to remain tight and succinct, if you can. Tenor Of The AI In the fourth section, we will do some housecleaning and ensure that the AI will be undertaking a pleasant and encouraging tenor: 'Section 4: Tone and Approach' ' Friendly tone . Be warm, patient, and plain-spoken; don't use too many exclamation marks or emojis.' . Be warm, patient, and plain-spoken; don't use too many exclamation marks or emojis.' ' Be conversational . Keep the session moving: always know the next step, and switch or end activities once they've done their job.' . Keep the session moving: always know the next step, and switch or end activities once they've done their job.' 'Be succinct. Be brief, don't ever send essay-length responses. Aim for a good back-and-forth.' The key here is that the AI might wander afield if you don't explicitly tell it how to generally act. 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Again, you could argue that this is somewhat repetitive and that the AI already likely got the drift from the prior sections. The tradeoff exists of making your emphasis clearly known versus going overboard. That's a sensible judgment you need to make when crafting custom instructions. Testing And Improving Once you have devised a set of custom instructions for whatever personal purpose you might have in mind, it would be wise to test them out. Go ahead and put your custom instructions into the AI and proceed to see what happens. In a sense, you should aim to test the instructions, along with debugging them, too. For example, suppose that the above set of instructions seems to get the AI playing a smarmy gambit of not ever answering the user's questions. Ever. It refuses to ultimately provide an answer, even after the user has become exhausted. This seems to be an extreme way to interpret the custom instructions, but it could occur. 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OpenAI provides this via the use of GPTs, which are akin to ChatGPT applets -- you can learn about how to use those in my detailed discussion at the link here and the link here. In my experience, many of the GPTs fail to carefully compose their custom instructions, and likewise seem to have failed or fallen asleep at the wheel in terms of testing their custom instructions. I would strongly advise that you do sufficient testing to believe that your custom instructions work as intended. Please don't be lazy or sloppy. Learning From Seeing And Doing I hope that by exploring the use of custom instructions, you have garnered new insights about how AI works, along with how to compose prompts, and of course, how to devise custom instructions. Your recommended next step would be to put this into practice. Go ahead and log into your preferred AI and play around with custom instructions (if the feature is available and enabled). Do something fun. Do something serious. Become comfortable with the approach. A final thought for now. Per the famous words of Steve Jobs: 'Learn continually -- there's always one more thing to learn.' Keep your spirits up and be a continual learner. You'll be pleased with the results.
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