Memlumor : A Luminescent Memory Device for Energy-Efficient Photonic Neuromorphic Computing
(2024) In ACS Energy Letters 9(5). p.2075-2082- Abstract
Neuromorphic computing promises to transform the current paradigm of traditional computing toward non-von Neumann dynamic energy-efficient problem solving. To realize this, a neuromorphic platform must possess intrinsic complexity reflected in the built-in diversity of its physical operation mechanisms. We propose and demonstrate the concept of a memlumor, an all-photonic device combining memory and a luminophore, and being mathematically a full equivalence of the electrically driven memristor. Using CsPbBr3 perovskites as a material platform, we demonstrate the synergetic coexistence of memory effects within a broad time scale from nanoseconds to minutes and switching energy down to 3.5 fJ. We elucidate the origin of such a... (More)
Neuromorphic computing promises to transform the current paradigm of traditional computing toward non-von Neumann dynamic energy-efficient problem solving. To realize this, a neuromorphic platform must possess intrinsic complexity reflected in the built-in diversity of its physical operation mechanisms. We propose and demonstrate the concept of a memlumor, an all-photonic device combining memory and a luminophore, and being mathematically a full equivalence of the electrically driven memristor. Using CsPbBr3 perovskites as a material platform, we demonstrate the synergetic coexistence of memory effects within a broad time scale from nanoseconds to minutes and switching energy down to 3.5 fJ. We elucidate the origin of such a complex response to be related to the phenomena of photodoping and photochemistry activated by a tunable light input. When the existence of a history-dependent photoluminescence quantum yield is leveraged in various material platforms, the memlumor device concept will trigger multiple new research directions in both material science and photonics.
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- author
- Marunchenko, Alexandr LU ; Kumar, Jitendra LU ; Kiligaridis, Alexander LU ; Tatarinov, Dmitry ; Pushkarev, Anatoly ; Vaynzof, Yana and Scheblykin, Ivan G. LU
- organization
- publishing date
- 2024
- type
- Contribution to journal
- publication status
- published
- subject
- in
- ACS Energy Letters
- volume
- 9
- issue
- 5
- pages
- 8 pages
- publisher
- The American Chemical Society (ACS)
- external identifiers
-
- scopus:85190111499
- ISSN
- 2380-8195
- DOI
- 10.1021/acsenergylett.4c00691
- language
- English
- LU publication?
- yes
- id
- 473c47d4-61e7-47d5-afa9-c37ccac1b135
- date added to LUP
- 2024-04-24 14:06:56
- date last changed
- 2024-10-14 11:57:44
@article{473c47d4-61e7-47d5-afa9-c37ccac1b135, abstract = {{<p>Neuromorphic computing promises to transform the current paradigm of traditional computing toward non-von Neumann dynamic energy-efficient problem solving. To realize this, a neuromorphic platform must possess intrinsic complexity reflected in the built-in diversity of its physical operation mechanisms. We propose and demonstrate the concept of a memlumor, an all-photonic device combining memory and a luminophore, and being mathematically a full equivalence of the electrically driven memristor. Using CsPbBr<sub>3</sub> perovskites as a material platform, we demonstrate the synergetic coexistence of memory effects within a broad time scale from nanoseconds to minutes and switching energy down to 3.5 fJ. We elucidate the origin of such a complex response to be related to the phenomena of photodoping and photochemistry activated by a tunable light input. When the existence of a history-dependent photoluminescence quantum yield is leveraged in various material platforms, the memlumor device concept will trigger multiple new research directions in both material science and photonics.</p>}}, author = {{Marunchenko, Alexandr and Kumar, Jitendra and Kiligaridis, Alexander and Tatarinov, Dmitry and Pushkarev, Anatoly and Vaynzof, Yana and Scheblykin, Ivan G.}}, issn = {{2380-8195}}, language = {{eng}}, number = {{5}}, pages = {{2075--2082}}, publisher = {{The American Chemical Society (ACS)}}, series = {{ACS Energy Letters}}, title = {{Memlumor : A Luminescent Memory Device for Energy-Efficient Photonic Neuromorphic Computing}}, url = {{http://dx.doi.org/10.1021/acsenergylett.4c00691}}, doi = {{10.1021/acsenergylett.4c00691}}, volume = {{9}}, year = {{2024}}, }