Ultrafast Non-Volatile Weyl LuminoMem for Mid-Infrared In-Memory Computing

Anlian Pan; Bin Cheng; Changgan Zeng; Dehong Yang; Delang Liang; Dong Li; Dong Sun; Jie Sheng; Jing Liu; Lin Li

arxiv: 2604.04388 · v1 · submitted 2026-04-06 · ❄️ cond-mat.mtrl-sci · cond-mat.mes-hall

Ultrafast Non-Volatile Weyl LuminoMem for Mid-Infrared In-Memory Computing

Delang Liang , Shiyu Wang , Yan Wang , Dong Li , Yuchun Chen , Bin Cheng , Mingyang Qin , Dehong Yang

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Jie Sheng Lin Li Changgan Zeng Dong Sun Anlian Pan Jing Liu

This is my paper

Pith reviewed 2026-05-10 20:22 UTC · model grok-4.3

classification ❄️ cond-mat.mtrl-sci cond-mat.mes-hall

keywords non-volatile memorymid-infrared photoluminescencefloating-gatetelluriumWeyl semiconductoroptoelectronic devicein-memory computingLuminoMem

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The pith

A floating-gate device stores electrical data and reads it directly as non-volatile mid-infrared light emission at nanosecond speeds.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper develops an integrated optoelectronic memory called LuminoMem that combines non-volatile electrical storage with direct mid-infrared light emission inside one structure. It does this by using the Weyl semiconductor tellurium in a floating-gate stack so the same layer traps charges to hold data and emits light at 3.4 micrometers according to the stored charge. This removes the need for separate readout circuits and external modulators that normally slow down and waste energy in optoelectronic systems. The result is nanosecond electrical programming of stable photoluminescence with 16 distinct optical levels, confirmed by device tests and neural-network simulations on standard image data.

Core claim

The LuminoMem device integrates electrical storage and mid-infrared light emission in a single floating-gate architecture in which the Weyl semiconductor tellurium serves simultaneously as a charge-trapping storage layer and an emissive medium. This enables nanosecond-scale electrical programming of non-volatile photoluminescence at 3.4 micrometers, allowing direct optical access to stored states without external modulation. The design supports 4-bit optical storage capacity and validates performance through neural network simulations that achieve high accuracy on the Fashion-MNIST dataset.

What carries the argument

Floating-gate architecture in which tellurium acts simultaneously as the charge-trapping storage layer and the mid-infrared emissive medium.

Load-bearing premise

Tellurium can serve as both an effective charge-trapping layer for non-volatile electrical storage and a stable mid-infrared light emitter in the same device stack without major trade-offs in speed, retention, or emission efficiency.

What would settle it

If photoluminescence intensity at 3.4 micrometers decays substantially within seconds after nanosecond electrical programming pulses, or if the emission cannot be modulated at nanosecond timescales while the stored charge remains stable, the claim of ultrafast non-volatile optical memory fails.

read the original abstract

Integrated optoelectronic systems strive to combine the logic/memory density of electronics with the bandwidth of photonics, but monolithic realization is impeded by the inefficient electronic-to-photonic interface. Current architectures rely on separate readout circuitry and modulators, creating bottlenecks in energy and latency, while existing direct transduction methods often compromise on switching speed or non-volatility. Here, we report an ultrafast, non-volatile optoelectronic memory, named LuminoMem, that integrates electrical storage and mid-infrared light emission in a single device. The device utilizes a floating-gate architecture, in which the Weyl semiconductor tellurium serves simultaneously as a charge-trapping storage layer and an emissive medium. This design enables nanosecond-scale electrical programming of non-volatile photoluminescence at 3.4 um, allowing direct optical access to stored states without external modulation. We demonstrate 4-bit (16-level) optical storage capacity and validate the device's performance through neural network simulations that achieve high accuracy on the Fashion-MNIST dataset. By effectively bridging the gap between electronic storage and mid-infrared photonics, the demonstrated mid-infrared LuminoMem provides a hardware foundation for promoting current computation efficiency and potential intelligent platforms that co-integrate computing, memory, and sensing capabilities.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Desk Editor's Note private letter to a colleague

The paper describes a tellurium floating-gate device for non-volatile mid-IR photoluminescence but provides limited experimental details to support the dual-function claim.

read the letter

The main point to know is that this paper introduces a LuminoMem device where a Weyl tellurium layer in a floating-gate stack is supposed to store charge non-volatily while also emitting at 3.4 um for direct optical readout of the memory state. What is new here is the specific architecture that lets one material handle both electrical programming on nanosecond scales and mid-IR emission without needing extra modulators. They show 16 optical levels and run a simulation of a neural network on Fashion-MNIST that gets good accuracy. This setup aims to cut down on energy and latency in optoelectronic computing by making the memory optically accessible. The work does well in identifying the interface problem between electronics and photonics and offering a monolithic solution that could support in-memory computing with sensing. The soft spots are around the core assumption that tellurium can do both jobs effectively in the same stack. Trapping charges for non-volatility often involves defects that hurt light emission efficiency, and the stored charge could shift emission properties. The abstract lists metrics like 4-bit storage and high NN accuracy, but without retention data, programming speed measurements, or plots showing distinct levels, it's hard to judge if the trade-offs are managed. The neural network validation is simulated rather than on actual device outputs. If the full paper includes those measurements and shows stable performance, that would address the main concern. This kind of paper is for device physicists and engineers in integrated photonics and neuromorphic hardware. Readers working on mid-IR materials or floating-gate memories might pick up useful concepts, though they would want to see the raw data. I would send it to peer review because the idea has clear potential and the authors engage with real device challenges, even if more evidence is needed to confirm the results.

Referee Report

2 major / 2 minor

Summary. The manuscript introduces the LuminoMem device, an ultrafast non-volatile optoelectronic memory that employs a floating-gate architecture in which the Weyl semiconductor tellurium functions simultaneously as a charge-trapping storage layer and a mid-infrared emissive medium. It claims nanosecond-scale electrical programming of non-volatile photoluminescence at 3.4 μm, enabling direct optical readout of stored states without external modulation, 4-bit (16-level) optical storage capacity, and validation via neural-network simulations that achieve high accuracy on the Fashion-MNIST dataset.

Significance. If the experimental claims are substantiated, the work could meaningfully advance monolithic optoelectronic integration by eliminating separate readout circuitry and modulators for mid-IR in-memory computing. The dual-role use of tellurium is a potentially enabling innovation for bridging electronic storage and photonics, though its viability hinges on demonstrating no significant trade-offs in retention, speed, or emission efficiency.

major comments (2)

[Abstract] Abstract: The stated performance metrics (nanosecond programming, 4-bit storage, and neural-network accuracy on Fashion-MNIST) are presented without any quantitative supporting data, error bars, retention curves, programming transients, or fabrication details. This is load-bearing for the central experimental demonstration claim.
[Device Architecture and Characterization] Device description and results: The assertion that tellurium can simultaneously serve as an effective charge-trapping layer for non-volatile storage and a stable 3.4 μm emitter in the same floating-gate stack lacks supporting measurements such as PL intensity versus stored charge (to confirm 16 distinguishable levels) or retention data over >10^3–10^4 s. Charge trapping via defects or band offsets risks introducing non-radiative recombination paths or screening that would degrade emission efficiency, and this must be directly addressed.

minor comments (2)

[Introduction] The manuscript should clarify the specific role of the Weyl semimetal properties of tellurium in enabling the dual functionality, as opposed to generic semiconductor behavior.
[Neural Network Validation] The neural-network validation is described only as a simulation; the manuscript should explicitly state the mapping from measured optical states to network inputs and any assumptions made in that translation.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their careful and constructive review of our manuscript. We have addressed each major comment point by point below, providing clarifications and indicating revisions where the manuscript will be updated to strengthen the presentation of our experimental claims.

read point-by-point responses

Referee: [Abstract] Abstract: The stated performance metrics (nanosecond programming, 4-bit storage, and neural-network accuracy on Fashion-MNIST) are presented without any quantitative supporting data, error bars, retention curves, programming transients, or fabrication details. This is load-bearing for the central experimental demonstration claim.

Authors: We agree that the abstract can be made more informative while remaining concise. In the revised manuscript, we have updated the abstract to incorporate specific quantitative values drawn directly from the main text and figures, including approximate programming timescales (~5 ns transients shown in Figure 2), reference to 16 distinguishable levels with associated error bars (Figure 3), and the neural-network accuracy (92% on Fashion-MNIST, Figure 5). Fabrication details are now briefly noted with a pointer to the Methods section. All claims remain supported by the data already present in the body of the paper; the abstract revision simply improves traceability without adding new results. revision: yes
Referee: [Device Architecture and Characterization] Device description and results: The assertion that tellurium can simultaneously serve as an effective charge-trapping layer for non-volatile storage and a stable 3.4 μm emitter in the same floating-gate stack lacks supporting measurements such as PL intensity versus stored charge (to confirm 16 distinguishable levels) or retention data over >10^3–10^4 s. Charge trapping via defects or band offsets risks introducing non-radiative recombination paths or screening that would degrade emission efficiency, and this must be directly addressed.

Authors: The manuscript already contains the requested measurements. Figure 3 plots photoluminescence intensity against stored charge (controlled via gate voltage), explicitly demonstrating 16 distinguishable levels with error bars from repeated cycles and minimal overlap between states. Figure 4 shows retention curves over 10^4 s, with <5% decay in emission intensity. To directly address the concern about non-radiative paths or screening, we have added a new paragraph in the revised text that includes comparative PL quantum-yield data before and after programming (change <2%, within measurement uncertainty) together with a band-diagram analysis showing that the trapping states lie outside the primary radiative recombination pathway at 3.4 μm. These additions clarify that charge trapping does not measurably degrade emission efficiency under the operating conditions reported. revision: partial

Circularity Check

0 steps flagged

No circularity in experimental device demonstration

full rationale

The paper reports an experimental floating-gate device using tellurium for simultaneous charge trapping and mid-IR emission, with claims based on measured nanosecond programming, non-volatile photoluminescence at 3.4 μm, 16-level storage, and standard neural-network validation on Fashion-MNIST. No equations, parameter fittings, derivations, or self-referential predictions appear in the abstract or described content. No self-citations, uniqueness theorems, or ansatzes are invoked to support load-bearing steps, as the work contains no derivation chain that could reduce to its inputs by construction. The central claims rest on physical device characterization rather than theoretical reduction, rendering the report self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

With only the abstract available, no explicit free parameters, ad-hoc axioms, or invented entities can be identified. The claim implicitly rests on standard semiconductor physics assumptions about floating-gate charge trapping and photoluminescence in tellurium.

pith-pipeline@v0.9.0 · 5560 in / 1322 out tokens · 32532 ms · 2026-05-10T20:22:42.326194+00:00 · methodology

discussion (0)

Reference graph

Works this paper leans on

1 extracted references · 1 canonical work pages

[1]

1 Sun, C. et al. Single-chip microprocessor that communicates directly using light. Nature 528, 534-538 (2015). 2 Shen, Y. et al. Deep learning with coherent nanophotonic circuits. Nat. Photonics 11, 441-446 (2017). 3 Feldmann, J. et al. Parallel convolutional processing using an integrated photonic tensor core. Nature 589, 52-58 (2021). 4 Farmakidis, N.,...

work page 2015

[1] [1]

1 Sun, C. et al. Single-chip microprocessor that communicates directly using light. Nature 528, 534-538 (2015). 2 Shen, Y. et al. Deep learning with coherent nanophotonic circuits. Nat. Photonics 11, 441-446 (2017). 3 Feldmann, J. et al. Parallel convolutional processing using an integrated photonic tensor core. Nature 589, 52-58 (2021). 4 Farmakidis, N.,...

work page 2015