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REVIEW 5 major objections 5 minor 1 references

Wettability and Color Change of Copper by Controlling Area Fraction of Laser Ablated Surface

T0 review · 5 major / 5 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read Laser-ablated area fraction is a single control parameter that programs both the water contact angle and the color of copper surfaces.

desk verdict Likely real experimental trend, but the central 'ablated area fraction' is inverted in Eq. (7), so the paper's quantitative claims don't stand as written. read the letter →

arxiv 2411.17324 v2 pith:M6YK2XTE submitted 2024-11-26 physics.optics cond-mat.mtrl-sciphysics.app-phphysics.comp-ph

Mantas Gaidys , Stella Maragkaki , Alexandros Mimidis , Antonis Papadopoulos , Andreas Lemonis , Evangelos Skoulas , Andrius Žemaitis , Emmanuel Stratakis
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Mindaugas Gedvilas
This is my paper · ORCID
classification physics.opticscond-mat.mtrl-sciphysics.app-phphysics.comp-ph
keywords super-hydrophobichighly-hydrophilicareafractioncopperlaserablationsurfaceroughnesscolorchangewettability
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

The paper reports that the fraction of a copper surface removed by laser ablation is a single control parameter for two surface properties at once: wettability and color. By scanning nanosecond and picosecond pulses over a fluence range from 0.16 to 9.6 J/cm², the water contact angle could be set from almost 0° to 132°, and the paper describes this as running from highly hydrophilic to super-hydrophobic behavior. The same area fraction produced linear changes in color distance, average gray value, and gray luminance, so the surface's optical appearance tracks its wetting state. The contact-angle data are interpreted with Cassie, Cassie-Baxter, and combined Wenzel-Cassie-Baxter models, which reproduce the decrease in contact angle as the ablated share grows.

What carries the argument

The load-bearing object is the ablated area fraction $f_1$, defined as the share of pixels in a microscope image whose gray value falls below the threshold $GV_{th}=0.48$ after the color-to-gray 'value' conversion $GV=\max(R,G,B)$. The threshold is chosen as the midpoint between the average gray value of untreated copper ($0.89$) and copper ablated at maximum fluence ($0.062$). Around this quantity the paper builds monotonic and linear relations for contact angle, color distance, gray value, and gray luminance; on the modeling side, the contact-angle relation is carried by the Cassie equation for heterogeneous surfaces, the Cassie-Baxter equation for surfaces with trapped air, and the combined Wenzel-Cassie-Baxter equation that multiplies a roughness factor $r_1$ into the heterogeneous-surface formula.

What would settle it

Recompute every area fraction from the same microscope images using thresholds of, say, 0.30 and 0.65; if the contact-angle-versus-$f_1$ curves become non-monotonic or the picosecond and nanosecond data separate, the claim that $f_1$ is the control variable is falsified. A stronger check is to measure the ablated area directly on the same samples by profilometry or scanning-electron microscopy and compare with the threshold-segmented $f_1$; a large mismatch would show the reported fractions are an artifact of the chosen gray-level cut.

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Extended reading notes

Core claim

The central claim is that the laser-ablated area fraction $f_1$ is the organizing variable for laser-textured copper: increasing $f_1$ from essentially 0% to near 100% lowers the static water contact angle from 132° to almost 0° for both 10 ns and 10 ps pulses, while color distance rises linearly and gray value and luminance fall linearly. The paper establishes this by texturing 15 sites at different fluences, imaging each with an optical microscope, converting images to grayscale with the value method, and segmenting them into ablated and unablated pixels using a fixed threshold $GV_{th}=0.48$ that is the midpoint between untreated copper (average $GV=0.89$) and maximally ablated copper (average $GV=0.062$). The fitted Cassie model uses contact angles $\theta_1=0^\circ$ and $\theta_2=129^\circ$, and the combined Wenzel-Cassie-Baxter model uses $\theta_1=4^\circ$, $\theta_2=98^\circ$, and roughness factor $r_1=1.01$; the data agree well, especially for picosecond pulses. The paper presents this as the first demonstration that wettability and color of copper are controlled together through the area fraction of the ablated surface.

Load-bearing premise

Every reported area fraction comes from calling a pixel 'ablated' when its gray value falls below 0.48, which is simply the midpoint between the average gray values of untreated and maximally ablated copper; if that threshold does not mark the true physical edge of the ablated regions, all $f_1$ values and the fitted wetting and color laws shift.

Editorial extensions

If this is right

  • A copper heat exchanger or cooling surface can be given a chosen wetting state, from fully spreading to a 132° droplet, in a single laser pass without chemical treatment.
  • Because color distance, gray value, and luminance are linear functions of $f_1$, the color of a textured copper part can serve as an immediate, non-contact check of its wetting state during production.
  • The fitted Cassie, Cassie-Baxter, and Wenzel-Cassie-Baxter curves give a design rule: choose the target contact angle, read off the required ablated area fraction, and set the laser fluence accordingly.
  • The same scanned-beam, chemical-free process is scalable to large areas and complex shapes, which is the paper's stated route toward atmospheric water generators, fog harvesting, power plants, and solar thermal water systems.
  • Picosecond pulses reach the same wettability range with much smaller roughness and profile arc length than nanosecond pulses, so pulse duration can be chosen for surface finish rather than for the achievable wetting range.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The paper's logic implies that two surfaces with the same measured $f_1$ but different pulse durations should show the same contact angle; the data are consistent with that but it is not directly tested.
  • Because $f_1$ rests on a fixed gray threshold, the fitted numbers are protocol-bound; transferring them to a different microscope would require recalibrating the threshold, although the monotonic control by ablated share should remain.
  • A testable extension would be to apply the same area-fraction framework to other laser-texturable metals or to copper with different surface chemistry; the paper demonstrates the effect only on 99.9% pure copper.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

5 major / 5 minor

Summary. The manuscript reports a single-step laser texturing method for copper using nanosecond and picosecond pulses, in which the laser fluence is varied to create arrays of ablated dimples. The authors quantify the laser-ablated area fraction f1 by thresholding optical microscope grayscale images, measure the water contact angle, color distance, grayscale value, luminance, and surface roughness, and report that the contact angle decreases and the color changes linearly as f1 increases. They fit the contact-angle data with the Cassie, Cassie-Baxter, and combined Cassie-Baxter/Wenzel models and claim full wettability control from nearly 0° to 132°, including an asserted super-hydrophobic regime. The central experimental observation — that higher laser fluence produces darker, more hydrophilic, and color-changed copper surfaces — is plausible from the presented images and measurements, but the paper's quantitative definition of the area fraction is internally inconsistent as written, and several reported statements are mutually contradictory.

Significance. If the reported effect is real and reproducible, the work offers a practical, chemical-free route to program both wettability and color on copper in a single laser pass, which could be relevant for heat-transfer surfaces, atmospheric water generators, and fog-harvesting devices. The strength of the paper is its systematic variation of laser fluence with direct measurement of water contact angle, color, roughness, and thresholded area fraction, together with a clear attempt to interpret the data through classical wetting models. However, the quantitative claim of control by area fraction is currently not reproducible because the binarization equation as printed assigns the opposite polarity from the one used in the reported f1 values, and the model fits use parameters taken from the same dataset they are supposed to validate. The abstract's 'super-hydrophobic' claim is also not supported by the maximum measured angle of 132°.

major comments (5)
  1. [§4.1, Eqs. (7)-(8)] As printed, Eq. (7) sets BW = 1 when GV ≥ GVth and BW = 0 when GV < GVth. With GVth = 0.48, untreated copper (⟨GV⟩ = 0.89) therefore gives BW = 1 everywhere, which by Eq. (8) yields f1 = 100%, while maximally ablated copper (⟨GV⟩ = 0.062) gives f1 = 0%. This is the opposite of the reported trend, where f1 is the ablated area fraction and increases with fluence (Fig. 5(d), Fig. S3(b)). The quantity defined by Eqs. (7)-(8) is the fraction of bright, unablated surface, not the ablated fraction. This affects every f1 value, the color correlations, and all model parameters in Table 1. The authors must either invert the inequality in Eq. (7) or explicitly redefine f1 as the unablated fraction and invert the axes of Figs. 5-6 accordingly.
  2. [§4.2, Eq. (10)] The threshold GVth = 0.48 is defined as the midpoint between the average grayscale values of untreated copper and maximally ablated copper, with no independent calibration or validation. Since all f1 values, the fitted models in Fig. 6(a), and the linear color correlations depend on this single threshold, the quantitative claims are sensitive to an arbitrary convention. The authors should provide a sensitivity analysis showing how f1 and the fitted parameters change for a range of physically reasonable threshold values, or otherwise justify that the threshold identifies the laser-damaged surface independently of the endpoint images used to define it.
  3. [Abstract and §5.1, Fig. 6(a)] The abstract and conclusions describe the surfaces as 'super-hydrophobic', but the maximum reported contact angle is 132°, which is below the 150° threshold the paper itself uses in §2 for super-hydrophobicity. The measured range is from nearly 0° to 132°, which is a wide and useful hydrophilic-to-hydrophobic range, but it is not a super-hydrophobic range. The wording should be corrected to avoid overclaiming the result.
  4. [§5.1, Table 1 and Fig. 6(a)] The claimed 'good agreement' between the theoretical curves and the experimental data in Fig. 6(a) is partly built into the fits: the Cassie model parameters θ1 = 0° and θ2 = 129° are taken from the minimum and maximum measured contact angles in the same dataset, and the combined model uses θ1 = 4°, θ2 = 98°, and r1 = 1.01, with the latter also drawn from the same dataset. Agreement between a curve and the endpoints used to fix its parameters is not an independent validation. The authors should present the fits with parameter uncertainties and, ideally, test the models on an independent dataset or report the prediction errors rather than only the curve agreement.
  5. [§5.1, paragraph on r1] The statement that the normalized profile arc length r1 for picosecond pulses is 'more than 100 times smaller' than for nanosecond pulses is physically implausible as written, since r1 is a ratio of actual to projected profile length and is close to 1 in both cases (e.g., Fig. S5(a) shows ns values around 1.2 and ps values near 1.0). A factor-of-100 difference would require a nanosecond profile arc length of order 100, which is not observed. The authors likely mean that the deviation of r1 from 1 is about 100 times smaller for ps than for ns, or that the roughness is about 10 times smaller, and the text should be corrected accordingly.
minor comments (5)
  1. [Fig. 5 caption] The fluence labels contain apparent typos: '(iv) 0.128 J/cm2' is likely 1.28 J/cm2, and the list '(vii) 0.32 J/cm2 (viii) 0.48 J/cm2 (ix) 0.64 J/cm2 (x) 0.80 J/cm2 (xi) 8.0 J/cm2' should be checked for consistency with the power settings in §3.2.
  2. [Eq. (11)] The NTSC luminance formula is written as GL = 0.3R + 0.59R + 0.11B, but the second coefficient should apply to the green channel, i.e., GL = 0.3R + 0.59G + 0.11B.
  3. [§5.1, paragraph after Fig. 5(d)] The sentence stating that grayscale luminance ⟨GL⟩, grayscale value ⟨GV⟩, and color distance ⟨CD⟩ 'increased linearly with increasing peak laser fluence' conflicts with Fig. 6(c)-(d), where gray value and gray luminance decrease with increasing ablated area fraction. The direction of each correlation should be stated consistently.
  4. [Fig. 6 and §5.2] The linear fit equations use gray value and luminance on a 0-100 or 0-255 scale (e.g., GV = 91.3 - 0.79 f1), while earlier equations and figure labels give ⟨GV⟩ as a normalized value around 0.89. The units of these quantities should be defined consistently so that the fitted coefficients are reproducible.
  5. [Eq. (5)] The displayed formula for the normalized profile arc length is garbled in the text; it should be typeset as r1 = (1/Δx) ∫ sqrt(1 + (dh/dx)^2) dx so that the ratio of actual profile length to projected length is unambiguous.

Circularity Check

2 steps flagged · score 4.0 of 10

GV–f1 correlation and endpoint-fitted wetting models are partly self-constructed; the central wetting claim remains independently measured.

  1. self definitional [Sec. 4.1 Eqs. (6)-(8) and Sec. 5.2 linear fit after Fig. 6(c)]
    "the image was transformed to the grayscale mode by calculating the grayscale value GV using the formula GV = max(R,G,B) ... grayscale pictures were converted to black-and-white binary mode by using a certain threshold value GVth using formula: BW = 1, if GV >= GVth; 0, if GV < GVth ... area fraction f1 ... by averaging the equation of binary image intensity: f1 = (1/n) Σ BW_i × 100% ... The gray value decreases as the ablated area fraction increases ... The linear fit equation is: GV = (91.3±1.5) − (0.79±0.02)f1"

    f1 is computed by thresholding the same grayscale value GV that is then reported as a linearly decreasing function of f1. Once the binary mask is defined by a threshold on GV, the average GV and the fraction of pixels above/below that threshold are mathematically coupled; a change in the dark/bright pixel fraction necessarily moves the mean GV in the opposite direction. The reported GV-versus-f1 correlation is therefore largely a consequence of the segmentation rule rather than an independent optical observation.

  2. fitted input called prediction [Sec. 5.2, Table 1 and the paragraph reporting Fig. 6(a) fits]
    "Fitting parameters for Eq. (2), Eq. (3), and Eq. (4) for curves given in Figure 6(a) are depicted Table 1 ... For Cassie model Eq. (2) the contact angles of θ1 = 0° which correspond well to the experimental value minimal contacted angle of <4° ... and θ2 = 129° correspond well to the experimental value maximal measures angle ... There is good agreement between experimental data and theoretical fits"

    The model parameters θ1 and θ2 are set to the endpoint contact angles of the same dataset being plotted (θ1 = 0° matches the measured <4° at high fluence, θ2 = 129° matches the measured maximum at 0.48 J/cm²). The 'good agreement' between Eqs. (2)-(4) and the data is therefore enforced at the endpoints by construction. The curves are interpolations or fits, not independent predictions, despite being introduced as theoretical predictions.

full rationale

The central wetting claim rests on two independently measured quantities: the sessile-drop contact angle and a binary image fraction f1 computed from microscope images. The relation CA(f1) is empirical and would be meaningful even if the theoretical models were absent. However, two parts of the paper are circular in a limited way. First, f1 is defined by thresholding the grayscale value GV (Eqs. 6-8), and the same GV is then reported as a linearly decreasing function of f1 with a fitted line; this correlation is largely constructed by the segmentation rule. Second, the Cassie/Cassie-Baxter/Wenzel curves in Fig. 6(a) are called theoretical predictions but are fitted using endpoint angles θ1 and θ2 from the same dataset (Table 1), so their 'good agreement' is partly built in. Neither of these affects the independent contact-angle-versus-f1 trend, so the central claim is not circular. Separately, Eq. (7) as printed assigns BW=1 to GV≥GVth, which with GVth=0.48 would classify untreated copper (⟨GV⟩=0.89) as 100% and strongly ablated copper (⟨GV⟩=0.062) as 0%; this appears opposite to the reported 'ablated area fraction' trend and is a reproducibility/correctness concern rather than a circularity. The threshold method cites prior work by the same group (ref. 100), but it is used as an image-processing convention rather than as an argument that forces the wetting result, so it does not add circularity. Score 4 reflects the partial self-construction of the color and fitting claims while the main wettability result remains independent.

Assumptions & free parameters 4 free parameters · 4 assumptions · 0 invented entities

The central claim does not introduce new physical entities; it relies on a custom image threshold, an identification between image area fraction and model solid fraction, and standard wetting models with parameters fitted to the data.

free parameters (4)
  • Grayscale threshold GVth = 0.48 ± 0.02
    Set by Eq. (10) as the midpoint between the average gray values of untreated and maximally ablated copper; all reported area fractions f1 depend on this choice.
  • Cassie model contact angles θ1 and θ2 = θ1 = 0°, θ2 = 129°
    Chosen from the experimental endpoint contact angles (Table 1) to draw the fit curve for Eq. (2).
  • Cassie-Baxter contact angle θ1 = 0°
    Set to the near-zero endpoint contact angle for Eq. (3).
  • Combined Cassie-Baxter/Wenzel parameters = θ1 = 4°, θ2 = 98°, r1 = 1.01
    Selected from the experimental endpoints and a nearly flat roughness factor for Eq. (4).
assumptions (4)
  • ad hoc to paper The average grayscale threshold of Eq. (10) objectively separates laser-ablated from unablated copper pixels.
    The threshold is chosen as the midpoint of two extremes without independent validation; Section 4.2.
  • domain assumption The measured ablated area fraction f1 can be identified with the solid fraction in the Cassie and Cassie-Baxter models.
    Sections 2.2-2.3 and 5.2; the models use f1 directly, but the physical identification of image-derived ablated area with solid-liquid contact fraction is assumed.
  • domain assumption Contact angles measured 15 days after laser texturing represent the stable value.
    Section 3.4, citing refs. 97 and 98; no aging curve is shown for this copper.
  • domain assumption The Cassie, Cassie-Baxter, and Wenzel model framework is applicable to these laser-textured copper surfaces.
    Sections 2 and 5.2; the paper adopts these models to explain the data but does not test alternative mechanisms such as surface chemistry changes.

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Cite this review

Pith. "Pith review of Wettability and Color Change of Copper by Controlling Area Fraction of Laser Ablated Surface." pith.science (2026). https://pith.science/paper/M6YK2XTE

@misc{pith2026241117324,
  author       = {Pith},
  title        = {Pith review of: Wettability and Color Change of Copper by Controlling Area Fraction of Laser Ablated Surface},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/M6YK2XTE}},
  note         = {Machine review of arXiv:2411.17324}
}
read the original abstract

In this research, wettability control by area fraction of laser ablated surface of copper is presented. The functional surfaces with full wettability control from highly hydrophilic to super-hydrophobic were created on copper by nanosecond (ns) and picosecond (ps) laser irradiation. The area fraction and color change were evaluated by digital image processing of microscopic images of the laser-ablated copper surface. The control of the wetting angle from almost 0 degrees to 132 degrees was achieved for both ps and ns pulses by controlling the area fraction of the laser-ablated surface. Cassie, Cassie-Baxter, and Wenzel models were adopted to explain the experimental results. For the first time, the wettability and color of copper were controlled by controlling the area fraction of the laser-ablated surface. It is expected that the current results make an impact on the heat exchanger technology of water heat sinks, cooling units, atmospheric water generators, and fog harvesting and impact numerous applications from power plants to solar thermal water systems devices where highly-hydrophilic to super hydrophobic copper can be applied.

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Works this paper leans on

1 extracted references · 1 canonical work pages

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    Moth Eye

    1 Gaidys, M., Selskis, A., Gečys, P. & Gedvilas, M. Stainless steel colouring using burst and biburst mode ultrafast laser irradiation. Optics & Laser Technology 174, 110561, doi:10.1016/j.optlastec.2024.110561 (2024). 2 Zorba, V. et al. Biomimetic Artificial Surfaces Quantitatively Reproduce the Water Repellency of a Lotus Leaf. Advanced Materials 20, 40...

    work page arXiv 2024

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Reviewed August 12, 2026 · model on record in the stance chip above.