Progress in the Development of Multi-Element Monolithic Germanium Detectors in LEAPS-INNOV Project: Insights from Detector Performance Simulation

A. Balerna; B. Schmitt; C. Cohen; C. Ward; E. Collet; E. N. Gimenez; E. Welter; F. J. Iguaz; G. Dennis; H. Graafsma

REVIEW 6 major objections 5 minor 12 references

Progress in the Development of Multi-Element Monolithic Germanium Detectors in LEAPS-INNOV Project: Insights from Detector Performance Simulation

T0 review · 6 major / 5 minor · reviewed 2026-08-16 · deepseek-v4-flash

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Pith's one-line read This simulation study predicts that a multi-element monolithic germanium detector can detect cadmium in soil at concentrations as low as 1.21 ppm when placed 10 mm from the sample, with the detection limit rising to about 7.99 ppm at 200…

desk verdict A plausible but unvalidated simulation parameter scan whose qualitative distance/flux trends are physically expected; the quantitative detection limits are provisional until the simulation chain is benchmarked against experiment. read the letter →

arxiv 2504.14652 v1 pith:UL46WUP7 submitted 2025-04-20 physics.ins-det

N. Goyal , S. Aplin , A. Balerna , P. Bell , J. Casas , M. Cascella , S. Chatterji , C. Cohen

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E. Collet G. Dennis P. Fajardo E. N. Gimenez H. Graafsma H. Hiresmann F. J. Iguaz K. Klementiev T. Kolodziej L. Manzanillas T. Martin R. H. Menk M. Porro M. Quispe B. Schmitt S. Scully M. Turcato C. Ward E. Welter

This is my paper · ORCID

classification physics.ins-det

keywords monolithicgermaniumdetectordetectionlimitcadmiuminsoilX-rayfluorescenceXAFSMonteCarlosimulationsolid-statesynchrotroninstrumentation

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

This paper reports a simulation-based performance study of a multi-element monolithic germanium detector being developed for synchrotron X-ray spectroscopy. The authors compute the detection limit for cadmium in a standard soil sample by simulating the full detector response at a 30 keV beam and varying the sample-to-detector distance and photon flux. At the measured reference flux of $3.47\times10^{10}$ photons per second, the predicted cadmium detection limit is about 1.21 ppm at 10 mm and worsens to about 7.99 ppm at 200 mm, while higher fluxes improve the limit. The results are offered as guidance for placing such detectors close to samples in environmental trace-element monitoring, with experimental validation left to future work.

What carries the argument

The argument runs on a coupled detector-response simulation chain. A particle-transport Monte Carlo step generates the coordinates and deposited energies of X-ray interactions in the germanium sensor; a solid-state detector simulation then computes the electric field, charge drift and diffusion, weighting potentials, and electrode pulses through the Shockley–Ramo theorem, and adds realistic electronic noise. The load-bearing identity is the detection-limit formula $\mathrm{DL} = 3\,C\,\sqrt{N_{\mathrm{bkgd}}}/(\mathrm{OCR}_{\mathrm{sig}}\,T_{\mathrm{exp}})$, which converts the simulated background count and output count rate into a minimum detectable concentration in ppm. The simulation inputs include a bias voltage near 200 V, an impurity density near $10^{10}\,\mathrm{cm^{-3}}$, a 3 mm tungsten collimator, and experimental baseline noise.

What would settle it

Run the real big-pixel prototype on the same EnviroMAT cadmium soil at 30 keV and a flux of $3.47\times10^{10}$ ph/s, measuring the detection limit at 10, 50, 100, and 200 mm; if the measured limits do not follow the predicted trend from roughly 1.2 to 8 ppm within statistical uncertainty, the simulation chain's predictive claim is not supported.

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Extended reading notes

Core claim

The central claim is that the big-pixel configuration of the monolithic germanium detector can reach a cadmium detection limit in EnviroMAT soil of approximately 1.21 ppm at a sample-to-detector distance of 10 mm, rising to 2.48 ppm at 50 mm, 4.02 ppm at 100 mm, and 7.99 ppm at 200 mm, at 30 keV and a photon flux of $3.47\times10^{10}$ ph/s. The paper attributes the distance effect to X-ray attenuation in air and to increased noise susceptibility at larger distances, and it shows that the detection limit improves monotonically as the incident flux is increased from $10^7$ to $10^{12}$ ph/s. These values come from the detection-limit formula $\mathrm{DL} = 3\,C\,\sqrt{N_{\mathrm{bkgd}}}/(\mathrm{OCR}_{\mathrm{sig}}\,T_{\mathrm{exp}})$ applied to the simulated Cd K-$\alpha$ region of interest (22.5–24 keV) of a soil spectrum. The paper presents these numbers as simulation predictions and states that validation with the first prototype is planned.

Load-bearing premise

The entire set of predicted detection limits rests on the assumption that the simulated detector response, with its assumed bias voltage, impurity density, collimator, and electronic baselines, faithfully matches what the real prototype will measure.

Editorial extensions

If this is right

Placing the detector at 10 mm instead of 200 mm improves the predicted cadmium detection limit from 7.99 ppm to 1.21 ppm, so close geometry is the main practical lever for trace sensitivity.
Detection limit improves as photon flux rises from $10^7$ to $10^{12}$ ph/s, meaning brighter beams and longer exposure times lower the minimum detectable concentration.
The simulation chain assigns the distance penalty largely to air attenuation and noise, implying that a shorter air path or a vacuum/helium gap would preserve sensitivity at larger working distances.
The 50 mm distance was selected as an operating point for the flux study, balancing the need for sensitivity against the geometric constraints of real beamlines.

Reading between the lines

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

If the chain is validated, the same simulation recipe could be reused for other pollutant elements and other soil or water matrices by changing the target composition and energy region of interest, without new hardware.
The paper's distance trend suggests a testable prediction: removing air from the simulated path should flatten or eliminate the rise in detection limit with distance, isolating the noise contribution.
Because the conclusions are drawn for the 20 mm² big-pixel geometry, the smaller 5 mm² XAFS pixels may show a different distance-flux tradeoff; that comparison is not made here.
The quantitative ppm values should be read as design predictions pending the prototype experiment, since no measured detector response is yet presented.

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Editorial analysis

A structured set of objections, weighed in public.

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

Desk Editor's Note

read the letter

You should know this one before reading it: it is a parameter scan, not a validation. The authors use the Geant4 + SSD.jl chain they have already reported in refs. [3] and [9] to simulate a big-pixel monolithic Ge detector and estimate cadmium detection limits in EnviroMAT soil. The headline numbers — about 1.2 ppm at 10 mm rising to roughly 8 ppm at 200 mm for 30 keV, 3.47e10 ph/s — follow from counting statistics and solid angle. That is fine as far as it goes, and the qualitative trends (DL worsens with distance, improves with flux) are exactly what you would expect.

What the paper does well: it is honest that the simulation is a design tool, it uses a realistic measured beamline flux as input, and it spells out the intended path to experimental validation (Section 6). For someone planning a trace-element XRF experiment on a synchrotron beamline, the distance and flux dependences give a rough sense of what geometry matters. The work also usefully documents progress in the LEAPS-INNOV WP2 detector development program.

The soft spots are real but mostly fixable. Eq. (1) is garbled as printed — the S/B term inside the square root makes no dimensional sense — and Eq. (2) is the one that actually appears to be used, but NBckgd is not defined clearly enough to reproduce the numbers. There are no statistical error bars on the detection-limit points, which matters when the claim is a specific ppm value. More substantively, the text attributes the distance effect to X-ray attenuation in air and to larger-distance noise susceptibility, but the Geant4 model described in Section 3 includes only detector, W collimator, and sample — no air gap. If air is not in the simulation, then the claimed dominant cause for the 10 vs 200 mm trend is not actually in the model, and the trend instead comes from solid-angle change plus whatever noise handling SSD.jl applies. That does not break the qualitative conclusion, but it does undermine the physical explanation given. The "optimal 50 mm" statement in the conclusion is also unjustified: Fig. 4 shows DL monotonically decreasing with smaller distances, so 50 mm is only optimal if you impose some other constraint (e.g., practical geometry or sample environment), which is not stated.

Who benefits: mostly the LEAPS-INNOV collaboration and beamline scientists looking for provisional guidance. The paper deserves a serious referee rather than a desk reject, because the simulation methodology is substantive and the detector development context is important. But it should be conditional on fixing the equations, clarifying what is in the simulation geometry, adding error bars or at least a sensitivity study, and resolving the 50 mm inconsistency. I would not cite the specific ppm numbers until experimental validation appears.

Referee Report

6 major / 5 minor

Summary. This manuscript reports a simulation study of a multi-element monolithic germanium detector for detecting cadmium traces in EnviroMAT soil, using a Geant4 model of the detector, a tungsten collimator, and the sample, followed by charge-transport and pulse reconstruction with SolidStateDetectors.jl. For the big-pixel geometry, the authors compute the Cd detection limit as a function of sample-to-detector distance (10–200 mm) at a fixed 30 keV beam flux of 3.47e10 ph/s, and as a function of incident flux at a reference distance. They report that the detection limit degrades from about 1.21 ppm at 10 mm to about 7.99 ppm at 200 mm, and improves with increasing flux. Experimental validation is explicitly deferred to future work (Section 6).

Significance. If the simulation chain is reliable, the results provide useful, design-relevant guidance for the LEAPS-INNOV monolithic Ge detector program and for synchrotron XRF experimental geometry optimization. Strengths of the paper include the use of a realistic beam flux measured at the SAMBA beamline, a reasonably detailed Geant4 geometry with a tungsten collimator, and a full charge-transport treatment via SSD.jl rather than a simple efficiency tabulation. The main limitations are that the central quantitative claims rest on a simulation chain that is not yet benchmarked against experiment, that Eq. (1) is malformed and Eq. (2) leaves key quantities underspecified, and that one of the paper's explanatory claims (air attenuation) is not supported by the simulation setup as described. The numerical detection-limit values should therefore be regarded as predictions until the code is validated and the equations are corrected.

major comments (6)

[§4, Eq. (1)] Equation (1) is malformed as printed: the square-root symbol is followed by a product of N_Pixels, ICR_Pixel, (1−DT/100), S/B, S/T, and T_exp without parentheses indicating which terms are under the radical, and the expression is dimensionally inconsistent with Eq. (2). Since the text states that Eq. (1) is the basis for evaluating the detection limit, the numerical values in Figs. 4 and 5 cannot be reproduced from the paper as written; please rewrite the equation and define every symbol in the expression.
[§4, Eq. (2)] The symbol N_Bckgd is listed as a 'background count rate,' but in Eq. (2) it appears to be used as a count (or count rate) entering a detection-limit formula, and the paper does not specify whether it is the raw count in the Cd Kα region of interest (22.5–24 keV), a net count after continuum subtraction, or a background rate. The continuum-subtraction method is not described, so the reported DL values (1.21–7.99 ppm) cannot be independently checked or reproduced from the paper alone.
[§5] The distance dependence of the detection limit is attributed to 'attenuation of X-rays in air and increased susceptibility to noise at larger distances,' but the Geant4 setup described in §3 includes only the detector, the tungsten collimator, and the sample; no air gap is listed. If air is not included in the simulation, the claimed dominant physical cause is absent and the trend must instead arise mainly from solid-angle changes and the noise model; if air is included, that must be stated explicitly in §3.
[§6] The conclusion states that 'we used the optimal 50 mm sample-to-detector distance,' but Fig. 4 shows the detection limit monotonically decreasing with distance, with 10 mm (1.21 ppm) giving a better detection limit than 50 mm (2.48 ppm). This is a direct contradiction; the optimal-distance claim should be revised, or an unstated constraint (e.g., a practical minimum working distance) should be introduced and justified.
[§1 and §6] The introduction refers to the 'validated full simulation chain,' but Section 6 states that validation with experimental data is scheduled for the future, and no experimental spectrum, measured noise baseline, or comparison with measured detector response is presented. Because the headline detection-limit values depend entirely on the simulated signal and background, the paper should consistently label the results as unvalidated simulation predictions and should clearly report which inputs (e.g., baseline noise, flux) are measured rather than assumed.
[Figs. 4 and 5] No statistical uncertainties are shown for any detection-limit point, despite the use of finite Monte Carlo statistics and a noise baseline. The paper quotes values to three significant figures (e.g., 1.21 ppm vs. 2.48 ppm at 10 mm and 50 mm), but without error bars the reader cannot judge whether the reported differences are significant or whether the trend in Fig. 4 is robust to statistical fluctuations.

minor comments (5)

[§4, bullet list] The bullet list defines S/B as 'signal-to-noise or signal-to-background ratio,' which is ambiguous; choose one definition and use it consistently throughout, and define S/T precisely as the fraction of signal counts inside the full-energy peak relative to the total spectrum.
[§4, text before Eq. (1)] The detection limit is described as being at 90% confidence level, but the factor 3 in Eq. (2) corresponds to three standard deviations (approximately 99.7% for a Gaussian distribution). Please clarify how the factor 3 relates to the stated confidence level.
[§4 and elsewhere] Capitalization of the sample name is inconsistent: 'ENviroMAT' appears in Section 4 while 'EnviroMAT' is used elsewhere; standardize the spelling.
[Fig. 5] The left panel's vertical axis label ('signal-to-noise ratio') appears only in the caption, and the right panel's axes (photon flux and detection limit) are not labeled inside the figure; add axis labels directly to the figure panels.
[References] Reference [10] is incomplete as given (missing the full journal or conference publication details); please supply the complete citation.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: detection limits are direct simulation outputs through a standard formula, not fitted to the target results.

full rationale

The central claim (DL ≈ 1.21–7.99 ppm for Cd in EnviroMAT with distance) is computed from simulated signal and background counts inserted into Eq. (2), DL = 3*C*NBckgd/sqrt(OCR_sig*Texp). No parameter of that formula is fit to the reported DL values; rather, the signal and background counts are produced by a Geant4 + SSD.jl simulation chain with stated inputs (30 keV, 3.47e10 ph/s, 200 V bias, ~1e10 cm^-3 impurity, 3 mm W collimator, 1 s exposure). The distance and flux trends are consequences of the simulated count rates, not of an input quantity that already contains those trends. The paper cites prior collaboration work for the simulation chain (Refs. [3] and [9]), but it does not invoke those citations to define the DL values or to forbid alternative explanations. The main weakness is validation: Section 6 explicitly says validation against experimental data is anticipated to be scheduled shortly, so the quantitative DL values are unverified predictions. That is a correctness and reproducibility risk, not circularity. Also, Eq. (1) as printed is malformed and the extraction of NBckgd is incompletely specified, which impedes reproduction, but these are presentation gaps rather than circular reductions.

Assumptions & free parameters 5 free parameters · 4 assumptions · 0 invented entities

The central result rests on the fidelity of the Geant4 + SSD.jl simulation chain and on several chosen input parameters (bias voltage, impurity density, dead time, exposure time, test concentration). No new physical entities are introduced. The detection limit formula is standard counting statistics, but Eq. (1) is garbled and the dead-time value is unspecified. The simulation is not yet validated against experimental detector data, and the air-attenuation explanation for the distance trend is not clearly grounded in the described setup.

free parameters (5)

Bias voltage = ~200 V
Chosen in Section 3; affects charge transport and collection efficiency in the SSD simulation; no sensitivity study provided.
Impurity density = ~1e10 cm^-3
Chosen in Section 3; affects the electric field in the detector; no sensitivity study provided.
Dead time (DT) = not specified
Appears in Eq. (3) for output count rate but no value is given, making the computed OCR ambiguous.
Cd test concentration = 100 ppm
Used to define the signal in the RoI; the detection limit is scaled linearly from this concentration, assuming linear response.
Exposure time = 1 s
Set in the Figure 3 caption; detection limit scales as the inverse square root of exposure time.

assumptions (4)

domain assumption Geant4 and SSD.jl accurately model the physical response of the monolithic Ge detector.
The paper relies on the 'validated full simulation chain' but does not present an experimental comparison; validation is deferred to future work (Section 6).
domain assumption The background measured from a sample without Cd is an appropriate proxy for the matrix background in the Cd RoI.
Used in Section 4 to define N_Bckgd; assumes the soil matrix is otherwise identical and that there are no interfering lines.
standard math Counting statistics follow a Gaussian approximation such that DL = 3*C*sqrt(N_Bckgd)/(OCR_sig*Texp) gives a 90% C.L. limit.
Standard formula, but the paper's Eq. (1) is garbled; the 3-sigma convention is stated.
domain assumption The simulation includes (or does not need) air attenuation between sample and detector.
Section 5 attributes the distance dependence to air attenuation, but Section 3's setup lists only detector, collimator, and sample; if air is omitted, the explanation is unsupported.

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Cite this review

Pith. "Pith review of Progress in the Development of Multi-Element Monolithic Germanium Detectors in LEAPS-INNOV Project: Insights from Detector Performance Simulation." pith.science (2026). https://pith.science/paper/UL46WUP7

@misc{pith2026250414652,
  author       = {Pith},
  title        = {Pith review of: Progress in the Development of Multi-Element Monolithic Germanium Detectors in LEAPS-INNOV Project: Insights from Detector Performance Simulation},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/UL46WUP7}},
  note         = {Machine review of arXiv:2504.14652}
}

read the original abstract

This study presents a detailed simulation-based analysis of the detection limits of multi-element monolithic Germanium (Ge) detectors to cadmium traces in environmental soil samples. Using the capabilities of the Geant4 Monte Carlo toolkit in combination with the Solid State Detector Package, we evaluated the detection limit variation with the sample-to-detector distances and photon flux. These simulations were conducted to mimic realistic conditions, with a photon flux measured by the SAMBA beamline at the SOLEIL synchrotron facility. Our findings for the detection limit for trace amounts of pollutants in low concentrations like cadmium in the soil provide valuable insights for optimizing experimental setups in environmental monitoring and synchrotron-based applications, where precise detection of trace elements is critical.

Figures

Figures reproduced from arXiv: 2504.14652 by the authors.

**Figure 1.** Flowchart illustrating the full simulation chain using Geant4 and SSD.jl, discussed in detail in the text 2. Detector Description and Features In the context of WP2, two multi-element monolithic germanium sensors, were fabricated by Mirion company, featuring two element sizes: 5 mm² dedicated for XAFS experiments and 20 mm² for XRF experiments, chosen to optimize throughput and detection efficiency respectively. The… view at source ↗

**Figure 2.** Full simulation chain: Top-left: Geant4 constructed setup, which showcases the Ge detector with the big pixel along with a W collimator, and a 30 keV X-ray beam hitting the target sample; Top-right: X-ray mapping for Ge sensor produced using SSD with Julia; Bottom-left: simulated waveform for an event collected in a single contact; Bottom-right: Simulated energy spectrum of EnviroMAT soil sample using Geant4 output … view at source ↗

**Figure 3.** Simulated element energy spectrum with Ge sensor placed at a distance of 50, 70, 120 and 200 mm with a soil sample of EnviroMAT rich in Cd( 100 ppm) and without its trace. The exposure time considered here is 1 sec, with an incident beam energy of 30 keV, and the associated beam flux is 3.47 × 1010 ph/sec. The shaded green area defines the region of interest of the Cd Kα-peak. 5. Results and discussions The [PITH_F… view at source ↗

Figures from the paper (2 more)

**Figure 4.** Figure 4: Detection limit (in ppm) as a function of sample to detector distance varying systematically from 10 to 200 mm exposed with a photon flux of 3.47 × 1010 ph/sec [PITH_FULL_IMAGE:figures/full_fig_p006_4.png]

**Figure 5.** Figure 5: (Left) Response of signal-to-noise ratio with respect to varying EnviroMAT sample to detector distance in simulation Optimization of detection limits, analyzed over a S-D range of distances from 10 to 200 mm. (Right) The detection limit (in ppm) is represented on a log…

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Reference graph

Works this paper leans on

12 extracted references · 6 canonical work pages

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" write newline "" before.all 'output.state := FUNCTION blank.sep after.quote 'output.state := FUNCTION fin.entry output.state after.quoted.block = 'skip 'add.period if write newline FUNCTION new.block output.state before.all = 'skip output.state after.quote = after.quoted.block 'output.state := after.block 'output.state := if if FUNCTION new.sentence out...
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Pith tools

Reviewed August 16, 2026 · model on record in the stance chip above.

[1] [3]

F. Orsini et al., Xafs-det: A new high throughout x-ray spectroscopy detector system developed for synchrotron applications, https://doi.org/10.1016/j.nima.2022.167600 Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 1045 (2023)

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L. Bombelli, C. Fiorini, T. Frizzi, R. Alberti and A. Longoni, "CUBE", A low-noise CMOS preamplifier as alternative to JFET front-end for high-count rate spectroscopy , 2011 IEEE Nuclear Science Symposium Conference Record (2011) 1972 https://doi.org/10.1109/NSSMIC.2011.6154396

arXiv 2011

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write newline

" write newline "" before.all 'output.state := FUNCTION blank.sep after.quote 'output.state := FUNCTION fin.entry output.state after.quoted.block = 'skip 'add.period if write newline FUNCTION new.block output.state before.all = 'skip output.state after.quote = after.quoted.block 'output.state := after.block 'output.state := if if FUNCTION new.sentence out...

[4] [2]

Tartoni, S

N. Tartoni, S. Chatterji, R. Crook, T. Krings, L. Bombelli and A. Alborini, Hexagonal pad multichannel ge x-ray spectroscopy detector demonstrator: Comprehensive characterization, https://doi.org/10.1109/TNS.2020.3004923 IEEE Transactions on Nuclear Science 67 (2020) 1952

arXiv 2020

[5] [4]

Iguaz, T

F. Iguaz, T. Saleem, E. Fonda, G. Landrot, L. Manzanillas and F. Orsini, Detection limit of next-generation of multi-element germanium detectors in the context of environmental science, https://doi.org/10.1088/1742-6596/2380/1/012096 Journal of Physics: Conference Series 2380 (2022) 012096

work page doi:10.1088/1742-6596/2380/1/012096 2022

[6] [5]

Agostinelli, J

S. Agostinelli, J. Allison, K. Amako, J. Apostolakis, H. Araujo, P. Arce et al., Geant4—a simulation toolkit, https://doi.org/https://doi.org/10.1016/S0168-9002(03)01368-8 Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 506 (2003) 250

doi:10.1016/s0168-9002(03)01368-8 2003

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Abt et al., Simulation of semiconductor detectors in 3d with solidstatedetectors.jl, https://doi.org/10.1088/1748-0221/16/08/P08007 Journal of Instrumentation 16 (2021) P08007

I. Abt et al., Simulation of semiconductor detectors in 3d with solidstatedetectors.jl, https://doi.org/10.1088/1748-0221/16/08/P08007 Journal of Instrumentation 16 (2021) P08007

work page doi:10.1088/1748-0221/16/08/p08007 2021

[8] [7]

Dennis, W

G. Dennis, W. Helsby, D. Omar, I. Horswell, N. Tartoni, S. Hayama et al., First results using the new dls xspress4 digital pulse processor with monolithic segmented hpge detectors on xas beamlines, in AIP Conference Proceedings, vol. 2054, AIP Publishing, 2019

work page 2019