All the aforementioned parameters have been considered to comprehend their impacts on BSi doping profiles radiative optical properties and to enable a tuning route for obtaining a suitable absorber for a specific application. The doping profiles across the depth of the ion-implanted samples have been numerically calculated as a function of the ion-implantation parameters.
On the basis of the obtained dopant concentration profiles, we have calculated the threshold depth d defined as the depth after which the ion implanted BSi fails to retain the highest concentration level of the order of 1020 cm−3. Since we are primarily interested in values of doping larger than 1019 cm−3, this threshold depth is an important criterion in establishing optimum ion-implantation parameters to maximize radiation absorption at the sample surface in a depth lower than 1 μm. Thereafter, the skin depth, defined as the depth at which the intensity of the radiation inside the material falls to 1/e of its original value at the surface, is calculated for each sample. It can be expressed as δ=2ρωμ1+(ρωε)2+ρωε,(1)where ρ is the resistivity of the material, ω is the angular frequency = 2πf, f is the frequency, μ is the permeability of the material, μ=μrμ0 along μr is the relative magnetic permeability of the material, μ0 is the permeability of free space, ε=εrε0 is the permittivity of the material with εr the relative permittivity of the material, and ε0 is the permittivity of free space. We have calculated the skin depth for particular values of resistivity for p-type and n-type dopant, namely, boron and phosphorous at the highest doping level of 1020 cm−3, as this is the highest doping level achievable considering the solid solubility of the considered dopants in silicon. Then, we calculate the attenuation coefficient as 1−e−2d/δ, since the penetration depth of the electromagnetic waves in the material at normal incidence is proportional to the attenuation coefficient. Given the attenuation coefficient expression, we can have different situations where (i) d<δ, (ii) d=δ, and (iii) d>δ. The wavelength, λc, at which the condition of d=δ is fulfilled, gives us a critical value beyond which the absorption at the surface level will be reduced, and can be used to tune the absorber spectral selectivity. These quantities are illustrated in Figs. 1(II-c) and 1(II-d) and enable us not only to explain how light is absorbed in ion-implanted BSi but also to maximize the absorptivity using the optimum values of implantation dosage and ion-beam energy in a particular range of wavelengths. Bearing these quantities in mind, we present and discuss the results obtained with various BSi ion-implanted samples in the following paragraphs.Square samples of 1 cm2 have been diced upon completion of the ion-implantation. The radiative properties, the transmittance T and reflectance R in particular, were then measured on the 1 cm2 samples by Fourier Transform Infrared (FTIR) Spectroscopy using a Perkin Elmer Spectrum 3 spectrometer with a DTGS detector in the spectral range from 1.3 μm up to 26 μm at room temperature. The absorptivity A is then computed using the energy conservation principle as A=1−R−T.
We present and discuss in the following paragraphs the results obtained with various BSi ion-implanted samples.
We show in Fig. 2 the measured reflectance (a), transmittance (b), and absorptance (c) of ion-implanted BSi samples with of an energy of 100 KeV of the n-type wafer in the spectral range from 1 to 5 μm. The samples' properties are grouped in Table I.TABLE I. Ion-implantation parameters and wafer details of the studied samples.
Wafer IDEnergy (keV)Dose (at/cm²)W11001.0×1017W21002.0×1016W31001.0×1015W0Reference wafer (no ion-implantation)VDBSiVolume doped N typeFirst, regarding the samples' radiative properties, we observe that the heavily dosed samples of W1 record the lowest level of reflectance of 0.96% at 2.5 μm, and this rises to 1.84% at 5 μm. The level of reflectance rises as ion-implantation dosage decreases. Similarly, for transmittance, samples with the highest dosage exhibit the lowest transmittance. Among all the samples of the n-type wafer, it is observable that only those with heavy doses of ion-implantation, i.e., larger than 1016 at/cm2, have transmittance below 5%. Interestingly, for samples 1 and 2, until 5 μm, there is a noticeable peak of transmittance which reaches 1.5%, 4.5%, and 5.3% and then reduces to 0.023%, 0.123%, and 0.25%, respectively, for the entire wavelength range from 1.3 to 5 μm. All other samples rise above 15% of transmittance, and the highest value is reached by the n-type reference Si sample. When compared to volume-doped n-type BSi samples (VDBSi Sample), no ion-implanted sample records such low transmittance levels ∼0.02%. Regarding absorptance, the highest level of 98.86%–96.35% in the wavelength range 1.3–5 μm is reached by sample 1 with the highest dose of ion-implantation. The reference sample understandably records the lowest absorptance.
One should note that for wavelengths larger than 5 μm, smaller absorptance is recorded for the different samples (supplementary Fig. S1). We show in Fig. 3(a) the obtained dopant concentration profiles with ion-implantation simulations, phosphorous P+ in this case, of the samples under consideration. We have seen in Fig. 2 that W1 exhibits the lowest reflectance, lowest transmittance, and highest absorptance, followed by W2. From Fig. 3(a), we extract the values of d at a dopant concentration of 1020 cm−3 and calculate the attenuation coefficient 1−e−2d/δ shown in Fig. 3(b). The dopant concentration for W3 does not reach the cutoff value of 1020 atm/cm3, and, hence, does not appear in these figures. In Fig. 3(b), we see that the attenuation coefficient is the highest for W1 followed by W2 and progressively drops with decreasing values of dosage and consequently threshold depths, d, indicating that below a dosage of 1016 atm/cm2, a high attenuation coefficient cannot be achieved. For both W1 and W2, the threshold condition d=δ is fulfilled at a critical wavelength, λc= 3 and 4.5 μm, respectively. Going back to these samples absorptance at λc=3 [Fig. 2(c)], we observe that the absorptance falls below 98% for both samples beyond λc. This indicates that this condition is, indeed, useful to determine the depth of high doping concentration required to obtain high absorption of incident radiation.One can also conclude that ion-implantation with a dosage of 1017 at/cm2 is sufficient to reach a complete absorption of light at the surface for BSi up to 5 μm. We can also note that this measure of the penetration depth is a key indicator than can be used to design and fabricate surface-doped BSi with enhanced absorptance in the spectral range of 1–5 μm. Surface doping alone can then be employed to considerably enhance silicon absorptivity, in wide mid-infrared (MIR) range from 1 to 5 μm, even though it does not reach the performances of volume doped BSi in terms of absorptivity levels and the spectral range width.20,31,3220. S. Sarkar, A. A. Elsayed, F. Marty, J. Drévillon, Y. M. Sabry, J. Zhao, Y. Yu, E. Richalot, P. Basset, and T. Bourouina, in 25th International Workshop on Thermal Investigations of ICs and Systems (THERMINIC) ( IEEE, 2019), pp. 1–4.31. S. Sarkar, A. Elsayed, F. Marty, J. Drevillon, Y. Sabry, J. Zhao, Y. Yu, E. Richalot, P. Basset, and T. Bourouina, in Congrès Annuel de La Société Française de Thermique, 2020.32. S. Sarkar, A. A. Elsayed, E. Nefzaoui, J. Drévillon, P. Basset, F. Marty, M. Anwar, Y. Yu, J. Zhao, and X. Yuan, in IEEE 32nd International Conference on Micro Electro Mechanical Systems (MEMS) ( IEEE, 2019), pp. 860–862. At this stage of the discussion, it is worth noting that for highly doped silicon that displays plasmonic behavior,3333. S. Sarkar, A. A. Elsayed, Y. M. Sabry, F. Marty, J. Drévillon, X. Liu, Z. Liang, E. Richalot, P. Basset, and E. Nefzaoui, Adv. Photonics Res. (published online, 2022). https://doi.org/10.1002/adpr.202200223 the absorption of incident radiation is acutely dependent on its doping level. In a prior report,3333. S. Sarkar, A. A. Elsayed, Y. M. Sabry, F. Marty, J. Drévillon, X. Liu, Z. Liang, E. Richalot, P. Basset, and E. Nefzaoui, Adv. Photonics Res. (published online, 2022). https://doi.org/10.1002/adpr.202200223 the effect of doping was demonstrated on volume-doped BSi, where the depth of the entire substrate was 500 μm, whereas in the present case, the depth d is less than 1 μm, which also explains why surface-doped BSi has lesser level of absorption than volume-doped BSi.In addition, we also note (supplementary Fig. S2) that increasing levels of energy (keV) in the ion-implantation process increases the absorptance and reduces both reflectance and transmittance. Consequently, the largest absorptance is obtained with the largest ion-implantation energy, 100 keV in our case. This is consistent with the literature that reports that ion-beam energy is directly proportional to the depth of penetration.3434. P. Van Zant, Microchip Fabrication ( McGraw-Hill Education, 2014). However, the impact of energy is less conspicuous than the effect of dosage on the absorptance of BSi. Therefore, the dosage is the dominant factor to enhance the surface doped BSi absorptivity.At last, we analyze the effect of the used dopant and the type of wafer. Two wafers of n-type and p-type (samples 9 and 4) were implanted with opposite dopants, i.e., n-type implanted with p-type dopant, i.e., boron and p-type implanted with n-type dopant, i.e., phosphorous. We observe (supplementary Fig. S3) that p-type wafer implanted with n-type dopant or has lower absorptance than n-type wafer implanted with p-type dopant. Wafers 4 and 9 have absorptance levels dropping to 85% and 65%, respectively, at 5 μm. The radiative properties, i.e., reflectance, transmittance, and absorptance of n and p-type wafers at benchmark wavelengths of 5, 8, 10, and 13 μm, have been noted in Tables SI and SII in the supplementary material. In any case, all of these different combinations lead to lower performances, if we consider large absorptivity as a target, than those presented and discussed above, if we consider the absorptance level as our figure of merit.To summarize, surface doping on BSi can be employed to achieve considerably enhanced MIR absorptivity of silicon, in particular, in the spectral range 1–5 μm. Even though it does not lead absorption levels and spectral ranges as high and wide than those of heavily volume doped BSi, it offers the flexibility of altering only the samples surface, while keeping low doping concentration in the volume. This capability is very important for numerous applications such as photodetectors and solar cells, for instance. In the case of surface doping, the dosage of ion-implantation is the dominant parameter for obtaining large absorptivity. In the present work, the highest levels of absorptance 98.9% are provided by wafers subjected to highest phosphorous doping dosage of the order of 1017 at/cm2. Higher ion-implantation energy levels also provide highest levels of absorptance, but the results are less sensitive to energy than to the dosage. Quantitative analysis with dopant concentrations profiles and an evaluation of the respective skin depths for each sample according to their threshold depths (d) for the highest concentration attests to the fact that highest dosage provides the highest threshold depth, d. Only for samples where the dosage is of the order of 1017 at/cm2 and specifically in our case for n-type wafer doped with phosphorous, the condition d=δ is fulfilled. This explains the highest absorptances recorded by these samples within 1–5 μm. This indication provides a simple design rule to maximize the absorptivity of surface doped BSi by ion-implantation.
See the supplementary material for the surface doping conditions and the radiative properties of all the samples covered in the present study. Only a subset of the samples considered as the most promising was included in the main manuscript.This work was supported by the I-SITE FUTURE Initiative (Reference No. ANR-16-IDEX-0003) in the framework of the Project No. NANO-4-WATER.
Conflict of Interest
The authors have no conflicts to disclose.
Author Contributions
Sreyash Sarkar: Data curation (lead); Formal analysis (lead); Investigation (lead); Software (equal); Visualization (lead); Writing – original draft (lead). Elyes Nefzaoui: Conceptualization (equal); Funding acquisition (equal); Investigation (supporting); Methodology (equal); Project administration (lead); Resources (lead); Supervision (lead); Validation (lead); Visualization (supporting); Writing – review & editing (lead). Georges Hamaoui: Investigation (supporting); Writing – review & editing (supporting). Frederic Marty: Investigation (equal); Resources (lead); Writing – review & editing (supporting). Philippe Basset: Conceptualization (equal); Supervision (equal); Validation (supporting); Writing – review & editing (supporting). Tarik Bourouina: Conceptualization (equal); Funding acquisition (equal); Methodology (equal); Project administration (lead); Resources (equal); Supervision (lead); Validation (lead); Writing – review & editing (supporting).
The data that support the findings of this study are available from the corresponding author upon reasonable request.
REFERENCES
1. S. Mohammadi, A. A. Eftekhar, A. Khelif, W. D. Hunt, and A. Adibi, Appl. Phys. Lett. 92, 221905 (2008). https://doi.org/10.1063/1.2939097, Google ScholarScitation, ISI2. A. Blanco, E. Chomski, S. Grabtchak, M. Ibisate, S. John, S. W. Leonard, C. Lopez, F. Meseguer, H. Miguez, J. P. Mondia, G. A. Ozin, O. Toader, and H. M. van Driel, Nature 405, 437 (2000). https://doi.org/10.1038/35013024, Google ScholarCrossref, ISI3. E. Nefzaoui, J. Drevillon, and K. Joulain, J. Appl. Phys. 111, 084316 (2012). https://doi.org/10.1063/1.4705363, Google ScholarScitation, ISI4. R. Halir, A. Ortega-Moñux, D. Benedikovic, G. Z. Mashanovich, J. G. Wangüemert-Pérez, J. H. Schmid, Í. Molina-Fernández, and P. Cheben, Proc. IEEE 106, 2144 (2018). https://doi.org/10.1109/JPROC.2018.2851614, Google ScholarCrossref5. Y.-B. Chen and Z. M. Zhang, J. Phys. D 41, 095406 (2008). https://doi.org/10.1088/0022-3727/41/9/095406, Google ScholarCrossref6. Y. Zhang, M. Yuan, L. Chen, B. Cai, R. Yang, and Y. Zhu, Opt. Commun. 361, 148 (2016). https://doi.org/10.1016/j.optcom.2015.10.051, Google ScholarCrossref7. L. Gao, E. Nefzaoui, F. Marty, X. Wei, S. Bastide, Y. Leprince-Wang, and T. Bourouina, Sol. Energy Mater. Sol. Cells 243, 111793 (2022). https://doi.org/10.1016/j.solmat.2022.111793, Google ScholarCrossref8. J. Lv, T. Zhang, P. Zhang, Y. Zhao, and S. Li, Nanoscale Res. Lett. 13(1), 110 (2018). https://doi.org/10.1186/s11671-018-2523-4, Google ScholarCrossref9. Y. Xia, B. Liu, J. Liu, Z. Shen, and C. Li, Sol. Energy 85, 1574 (2011). https://doi.org/10.1016/j.solener.2011.03.012, Google ScholarCrossref10. H. Savin, P. Repo, G. V. Gastrow, P. Ortega, E. Calle, M. Garín, and R. Alcubilla, Nat. Nanotechnol. 10, 624 (2015). https://doi.org/10.1038/nnano.2015.89, Google ScholarCrossref11. P. Hoyer, M. Theuer, R. Beigang, and E.-B. Kley, Appl. Phys. Lett. 93, 091106 (2008). https://doi.org/10.1063/1.2978096, Google ScholarScitation, ISI12. E. P. Ivanova, J. Hasan, H. K. Webb, G. Gervinskas, S. Juodkazis, V. K. Truong, A. H. Wu, R. N. Lamb, V. A. Baulin, and G. S. Watson, Nat. Commun. 4(1), 2838 (2013). https://doi.org/10.1038/ncomms3838, Google ScholarCrossref13. S. A. Iakab, P. Ràfols, M. Tajes, X. Correig-Blanchar, and M. García-Altares, ACS Nano 14, 6785 (2020). https://doi.org/10.1021/acsnano.0c00201, Google ScholarCrossref14. X.-Y. Yu, J.-H. Zhao, C.-H. Li, Q.-D. Chen, and H.-B. Sun, IEEE Trans. Nanotechnol. 16, 502 (2017). https://doi.org/10.1109/TNANO.2017.2693691, Google ScholarCrossref15. D. G. Kotsifaki, M. Kandyla, and P. G. Lagoudakis, Sci. Rep. 6(1), 26275 (2016). https://doi.org/10.1038/srep26275, Google ScholarCrossref16. Y. Song, T. Liu, S. Liu, J. Huang, J. Li, C. Tian, T. Yu, Y. He, Y. Liu, and Z. Zhong, J. Mater. Sci. 31, 4696–4701 (2020). https://doi.org/10.1007/s10854-020-03025-2, Google ScholarCrossref17. Y. Chen, G. Kang, A. Shah, V. Pale, Y. Tian, Z. Sun, I. Tittonen, S. Honkanen, and H. Lipsanen, Adv. Mater. Interfaces 1, 1300008 (2014). https://doi.org/10.1002/admi.201300008, Google ScholarCrossref18. S. M. Asiala, J. M. Marr, G. Gervinskas, S. Juodkazis, and Z. D. Schultz, Phys. Chem. Chem. Phys. 17, 30461 (2015). https://doi.org/10.1039/C5CP04506A, Google Scholar
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