Improved Transition Metal Dichalcogenides-Based Surface Plasmon Resonance Biosensors

Round 1

Reviewer 1 Report

In this paper, the performance of propagating SPR sensors consisting of metal thin films, BP, and TMDC layers are theoretically investigated. The theoretical expressions described in this paper are general and the obtained results are reasonable. After the appropriate revision for the following comments, this manuscript will be suitable for the publication in Condensed Matter.

1. The authors should explain the origin of thicknesses of MoS2, MoSe2, WS2, andWeSe2.

2. As shown in Figure 3, the suitable refractive indices for the use of Au and Ag for the best sensitivities are different. The authors should explain these results.

Author Response

Reviewer 1 Report

We thank Reviewer 1 for providing valuable feedback and comments to improve the quality of our paper. Our response is given in bold red font.

Reviewer 1: The authors should explain the origin of thicknesses of MoS₂, MoSe₂, WS₂, andWeSe₂.

Response: The visible and reasonable thickness range for Ag and Au are 25-60 nm, and mostly best response prefer less than 50 nm [1, 2]. For the TMDCs, the more decreasing the thickness, the more increasing the sensitivity but those TMDCs have a minimum thickness for obtaining the valid sensitivity in vast application area [3].

Reviewer 1: As shown in Figure 3, the suitable refractive indices for the use of Au and Ag for the best sensitivities are different. The authors should explain these results.

Response: Yes, we agree, the refractive indices for the use of Au and Ag for the best sensitivities are different. Comparing with the two-layers performance, Ag shows the highest sensitivity of 375 º/RIU at refractive index 1.3440, and Au shows 285 º/RIU at 1.3400.  For further information, some other results are shown below:

Following references are cited in the text:

1.       Miceli, P.; Neumann, D.; Zabel, H. X‐ray refractive index: A tool to determine the average composition in multilayer structures. Appl. physics letters 1986, 48, 24-26

2.       Johnson, P.; Christy, R. Optical constants of transition metals: Ti, v, cr, mn, fe, co, ni, and pd. Physical Review B 1974, 9, 5056.

3.       Wu, L.; Guo, J.; Wang, Q.; Lu, S.; Dai, X.; Xiang, Y.; Fan, D. Sensitivity enhancement by using few-layer black phosphorus-graphene/TMDCs heterostructure in surface plasmon resonance biochemical sensor. Sensors and Actuators B: Chemical 2017, 249, 542-548.

We thank the Reviewer.

Author Response File: Author Response.pdf

Reviewer 2 Report

Dear Author,

I think your work describes an interesting simulation of TDMC performance as SPR transductor.

My main concern is related to the future biosensing application that you claim for your numerical model. In C. 2 row 75 you considered the variation of medium the refractive index from 1.33 to 1.35: is this relevant from a biosensing application point of view? If so, please add some reference to prove it. Furthermore, in the simulation model of Fig. 1 a biological probe layer in contact with the liquid medium is missing: what kind of biosensor do you think to simulate? Without a probe layer, I suppose it will not be an affinity one: do you think to detect only the variation of the refractive index of the liquid medium at the interface of TDMC? Please describe the biosensing strategy you plan to implement.

Regarding your draft, please consider the following notes for redrafting:

-) unless further explanations, I suggest that you remove any reference to biosensing from your draft, starting from the title;

-) C. 1 row 51-54: please describe in greater detail the role of FWHM in defining the properties of Ag over Au;

-) C. 2 row 65-68: please briefly describe the manufacturing processes you plan to use to create your sensing multilayer, e.g., sputter, chemical vapor deposition or other;

-) C. 4.2.1: please describe why you simulate only four combinations of layer thicknesses, and why you choose those values;

-) Fig. 4: please clarify what are the multilayer parameters that generate the curves: is the multilayer already optimized?

-) Fig. 5: please describe why the simulated data with the complete multilayer, i.e., with Ag, BP and WS2 thicknesses > 0, have a different behavior than the other cases, showing a maximum at about n=1.345;

-) Fig. 7 and 8: please clarify if these simulations have been obtained by setting the parameters to the optimal values obtained from the previous analysis, e.g., Ag always at 35 nm;

-) row 216-217: what do you mean with “target molecules”? From Fig. 1 it seems that BP is not in contact with the liquid medium, so why using it as a probe layer?

-) I think that a closing graph is missing, the one related to the variation of reflectivity of the complete multilayer as a function of incidence angle for mediums with different refractive indexes. Is it Fig. 4?

Author Response

Reviewer 2 Response

We thank Reviewer 2 for providing valuable feedback and comments to improve the quality of our paper. Our response is given in bold Red font.

Summery:

Reviewer 2: My main concern is related to the future biosensing application that you claim for your numerical model. In C. 2 row 75 you considered the variation of the medium the refractive index from 1.33 to 1.35: is this relevant from a biosensing application point of view? If so, please add some reference to prove it.

Our response: We thank the Reviewer 2 for this valuable suggestion. We have added the information on biosensing in the text as the refractive index (n) of the probing medium is 1.33, and the variation of n is considered in the range of 1.3300 to 1.3500, i.e., Dn in the range of 0.01 to 0.02. These refractive indices correspond closely to the refractive index of urine (a bio-sample) with various concentration concerning the specific gravity depending on whether the disease is normal, moderate, acute or above average. A new reference is also added in the text as [17,18]. We hope this clarifies.

Furthermore, in the simulation model of Fig. 1 a biological probe layer in contact with the liquid medium is missing: what kind of biosensor do you think to simulate? Without a probe layer, I suppose it will not be an affinity one: do you think to detect only the variation of the refractive index of the liquid medium at the interface of TDMC? Please describe the biosensing strategy you plan to implement.

Our response: Fig. 1 is updated, and the experimental description is added in the text. Corresponding references are also added. We hope this clarifies.

Reviewer 2: Unless further explanations, I suggest that you remove any reference to biosensing from your draft, starting from the title.

Our response: We hope that the above explanation would be enough to keep the proposed scheme suitable for biosensing application.

Reviewer 2: C 1 row 51-54: please describe in greater detail the role of FWHM in defining the properties of Ag over Au.

Our response: A relatively low FWHM is preferred when it comes to designing a biosensor that would show the best performance. The sharper the FWHW, the accurate in determining the angular modulation with high accuracy detection. The magnitude of FWHM is mainly depended on the excitation configuration, the layers and the optical properties of prism used.

Gold is most commonly used as it possesses highly stable optical and chemical properties. However, the FWHM in air, for gold: 10.67° and for silver: 0.71°. That means silver provides, in contrast, the sharpest SPR signal. Silver is reported to have an enhanced sensitivity to the thickness and refractive index variation in comparison to gold. Also, the penetration length of a 50 nm thick gold film is about 164 nm with a light source of 630 nm, whereas a 50 nm thick silver film has an enlarged penetration length of 219 nm. New citations [11-15], relevant to these facts are included in the revised text. We hope this clarifies.

Reviewer 2: C. 2 row 65-68: please briefly describe the manufacturing processes you plan to use to create your sensing multilayer, e.g., sputter, chemical vapour deposition or other.

Our response: We plan to grow TMDC layers using molecular beam epitaxy as it has shown to enable high purity heterostructures [19]. A short paragraph is added at the end of Section.

Reviewer 2: C. 4.2.1: please describe why you simulate only four combinations of layer thicknesses, and why you choose those values.

Our response: We performed many different simulations and tuned to get the maximum possible value for performance parameters.

At first, after analyzing previous researches, we selected layers to use in our configuration. In terms of selecting layers, we kept into mind that it should be only three layers between the prism and sensing medium. Those three layers have been selected for their useful characteristic which modifies the performance of the biosensor.

So, we did many simulations to select which layer we should take. Then again, many simulations to get the optimized thickness of the selected layers.

All these simulations could not be shown in the paper. So, we tried to show the zest of our decision after many simulations through those four structures. Moreover, those values are also the product of our numerous simulations done for checking. 

Reviewer 2: Fig. 4: please clarify what are the multilayer parameters that generate the curves: is the multilayer already optimized?

Our response: Yes, absolutely these multilayers are optimized. Layers of different materials and their thickness are compiled after many simulations. Finally, the combination is selected for our configuration.

Reviewer 2: Fig. 5: Please describe why the simulated data with the complete multilayer, i.e., with Ag, BP and WS2 thicknesses > 0, have different behavior than the other cases, showing a maximum at about n=1.345.

Our response: We simulated data with complete multilayers because that complete numbers had been finalized by numerous simulations. After trying all numbers for the thickness of layers in simulation, the combination of those complete numbers had given the most optimized result. In this paper, we just showed the result with finalized numbers.

The behavior of the curves for different configuration changes because of molecular binding rate in the sensing medium. At, 1.345, maximum molecular binding Is the reason behind the highest sensitivity. Here, the exact RI is 1.344 at which maximum sensitivity occurs.

Reviewer 2: Fig. 7 and 8: please clarify if these simulations have been obtained by setting the parameters to the optimal values obtained from the previous analysis, e.g., Ag always at 35 nm.

Our response: After our optimization, we found that Ag at 35 nm gives the highest sensitivity with the lowest minimum reflectance. Moreover, that is the most desirable. So, for other layer optimization, we kept the Ag layer's thickness at 35nm.

Reviewer 2: Row 216-217: what do you mean with “target molecules”? From Fig. 1 it seems that BP is not in contact with the liquid medium, so why using it as a probe layer?

Our response: The basic idea of the Kretschmann configuration has only a coupling prism with a metal layer above the prism and a sensing layer. Later in other research, to modify the sensor various layers have been used. The function of these layers is to reduce the loss by corrosion in metal layers. Moreover, these layers help to increase the absorbance of biomolecules in the sensing medium. These layers help to pass the light after total reflection to pass without loss. So, the total energy gets transferred. BP layers are not the sensing layers, but it helps by its characteristics to let the sensing medium absorb more molecules. Fig 1 is updated.

Reviewer 2: I think that a closing graph is missing, the one related to the variation of reflectivity of the complete multilayer as a function of incidence angle for mediums with different refractive indexes. Is it Fig. 4?

Our response: Yes, the complete and final structure graph is Fig. 4, where we have shown final values for the proposed model.

Following new references relevant to the work reported in this paper are added in the text:

1.      H. Liu, A. T. Neal, Z. Zhu, Z. Luo, X. Xu, D. Tománek, et al., "Phosphorene: an unexplored 2D semiconductor with high hole mobility," ACS nano, vol. 8, pp. 4033-4041, 2014.

2.      S. Nelson, K. S. Johnston, and S. S. Yee, "High sensitivity surface plasmon resonace sensor based on phase detection," Sensors and actuators B: Chemical, vol. 35, pp. 187-191, 1996.

3.      K. S. Novoselov, A. K. Geim, S. V. Morozov, D. Jiang, Y. Zhang, S. V. Dubonos, et al., "Electric field effect in atomically thin carbon films," science, vol. 306, pp. 666-669, 2004.

4.      B. Sa, Y.-L. Li, J. Qi, R. Ahuja, and Z. Sun, "Strain engineering for phosphorene: the potential application as a photocatalyst," The Journal of Physical Chemistry C, vol. 118, pp. 26560-26568, 2014.

5.      L. Shulenburger, A. D. Baczewski, Z. Zhu, J. Guan, and D. Tomanek, "The nature of the interlayer interaction in bulk and few-layer phosphorus," Nano letters, vol. 15, pp. 8170-8175, 2015.

We thank the Reviewer.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Dear Authors,

thank you for your redrafting efforts. 

Kind regards.