Surface-Enhanced Infrared Absorption of Self-Aligned Nanogap Structures

Plasmonic nanostructures are often used in surface-enhanced infrared absorption (SEIRA) spectroscopy to probe surface assembled molecules or the dielectric environment surrounding the metallic nanostructures. Here we fabricate metallic nanogap structures using self-aligned techniques on an intrinsic silicon substrate and correlate resulting SEIRA spectra with the choice of metal nanostructure geometry. A motivation is to compare the enhancement from hybridization of bright plasmon modes with the effect of hybridization between bright and dark plasmon modes. These structures provide a gap size below 10 nm and support strong field enhancements. The structures demonstrate their sensitivity through the enhanced absorption signature of the Si–O stretch in the native silicon oxide layer of nanometer thickness beneath the metal. Simulations reveal this thin layer plays a critical role in determining the plasmon modes of the nanostructures. Numerical simulations of the optical properties are consistent with the observations that stronger Si–O stretch signals are detected on self-aligned nanogap structures than nanorod arrays, highlighting the enhanced electromagnetic fields in the underlying native oxide

Additional file 1 of Identification and validation of glomerulotubular crosstalk genes mediating IgA nephropathy by integrated bioinformatics

Additional file 1

Threshold estimation results.

Based on 2010–2019 Chinese logistics listed companies as research samples, the paper used the binary Logit model measuring degree of financing constraints. The Kernel density function and Markov chain model are used to forecast China listed companies financing logistics dynamic constraints and business performance growth. Furthermore the stock of knowledge was chosen as a threshold variable to explore the impact of financing constraints on corporate performance growth of listed logistics enterprises. We find that the degree of financing constraints of logistics enterprises in our country has not been significantly eased. Corporate performance has not changed significantly and there are no obvious spatial gap and polarization with the passage of time. The impact of financing constraints on the corporate performance growth of logistics enterprises in China has a double threshold effect of knowledge stock, and has an inhibitory effect that first increases and then decreases. This is because in the short term, the investment of knowledge stock by enterprises can crowd out more corporate liquidity, and in the long run, it is related to the conversion rate of the knowledge stock itself. Because of the uneven regional distribution of resources and differences in the degree of economic development, there is a growing disincentive effect in central China as the stock of knowledge accumulates.</div

Eastern region threshold regression results.

Based on 2010–2019 Chinese logistics listed companies as research samples, the paper used the binary Logit model measuring degree of financing constraints. The Kernel density function and Markov chain model are used to forecast China listed companies financing logistics dynamic constraints and business performance growth. Furthermore the stock of knowledge was chosen as a threshold variable to explore the impact of financing constraints on corporate performance growth of listed logistics enterprises. We find that the degree of financing constraints of logistics enterprises in our country has not been significantly eased. Corporate performance has not changed significantly and there are no obvious spatial gap and polarization with the passage of time. The impact of financing constraints on the corporate performance growth of logistics enterprises in China has a double threshold effect of knowledge stock, and has an inhibitory effect that first increases and then decreases. This is because in the short term, the investment of knowledge stock by enterprises can crowd out more corporate liquidity, and in the long run, it is related to the conversion rate of the knowledge stock itself. Because of the uneven regional distribution of resources and differences in the degree of economic development, there is a growing disincentive effect in central China as the stock of knowledge accumulates.</div

Variable definition.

Based on 2010–2019 Chinese logistics listed companies as research samples, the paper used the binary Logit model measuring degree of financing constraints. The Kernel density function and Markov chain model are used to forecast China listed companies financing logistics dynamic constraints and business performance growth. Furthermore the stock of knowledge was chosen as a threshold variable to explore the impact of financing constraints on corporate performance growth of listed logistics enterprises. We find that the degree of financing constraints of logistics enterprises in our country has not been significantly eased. Corporate performance has not changed significantly and there are no obvious spatial gap and polarization with the passage of time. The impact of financing constraints on the corporate performance growth of logistics enterprises in China has a double threshold effect of knowledge stock, and has an inhibitory effect that first increases and then decreases. This is because in the short term, the investment of knowledge stock by enterprises can crowd out more corporate liquidity, and in the long run, it is related to the conversion rate of the knowledge stock itself. Because of the uneven regional distribution of resources and differences in the degree of economic development, there is a growing disincentive effect in central China as the stock of knowledge accumulates.</div

The LFC index calculations.

Based on 2010–2019 Chinese logistics listed companies as research samples, the paper used the binary Logit model measuring degree of financing constraints. The Kernel density function and Markov chain model are used to forecast China listed companies financing logistics dynamic constraints and business performance growth. Furthermore the stock of knowledge was chosen as a threshold variable to explore the impact of financing constraints on corporate performance growth of listed logistics enterprises. We find that the degree of financing constraints of logistics enterprises in our country has not been significantly eased. Corporate performance has not changed significantly and there are no obvious spatial gap and polarization with the passage of time. The impact of financing constraints on the corporate performance growth of logistics enterprises in China has a double threshold effect of knowledge stock, and has an inhibitory effect that first increases and then decreases. This is because in the short term, the investment of knowledge stock by enterprises can crowd out more corporate liquidity, and in the long run, it is related to the conversion rate of the knowledge stock itself. Because of the uneven regional distribution of resources and differences in the degree of economic development, there is a growing disincentive effect in central China as the stock of knowledge accumulates.</div

Corporate performance horizontal Markov model transfer probability matrix (k = 4).

Corporate performance horizontal Markov model transfer probability matrix (k = 4).</p

Private enterprises state-owned enterprises threshold regression results.

Private enterprises state-owned enterprises threshold regression results.</p

Total sample threshold regression results.

Based on 2010–2019 Chinese logistics listed companies as research samples, the paper used the binary Logit model measuring degree of financing constraints. The Kernel density function and Markov chain model are used to forecast China listed companies financing logistics dynamic constraints and business performance growth. Furthermore the stock of knowledge was chosen as a threshold variable to explore the impact of financing constraints on corporate performance growth of listed logistics enterprises. We find that the degree of financing constraints of logistics enterprises in our country has not been significantly eased. Corporate performance has not changed significantly and there are no obvious spatial gap and polarization with the passage of time. The impact of financing constraints on the corporate performance growth of logistics enterprises in China has a double threshold effect of knowledge stock, and has an inhibitory effect that first increases and then decreases. This is because in the short term, the investment of knowledge stock by enterprises can crowd out more corporate liquidity, and in the long run, it is related to the conversion rate of the knowledge stock itself. Because of the uneven regional distribution of resources and differences in the degree of economic development, there is a growing disincentive effect in central China as the stock of knowledge accumulates.</div

Financing constraint horizontal Markov model transfer probability matrix (k = 4).

Financing constraint horizontal Markov model transfer probability matrix (k = 4).</p