A method for analyzing rare earth doped up-conversion luminescence behavior based on random walk model

Abstract

The application discloses a rare earth doped upconversion luminescence behavior analysis method based on a random walk model, which comprises the following steps: establishing an upconversion luminescence nanospace structure and a luminescence center distribution configuration; setting an ion energy level structure of a double-doped upconversion luminescence system; setting various energy transport processes and corresponding probabilities in the upconversion luminescence process; simulating a random walk process of energy in the upconversion particle system by using a Monte Carlo method; calculating an excitation and decay process of the upconversion luminescence system; and outputting upconversion transient luminescence behavior data. The method and the model can describe the energy transport process of the rare earth doped upconversion luminescence system at the nanometer scale at a micro level, can be used for luminescence behavior regulation and luminescence mechanism research, and can provide theoretical support for designing and developing rare earth doped upconversion luminescence particles with specific luminescence characteristics.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of rare earth doped upconversion luminescence, and particularly relates to a rare earth doped upconversion luminescence behavior analysis method based on a random walk model. BACKGROUND

[0002] Upconversion luminescence, also known as anti-Stokes luminescence, can absorb long-wavelength light and emit short-wavelength light. The rare earth doped upconversion luminescence material has high luminescent efficiency, rich luminescent wavelength, and the characteristics of easy storage, easy recombination and stable luminescence, and has important applications in the fields of biological imaging, anti-counterfeiting and optogenetics.

[0003] With the development of nanotechnology, the development of nano-scale structure materials further expands the application scope of upconversion luminescence, and some novel optical phenomena are discovered. The understanding of the upconversion luminescence process and the research on the luminescence mechanism are further developed. At present, the research on the theoretical model of upconversion luminescence cannot meet the new optical material preparation, optical structure design and discovery and analysis of new luminescence phenomena. Some researchers have proposed or established some theoretical research models, for example, Grant and Zubenko have established a rate equation model and a random walk model, which provide some basic guidance methods for analyzing and predicting ion luminescence. However, due to the complexity of the rare earth luminescence principle and the emergence of new nano materials, it is urgent to establish a theoretical model that can cover the main luminescence process (energy transport) in the luminescence system to restore the luminescence behavior and provide theoretical guidance for the research on the upconversion luminescence mechanism.

[0004] The random walk model can to a great extent reflect the energy transport process of rare earth ions in nano structures. The energy is distributed in space (i.e. the energy transport process) through the interaction between sensitizers and sensitizers, sensitizers and activators, and luminescence centers and substrates, thereby affecting the luminescence behavior. It should be pointed out that the energy migration behavior between the sensitizing ions in this model plays a key role in the generation and regulation of luminescence. At present, the model has attracted the attention of researchers, for example, Zuo et al. simulated the micro-interaction between ions in nanocrystals by using the random walk model, but the assumption of ion distribution in the nanocrystal is too simple, and the change of ion state and its surrounding environment at each moment in the energy transport process is not considered, and the energy level structure is only a simple two-photon system. We comprehensively consider the common ion distribution problem, the problem of oversimplified energy level, and the process competition probability, and combine the statistical simulation method adopted in the Monte Carlo simulation to obtain numerical results by relying on a large number of repeated random sampling, to establish a new type of upconversion luminescence analysis model in which the random walk probability changes with the spatial distribution and can analyze complex energy level systems, which is expected to provide an important tool for studying the ion energy transfer mechanism in the field of rare earth doped upconversion luminescence. SUMMARY

[0005] In order to solve the above problems, the application provides a rare earth doped material up-conversion luminescence analysis method based on a random walk model.

[0006] The application provides a rare earth doped up-conversion luminescence behavior analysis method based on a random walk model, characterized by comprising the following steps:

[0007] Step S1: establishing an up-conversion luminescence nano-space structure and a luminescence center distribution configuration;

[0008] Step S2: setting an ion energy level structure of a double-doped up-conversion luminescence system;

[0009] Step S3: setting various energy transport processes and corresponding probabilities in the up-conversion luminescence process;

[0010] Step S4: simulating a random walk process of energy in the up-conversion particle system by using a Monte Carlo method;

[0011] Step S5: calculating an up-conversion luminescence system excitation and decay process, and outputting up-conversion transient luminescence behavior data;

[0012] The step S1 comprises:

[0013] Step S101: establishing an up-conversion luminescence nano-space structure;

[0014] Step S102: distributing ground state sensitizers and ground state activator ions in the up-conversion luminescence nano-space structure in a random distribution manner;

[0015] The step S3 comprises:

[0016] Step S301: simplifying energy transport processes in the up-conversion luminescence process, and only including energy migration, energy transfer, pump absorption, radiation transition and non-radiation transition processes;

[0017] Step S302: calculating probabilities of each energy transport process;

[0018] The pump absorption probability is obtained by the following formula:

[0019]

[0020] Wherein, ρ represents an excitation energy density, σ represents an ion absorption cross section, Δt represents a time step of each random walk, and E represents a single photon energy in the medium;

[0021] The energy migration, energy transfer, radiation transition and non-radiation transition probabilities are obtained by the following formula:

[0022]

[0023] wherein represents the probability of each energy transport process of the excited state ion, and Δt represents the time step of each random walk;

[0024] The step S4 comprises:

[0025] Step S401, the ground state sensitizer ion randomly occurs pump absorption according to the pump absorption probability;

[0026] Step S402, judging the nearest neighbor ion species of the excited state sensitizer ion;

[0027] Step S403, the excited state sensitizer ion and the nearest neighbor ion are calculated to occur random energy transport probability, and the excited state sensitizer ion occurs random energy transport process according to the probability;

[0028] Step S404, the excited state activator ion randomly occurs radiative transition and non-radiative transition according to the radiative transition and non-radiative transition probability.

[0029] The excitation process of the application is to repeat steps S401-S404 for time steps from 0 time, until the excitation stops. The decay process of the application is to repeat steps S402-S404 for time steps from the excitation stop, until the decay time is exhausted or the number of activator ions that occur radiative transition is 0.

[0030] The output of the upconversion transient luminescence behavior data of the application is the number of activator ions that occur radiative transition in the excitation and decay processes.

[0031] The ion energy level structure in the step S2 of the application can be simplified or set according to the actual energy level structure, and the ion species can be adjusted.

[0032] The application has the following advantages:

[0033] At present, it has been proved in experiments that the energy migration process has an important influence on upconversion luminescence, but the mainstream rate equation model cannot reflect the energy migration process, and the energy migration process occupies a dominant position in the random walk model, so the model and the experimental conclusion have high consistency.

[0034] While establishing a more complex upconversion luminescence energy level system, the probability of ion random walk changes with the change of its surrounding environment, which can well reflect the influence of the change of the surrounding environment of the luminescence center in the real upconversion luminescence nanospace on the upconversion luminescence.

[0035] According to the actual situation, adjust various energy transport processes and change the three-dimensional array structure to adjust the upconversion luminescence nanospace structure and the luminescence center distribution configuration, realize the regulation and control of the rare earth doped upconversion luminescence system in experiments, and simulate the upconversion luminescence system closer to the reality. BRIEF DESCRIPTION OF DRAWINGS

[0036] Figure 1 Flow chart of random walk process provided for the embodiment 1 of the present application.

[0037] Figure 2 Energy level structure diagram of up-conversion luminescence system established for the embodiment 1 of the present application.

[0038] Figure 3 Up-conversion transient luminescence behavior data image output for the embodiment 1 of the present application.

[0039] Figure 4 Up-conversion transient luminescence behavior data image output for the embodiment 2 of the present application.

[0040] Figure 5 Up-conversion transient luminescence behavior data image output for the embodiment 3 of the present application. DETAILED DESCRIPTION

[0041] The specific embodiments of the present application are described in detail below by taking a typical energy level structure system of rare earth doped up-conversion luminescence nanomaterials and combining with charts. Embodiment 1

[0042] Figure 1 The flow chart of random walk process provided for the embodiment of the present application specifically includes:

[0043] Step S1 is to establish up-conversion luminescence nanospace structure and luminescence center distribution configuration;

[0044] Step S1 specifically includes:

[0045] Step S101: a 100x100x100 matrix is established by using a three-dimensional array, and other configurations can also be used;

[0046] Step S102: the sensitizer and activator ions in the ground state are respectively distributed in the up-conversion luminescence nanospace structure in a random distribution manner at a ratio of 2% and 98%.

[0047] Step S2 is to set the ion energy level structure of the double-doped up-conversion luminescence system, specifically as shown in Figure 2

[0048] Step S3 is to set various energy transport processes and corresponding probabilities in the up-conversion luminescence process;

[0049] Step S3 specifically includes:

[0050] Step S301: the energy transport processes in the up-conversion luminescence process are simplified to only include energy migration, energy transfer, pump absorption and radiation transition processes; ​

[0051] Step S302: calculating the probability of each energy transport process.

[0052] Specifically, the pump absorption probability is calculated by the following formula:

[0053]

[0054] wherein p represents the excitation energy density, s represents the ion absorption cross section, At represents the time step of each random walk, and E represents the energy of a single photon in vacuum;

[0055] The energy migration, energy transfer, radiative transition, and non-radiative transition probabilities are calculated by the following formula:

[0056]

[0057] wherein p represents the probability of each energy transport process of the excited state ion, and At represents the time step of each random walk.

[0058] Step S4 is to simulate the random walk process of energy in the upconversion particle system by the Monte Carlo method;

[0059] Step S4 specifically includes:

[0060] Step S401: the ground state sensitizer ion randomly undergoes pump absorption according to the pump absorption probability;

[0061] Step S402: judging the nearest neighbor ion species of the excited state sensitizer ion;

[0062] Step S403: the excited state sensitizer ion undergoes a random energy transport process according to the energy transport probability with the nearest neighbor ion;

[0063] Step S404: the excited state activator ion randomly undergoes radiative transition and non-radiative transition according to the radiative transition and non-radiative transition probability.

[0064] Step S5, calculating the excitation and decay processes of the upconversion luminescence system, defining the excitation time as 8000 microseconds and the decay time as 4000 microseconds, and outputting the upconversion transient luminescence behavior data.

[0065] Specifically, the excitation process is to repeat steps S401-S404 in 1 microsecond one after another until the excitation time is exhausted; the decay process is to repeat steps S402-S404 in 1 microsecond one after another until the decay time is exhausted or the number of excited state activator ions undergoing radiative transition is 0, and the output of the upconversion transient luminescence behavior data is the number of activator ions undergoing radiative transition in the excitation and decay processes. Example 2

[0066] ​Figure 1 The flow chart for establishing the random walk process provided by the embodiment of the present application specifically includes:

[0067] Step S1 is to establish the up-conversion luminescent nano spatial structure and the luminescent center distribution configuration;

[0068] Step S1 specifically includes:

[0069] Step S101: a matrix with a size of 200x200x200 is established by using a three-dimensional array, and other configurations can also be used;

[0070] Step S102: the sensitizer ions and the activator ions in the ground state are respectively distributed in the up-conversion luminescent nano spatial structure in a random distribution manner at a ratio of 2% and 98%.

[0071] Step S2 is to set the ion energy level structure of the double-doped up-conversion luminescent system, and specifically as shown in Figure 2

[0072] Step S3 is to set various energy transport processes and corresponding probabilities in the up-conversion luminescent process;

[0073] Step S3 specifically includes:

[0074] Step S301: the energy transport processes in the up-conversion luminescent process are simplified to only include energy migration, energy transfer, pump absorption and radiation transition processes;

[0075] Step S302: the probability of each energy transport process is calculated.

[0076] Specifically, the pump absorption probability is calculated by the following formula: same as Embodiment 1;

[0077] The energy migration, energy transfer, radiation transition and non-radiation transition probabilities are calculated by the following formula: same as Embodiment 1.

[0078] Step S4 is to simulate the random walk process of energy in the up-conversion particle system by the Monte Carlo method;

[0079] Step S4 specifically includes:

[0080] Step S401: the ground state sensitizer ions randomly occur pump absorption according to the pump absorption probability;

[0081] Step S402: the nearest neighbor ion species of the excited state sensitizer ions is judged;

[0082] Step S403: the excited state sensitizer ions occur random energy transport processes according to the energy transport probability with the nearest neighbor ions;

[0083] ​Step S404: the excited state activator ions randomly occur radiation transition and non-radiation transition according to radiation transition and non-radiation transition probability.

[0084] Step S5: the up-conversion luminescence system excitation and decay process is calculated, the excitation time is defined as 8000 microseconds, the decay time is defined as 4000 microseconds, and the up-conversion transient luminescence behavior data is outputted.

[0085] Specifically, the excitation process is that steps S401-S404 are repeated in 1 microsecond by turns until the excitation time is exhausted; the decay process is that steps S402-S404 are repeated in 1 microsecond by turns until the decay time is exhausted or the number of excited state activator ions occurring radiation transition is 0, and the up-conversion transient luminescence behavior data is the number of activator ions occurring radiation transition in the excitation and decay process. Embodiment 3

[0086] Figure 1 The flow chart for establishing the random walk process provided for the embodiments of the present application specifically includes:

[0087] Step S1 is to establish the up-conversion luminescence nano spatial structure and luminescence center distribution configuration;

[0088] Step S1 specifically includes:

[0089] Step S101: a matrix with a size of 100*100*100 is established by using a three-dimensional array, and other configurations can also be used;

[0090] Step S102: the sensitizer and activator ions in the ground state are respectively distributed in the up-conversion luminescence nano spatial structure in a random distribution manner at a proportion of 10% and 90%, and the proportion allocation can be adjusted.

[0091] Step S2 is to set the ion energy level structure of the double-doped up-conversion luminescence system, and specifically as shown in Figure 2 ;

[0092] Step S3 is to set various energy transport processes and corresponding probabilities in the up-conversion luminescence process.

[0093] Step S3 specifically includes:

[0094] Step S301: the energy transport processes in the up-conversion luminescence process are simplified to only include energy migration, energy transfer, pump absorption and radiation transition processes.

[0095] Step S302: the probability of each energy transport process is calculated.

[0096] Specifically, the pump absorption probability is obtained by calculation according to the following formula: same as embodiment 1;

[0097] The energy transfer, energy transmission, radiation transition and non-radiation transition probability are calculated by the following formula: Same as Embodiment 1.

[0098] Step S4 is to simulate the random walking process of energy in the up-conversion particle system by Monte Carlo method;

[0099] Step S4 specifically comprises:

[0100] Step S401: the ground state sensitizer ion randomly occurs pump absorption according to pump absorption probability;

[0101] Step S402: judging the nearest neighbor ion species of the excited state sensitizer ion;

[0102] Step S403: the excited state sensitizer ion occurs random energy transport process according to the energy transport probability with the nearest neighbor ion;

[0103] Step S404: the excited state activator ion randomly occurs radiation transition and non-radiation transition according to the radiation transition and non-radiation transition probability.

[0104] Step S5, calculating the excitation and decay process of the up-conversion luminescence system, defining the excitation time as 8000 microseconds and the decay time as 4000 microseconds, and outputting the up-conversion transient luminescence behavior data.

[0105] Specifically, the excitation process is to repeat steps S401-S404 in 1 microsecond successively until the excitation time is exhausted; the decay process is to repeat steps S402-S404 in 1 microsecond successively until the decay time is exhausted or the number of radiation transition excited state activator ions is 0, and the output of the up-conversion transient luminescence behavior data is the number of activator ions which occur radiation transition in the excitation and decay process.

Claims

1. A method for analyzing rare-earth doped upconversion luminescence behavior based on a random walk model, characterized in that, The method comprises the following steps: Step S1: establishing an up-conversion luminescence nano spatial structure and a luminescence center distribution configuration; Step S2: setting an ion energy level structure of a double-doped up-conversion luminescence system; Step S3: setting various energy transport processes and corresponding probabilities in the up-conversion luminescence process; Step S4: simulating a random walking process of energy in the up-conversion particle system by using a Monte Carlo method; Step S5: calculating an excitation and decay process of the up-conversion luminescence system, and outputting up-conversion transient luminescence behavior data. The step S1 comprises: Step S101: establishing an up-conversion luminescence nano spatial structure; Step S102: distributing ground state sensitizers and ground state activator ions in the up-conversion luminescence nano spatial structure in a random distribution manner; The step S3 comprises: Step S301: simplifying the energy transport processes in the up-conversion luminescence process, and only including energy migration, energy transfer, pump absorption, radiation transition and non-radiation transition processes; Step S302: calculating the probability of each energy transport process; Wherein, the pump absorption probability is obtained by the following formula: Wherein, ρ represents an excitation energy density, σ represents an ion absorption cross section, Δt represents a time step length of each random walking, and E represents a single photon energy in the medium; Wherein, the energy migration, energy transfer, radiation transition and non-radiation transition probabilities are obtained by the following formula: P i = R i Δt where R i represents the probability of each energy transport process of the excited state ion, and Δt represents the time step of each random walk. The step S4 comprises: Step S401: the ground state sensitizer ion randomly occurs pump absorption according to the pump absorption probability; Step S402: judging a nearest neighbor ion species of the excited state sensitizer ion; Step S403: calculating a random energy transport probability of the excited state sensitizer ion and the nearest neighbor ion, and the excited state sensitizer ion occurs a random energy transport process according to the probability; Step S404: the excited state activator ion randomly occurs radiation transition and non-radiation transition according to the radiation transition and non-radiation transition probabilities.

2. The method of claim 1, wherein, The excitation process is that steps S401-S404 are repeated for time steps from 0 time to the excitation stops.

3. The method of claim 1, wherein, The decay process is that steps S402-S404 are repeated for time steps from the excitation stops to the decay time is exhausted or the number of activator ions that occur radiation transition is 0.

4. The method of claim 1, wherein, The up-conversion transient luminescence behavior data is that the number of activator ions that occur radiation transition in the excitation and decay processes is counted.

5. The method of claim 1, wherein, The ion energy level structure in the step S2 can be simplified or set according to an actual energy level structure according to requirements, and the ion species can be adjusted.

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