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ORIGINAL RESEARCH article

Front. Phys., 23 February 2021
Sec. Statistical and Computational Physics
Volume 8 - 2020 | https://doi.org/10.3389/fphy.2020.568554

Fractional-Order Investigation of Diffusion Equations via Analytical Approach

  • 1School of Mathematics and Information Sciences, Neijiang Normal University, Neijiang, China
  • 2Department of Mathematics, Abdul Wali khan University Mardan, Mardan, Pakistan
  • 3Department of Mathematics, Near East University TRNC, Mersin, Turkey
  • 4Department of Mathematics, Pir Mehr Ali Shah Arid Agriculture University, Rawalpindi, Pakistan
  • 5Department of Mathematics, Faculty of Arts and Sciences, Cankaya University, Ankara, Turkey
  • 6Institute of Space Sciences, Magurele-Bucharest, Romania

This research article is mainly concerned with the analytical solution of diffusion equations within a Caputo fractional-order derivative. The motivation and novelty behind the present work are the application of a sophisticated and straight forward procedure to solve diffusion equations containing a derivative of a fractional-order. The solutions of some illustrative examples are calculated to confirm the closed contact between the actual and the approximate solutions of the targeted problems. Through analysis it is shown that the proposed solution has a higher rate of convergence and provides a closed-form solution. The small number of calculations is the main advantage of the proposed method. Due to a comfortable and straight forward implementation, the suggested method can be utilized to nonlinear fractional-order problems in various applied science branches. It can be extended to solve other physical problems of fractional-order in multiple areas of applied sciences.

1 Introduction

Fractional calculus (FC) can be considered as one of the extensions of traditional ordinary calculus. The roots of FC dates back to about 300 years. The idea of fractional calculus arises from the fact that Leibniz used a notation for the nth derivative in his publication as (dny/dxn). LHo^pital posed a question to Leibniz about the derivative of order (1/2) in 1,695 [1]. In nature derivatives that involve an integer order are local, whereas a fractional order is nonlocal. The mathematical groundwork for derivatives of a fractional order was laid through the combined efforts of several mathematicians such as Caputo, Miller and Ross, Liouville, Riemann, Podlubny, and others. Later on, several mathematicians devoted their work to this area. Fractional calculus has attracted a lot of interest due to its potential implementations in different scientific areas such as biology, viscoelasticity, engineering, fluid mechanics, and other fields of science [210].

From the above applications, mathematicians implemented different methods to solve some vital differential equations of fractional-orders (FDEs), particularly partial differential equations of fractional-orders (FPDEs). FPDEs are considered to be basic mathematical techniques used to model various physical phenomena more precisely than integer-order. The non-linear FPDEs determine different phenomena in engineering and applied sciences. In particular, non-linear FPDEs are the best sources to be utilize in different fields such as material sciences, physics, thermodynamics, chemistry, chemical kinetics, and several other basic processes [1121]. Various methods to solve FDEs are used in the literature, such as the variational iteration method [22], the modified Adomian decomposition method (MADM) [23], the differential transformation method (DTM) [24], the optimal homotopy asymptotic method (OHAM) [25], and the homotopy perturbation method (HPM) [26].

In 2006, Daftardar-Gejji et al. introduced the iterative method (IM) to solve functional equations [27, 28]. IM is used to solve DEs, of both integers as well fractional-order. In this article, we used the Shehu transform method and the iterative technique and introduced a new technique called the Iterative Shehu Transform method [ISTM] to find the approximate solution of FPDEs. It has been observed that the suggested technique has a simple and effective implementation compared to other existing methods such as the homotopy perturbation method, the variational iteration method, and the Laplace Adomian decomposition method [29].

The diffusion equation is a PDE which expresses the phenomenon which transforms atoms or molecules from a higher construction. The Fick’s law of diffusion was first described by the physiologist Adolf Fick. Later on, Fick’s law was converted into the Diffusion equation. Researchers generalized the classical Diffusion law to obtain modified Diffusion equations such as the hybrid classical wave equation and slow diffusion [30]. There are several diffusion equation implementations such as filtration, electromagnetism, geochemistry, phase transition, cosmology, biochemistry, acoustics, and dynamics of biological groups [31].

In the present paper, we apply ISTM to solve diffusion equations of the form.

(1) One-dimensional diffusion equation having fractional-order of the form:

αμτα=2μϑ2μϑ+μ2μϑ2μ2+μ,0<α1,τ0.

Have the initial values

μ(ϑ,0)=g(ϑ).

(2) Two-dimensional diffusion equation with a fractional-order of the form:

αμτα=2μϑ2+2μζ2,0<α1,τ0.

Have the initial values

μ(ϑ,ζ,0)=g(ϑ,ζ).

(3) Three-dimensional diffusion equation with a fractional-order of the form:

αμτα=2μϑ2+2μζ2+2μω2,0<α1,τ0.

Have the initial values

μ(ϑ,ζ,ω,0)=g(ϑ,ζ,ω).

2 Preliminaries

In this section, important definitions regarding the present research article are presented.

2.1 Definition

Fractional derivative Caputo operator is given as [7, 8].

Dφαμ(ϑ,φ)=1Γ(kα)0φ(φρ)kα1μ(k)(ϑ,ρ)dρ,k1<αk,kN.

2.2 Definition

Riemann-Liouville fractional integral [7, 8].

Iταg(ϑ,τ)=1Γ(α)0τ(τρ)α1g(ϑ,ρ)dρ,ρ>0(k1<αk),kN.

Iτα stands for fractional integral.

2.3 Definition

Shehu transform (ST) [3235].

Shehu transform function in set A is expressed by

A={ν(τ):,ρ1,ρ2>0,|ν(τ)|<Me(|τ|/ρi),,if τ[0,).(1)

The Shehu transformation which is defined by S(.) for a function ν(τ) is expressed as [3235].

S{ν(τ)}=V(s,μ)=0ν(τ)e(sτ/μ)(τ)dτ,τ>0 s>0.(2)

The Shehu transformation of a function ν(τ) is V(s,μ): then ν(τ) is called the inverse of V(s,μ) which is defined as

S1{V(s,μ)}=ν(τ),for τ0, S1is inverse Shehu transformation.(3)

2.4 Definition

The fractional derivative in terms of ST [3235].

The ST of the fractional derivative is described as

S{ν(α)(τ)}=sαuαV(s,u)k=0n1(su)ν(k)(0)αk1,0<αn.(4)

2.5 Definition

The Mittag-Leffler function is expressed as [7, 8].

Eα(ω)=q=0ωqΓ(αq+1),(αC,Re(α)>0).

A further generalization of the equation is given in the form of

Eα,β(ω)=q=0ωqΓ(αq+β);(α,βC,Re(α)>0),Re(β)>0).

3 Idea of ISTM

In this section, we use ISTM to determine the general solution of fractional-order diffusion equations [3235].

Dταμ(ϑ,ζ,τ)+Rμ(ϑ,ζ,τ)+Nμ(ϑ,ζ,τ)=g(ϑ,ζ,τ),k1<αk,kN,(5)
μi(ϑ,ζ,o)=hi(ϑ,ζ),i=0,1,2,,m1,(6)

where Dταμ(ϑ,ζ,τ) is the fractional-order Caputo derivative, k1<αk, explained by Eq. 5, R is a linear and N a non-linear operator while p(ϑ,ζ,τ) is an analytic function.

Applying Shehu transformation to Eq. 5, we obtain [3235].

S[Dταμ(ϑ,ζ,τ)]+S[Rμ(ϑ,ζ,τ)+Nμ(ϑ,ζ,τ)]=S[g(ϑ,ζ,τ)],

and by using the property of Shehu transform differentiation, we obtain

S[μ(ϑ,ζ,τ)]=uαsαk=0m1(su)α1kμk(ϑ,ζ,0)+uαsαS[g(ϑ,ζ,τ)]uαsαS[Rμ(ϑ,ζ,τ)+Nμ(ϑ,ζ,τ)].(7)

On taking inverse Shehu transform of Eq. 7, we obtain [3235].

μ(ϑ,ζ,τ)=S1[uαsα(k=0m1sα1kμk(ϑ,ζ,0)+S[g(ϑ,ζ,τ)])]S1[uαsαS[Rμ(ϑ,ζ,τ)+Nμ(ϑ,ζ,τ)]].(8)

Now, applying the iterative method,

μ(ϑ,ζ,τ)=i=0μi(ϑ,ζ,τ).(9)

In Eq. 9, the linear and nonlinear parts R and N, respectively, are decomposed as follows Eqs. 11, 12

R(i=0μi(ϑ,ζ,τ))=i=0R[μi(ϑ,ζ,τ)],(10)
N(i=0μi(ϑ,ζ,τ))=N[μ0(ϑ,ζ,τ)]+i=1{N(k=0iμk(ϑ,ζ,τ)N(k=0i1μk(ϑ,ζ,τ))}.(11)

Substituting Eqs. 9, 11 in Eq. 8 yields

i=0μi(ϑ,ζ,τ)=S1[uαsα(k=0m1(us)α1kμk(ϑ,ζ,0)+S[g(ϑ,ζ,τ)])]S1[uαsαS[i=0R[μi(ϑ,ζ,τ)]+N[μ0(ϑ,ζ,τ)]+i=1{N(k=0iμk(ϑ,ζ,τ))N(k=0i1μk(ϑ,ζ,τ))}]].(12)

We set

μ0(ϑ,ζ,τ)=S1[uαsα(k=0m1(us)α1kμk(ϑ,ζ,0)+uαsαL(g(ϑ,ζ,τ)))],(13)
μ1(ϑ,ζ,τ)=S1[uαsαS[R[μ0(ϑ,ζ,τ)]+N[μ0(ϑ,ζ,τ)]],(14)
μm+1(ϑ,ζ,τ)=S1[uαsαS[R(μm(ϑ,ζ,τ)){N(k=0mμk(ϑ,ζ,τ))N(k=0m1μk(ϑ,ζ,τ))}]],m1.(15)

However, the m-term approximate solution of Eqs. 5, 6 is determined by

μ(ϑ,ζ,τ)μ0(ϑ,ζ,τ)+μ1(ϑ,ζ,τ)+μ2(ϑ,ζ,τ)++μm(ϑ,ζ,τ),m=1,2,(16)

4 Applications

In this section, we apply ISTM to obtain the solution of fractional order diffusion equation to show the accuracy and appropriateness of ISTM to solve exactly nonlinear FPDEs.

4.1 Example

Consider diffusion equation of fractional-order in one-dimension [31].

αμτα=2μϑ2μϑ+μ2μϑ2μ2+μ,0<α1,τ>0.(17)

Have the initial values

μ(ϑ,0)=expϑ.(18)

Applying Shehu transformation to Eq. 17, we obtain

S[μ(ϑ,τ)]=1sexpϑ+uαsα[S(2μϑ2μϑ+μ2μϑ2μ2+μ)].(19)

Taking inverse Shehu transform of Eq. 19

μ(ϑ,τ)=expϑ+S1[uαsα{S(2μϑ2μϑ+μ2μϑ2μ2+μ)}].(20)

Using iterative technique

μ0(ϑ,τ)=expϑ,μ1(ϑ,τ)=S1[uαsα{S(2μ0ϑ2μ0ϑ+μ02μ0ϑ2μ02+μ0)}]=expϑταΓ(α+1),
μ2(ϑ,τ)=S1[uαsα{S(2μ1ϑ2μ1ϑ+μ12μ1ϑ2μ12+μ1)}]=expϑτ2αΓ(2α+1),
μ3(ϑ,τ)=S1[uαsα{S(2μ2ϑ2μ2ϑ+μ22μ2ϑ2μ22+μ2)}]=expϑτ3αΓ(3α+1),
μ4(ϑ,τ)=S1[uαsα{S(2μ3ϑ2μ3ϑ+μ32μ3ϑ2μ32+μ3)}]=expϑτ4αΓ(4α+1).

Thus, in the form of a series, the analytical solution can be written as

μ(ϑ,τ)=μ0(ϑ,τ)+μ1(ϑ,τ)+μ2(ϑ,τ)+μ3(ϑ,τ)+μ3(ϑ,τ)+,=expϑ+expϑταΓ(α+1)+expϑτ2αΓ(2α+1)+expϑτ3αΓ(3α+1)+expϑτ4αΓ(4α+1)+,
μ(ϑ,τ)=expϑ(1+ταΓ(α+1)+τ2αΓ(2α+1)+τ3αΓ(3α+1)+τ4αΓ(4α+1)+,),μ(ϑ,τ)=expϑk=0(tα)kΓ(kα+1)=expϑEα(tα).

When α=1, the ISTM solution is

μ(ϑ,τ)=expϑk=0(t)kk!.(21)

The exact solution is:

μ(ϑ,τ)=exp(ϑ+τ).

4.2 Example

Consider diffusion equation of fractional-order in two-dimension [31].

αμτα=2μϑ2+2μζ2,0<α1,τ0,(22)

Having initial values

μ(ϑ,ζ,0)=(1ζ)expϑ.(23)

Applying Shehu transformation to Eq. 22, we obtain

S[μ(ϑ,ζ,τ)]=1s(1ζ)expϑ+uαsα[S(2μϑ2+2μζ2)].(24)

Taking inverse Shehu transform of Eq. 24

μ(ϑ,ζ,τ)=(1ζ)expϑ+S1[uαsα{S(2μϑ2+2μζ2)}].(25)

Using an iterative technique

μ0(ϑ,ζ,τ)=(1ζ)expϑ,μ1(ϑ,ζ,τ)=S1[uαsα{S(2μ0ϑ2+2μ0ζ2)}]=(1ζ)expϑταΓ(α+1),
μ2(ϑ,ζ,τ)=S1[uαsα{S(2μ1ϑ2+2μ1ζ2)}]=(1ζ)expϑτ2αΓ(2α+1),
μ3(ϑ,ζ,τ)=S1[uαsα{S(2μ2ϑ2+2μ2ζ2)}]=(1ζ)expϑτ3αΓ(3α+1),
μ4(ϑ,ζ,τ)=S1[uαsα{S(2μ3ϑ2+2μ3ζ2)}]=(1ζ)expϑτ4αΓ(4α+1).

Thus, in the form of a series, the analytical solution can be written as

μ(ϑ,ζ,τ)=μ0(ϑ,ζ,τ)+μ1(ϑ,ζ,τ)+μ2(ϑ,ζ,τ)+μ3(ϑ,ζ,τ)+μ3(ϑ,ζ,τ)+,μ(ϑ,ζ,τ)=(1ζ)expϑ+(1ζ)expϑταΓ(α+1)+(1ζ)expϑτ2αΓ(2α+1)+(1ζ)expϑτ3αΓ(3α+1)+(1ζ)expϑτ4αΓ(4α+1)+,
μ(ϑ,ζ,τ)=(1ζ)expϑ(1+ταΓ(α+1)+τ2αΓ(2α+1)+τ3αΓ(3α+1)+τ4αΓ(4α+1)+,),μ(ϑ,ζ,τ)=(1ζ)expϑk=0(tα)kΓ(kα+1)=(1ζ)expϑEα(tα).

When α=1, the ISTM solution is

μ(ϑ,ζ,τ)=(1ζ)expϑk=0(t)kk!.(26)

The exact solution in closed form is:

μ(ϑ,ζ,τ)=(1ζ)exp(ϑ+τ).

4.3 Example

Consider diffusion equation of fractional-order in two-dimension [31].

αμτα=2μϑ2+2μζ2,0<α1,τ0.(27)

Having initial values

μ(ϑ,ζ,0)=exp(ϑ+ζ).(28)

Applying Shehu transformation to Eq. 27, we obtain

S[μ(ϑ,ζ,τ)]=1sexp(ϑ+ζ)+uαsα[S(2μϑ2+2μζ2)].(29)

Taking inverse Shehu transform of Eq. 29

μ(ϑ,ζ,τ)=exp(ϑ+ζ)+S1[uαsα{S(2μϑ2+2μζ2)}].(30)

Using iterative technique

μ0(ϑ,ζ,τ)=exp(ϑ+ζ),μ1(ϑ,ζ,τ)=S1[uαsα{S(2μ0ϑ2+2μ0ζ2)}]=2exp(ϑ+ζ)ταΓ(α+1),
μ2(ϑ,ζ,τ)=S1[uαsα{S(2μ1ϑ2+2μ1ζ2)}]=4exp(ϑ+ζ)τ2αΓ(2α+1),
μ3(ϑ,ζ,τ)=S1[uαsα{S(2μ2ϑ2+2μ2ζ2)}]=8exp(ϑ+ζ)τ3αΓ3α+1,
μ4(ϑ,ζ,τ)=S1[uαsα{S(2μ3ϑ2+2μ3ζ2)}].=16exp(ϑ+ζ)τ3αΓ4α+1,

Thus, in the form of a series, the analytical solution can be written as

μ(ϑ,ζ,τ)=μ0(ϑ,ζ,τ)+μ1(ϑ,ζ,τ)+μ2(ϑ,ζ,τ)+μ3(ϑ,ζ,τ)+μ4(ϑ,ζ,τ)+,μ(ϑ,ζ,τ)=exp(ϑ+ζ)+2exp(ϑ+ζ)ταΓ(α+1)+4exp(ϑ+ζ)τ2αΓ(2α+1)+8exp(ϑ+ζ)τ3αΓ(3α+1)+16exp(ϑ+ζ)τ4αΓ(4α+1)+,
μ(ϑ,ζ,τ)=exp(ϑ+ζ)(1+2ταΓ(α+1)+(2τα)2Γ(2α+1)+(2τα)3Γ(3α+1)+(2τα)4Γ(4α+1)+,),μ(ϑ,ζ,τ)=exp(ϑ+ζ)k=0(tα)kΓ(kα+1)=(1ζ)expϑEα(tα).

When α=1, then the ISTM solution is

μ(ϑ,ζ,τ)=exp(ϑ+ζ)k=0(t)kk!.(31)

The exact solution is:

μ(ϑ,ζ,τ)=exp(ϑ+ζ+τ).

4.4 Example

Consider diffusion equation of fractional-order in three-dimension [31].

αμτα=2μϑ2+2μζ2+2μω2,0<α1,τ0.(32)

Having initial values

μ(ϑ,ζ,ω,0)=sinϑsinζsinω.(33)

Applying Shehu transformation to Eq. 32, we obtain

S[μ(ϑ,ζ,ω,τ)]=1ssinϑsinζsinω+uαsα[S(2μϑ2+2μζ2+2μω2)].(34)

Taking inverse Shehu transform of Eq. 34

μ(ϑ,ζ,ω,τ)=sinϑsinζsinω+S1[uαsα{S(2μϑ2+2μζ2+2μω2)}].(35)

Using iterative technique

μ0(ϑ,ζ,ω,τ)=sinϑsinζsinω,μ1(ϑ,ζ,ω,τ)=S1[uαsα{S(2μ0ϑ2+2μ0ζ2+2μ0ω2)}]=3sinϑsinζsinωταΓ(α+1),
μ2(ϑ,ζ,ω,τ)=S1[uαsα{S(2μ1ϑ2+2μ1ζ2+2μ1ω2)}]=(3)2sinϑsinζsinωτ2αΓ(2α+1),
μ3(ϑ,ζ,ω,τ)=S1[uαsα{S(2μ2ϑ2+2μ2ζ2+2μ2ω2)}]=(3)3sinϑsinζsinωτ3αΓ(3α+1),μ4(ϑ,ζ,ω,τ)=S1[uαsα{S(2μ3ϑ2+2μ3ζ2+2μ3ω2)}]=(3)4sinϑsinζsinωτ4αΓ(4α+1).

Thus, in the form of a series, the analytical solution can be written as

μ(ϑ,ζ,ω,τ)=μ0(ϑ,ζ,ω,τ)+μ1(ϑ,ζ,ω,τ)+μ2(ϑ,ζ,ω,τ)+μ3(ϑ,ζ,ω,τ)+μ4(ϑ,ζ,ω,τ)+,=sinϑsinζsinω3sinϑsinζsinωταΓ(α+1)+(3)2sinϑsinζsinωτ2αΓ(2α+1)(3)3sinϑsinζsinωτ3αΓ(3α+1)+(3)4sinϑsinζsinωτ4αΓ(4α+1)+,
μ(ϑ,ζ,ω,τ)=sinϑsinζsinω(13ταΓ(α+1)+(3τα)2Γ(2α+1)+(3τα)3Γ(3α+1)+(3τα)4Γ(4α+1)+,).

When α=1, then the ISTM solution in a closed form:

μ(ϑ,ζ,ω,τ)=sinϑsinζsinω(13τ+(3τ)22!+(3τ)33!+(3τ)44!+,).

The exact solution is:

μ(ϑ,ζ,ω,τ)=exp3τsinϑsinζsinω.(36)

5 Conclusion

In the present article, the fractional view analysis is analyzed using an efficient analytical technique. Fractional derivatives are expressed in a Caputo sense. The present method is tested to solve diffusion equation of fractional-order. After investigation, we show that the present method is the best tool to use to solve nonlinear fractional order problems. The exact and obtained solutions in closed contact has verified the reliability of the present technique. Moreover, the graphical representation has confirmed the convergence of the approximate solutions toward the exact solutions and provide the closed form solutions of the targeted problems. The convergence phenomenon has confirmed the reliability of the suggested method.if

FIGURE 1
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FIGURE 1. Exact solution (A) Exact (B) ISTM solutions of example one at α=1. In Figure 1, the Exact and ISTM solutions of Example 1, at α=1 are plotted by using sub-graphs A and B respectively. The graphical representation has shown the closed contact between the exact and ISTM solutions.

FIGURE 2
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FIGURE 2. ISTM solution of example 1 (C) at various fractional-order α (D) the fractional-order solutions at ξ=0.5. In Figure 2, the ISTM solutions at different values of α are presented. The sub-graphs (C) and (D) represents 3D and 2D plots of fractional order solutions of Example 1. The convergence of the fractional solutions towards integer solutions is observed.

FIGURE 3
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FIGURE 3. Exact solution (A) Exact (B) ISTM solutions of example 2 at α=1. In Figure 3, the Exact and ISTM solutions of Example 2, at α=1 are plotted by using sub-graphs A and B respectively. The graphical representation has shown the closed contact between the exact and ISTM solutions of Example 2.

FIGURE 4
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FIGURE 4. ISTM solution of example 2 (C) at various fractional-order α (D) the fractional-order solutions at ξ=0.5. In Figure 4, the ISTM solutions of Example 2 at different values of α are presented. The sub-graphs (C) and (D) represents 3D and 2D plots of fractional order solutions of Example 2. The convergence of the fractional solutions towards integer solutions is observed.

FIGURE 5
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FIGURE 5. ISTM solution of example 3 (A) at various fractional-order α (B) the fractional-order solutions at ξ=0.5. In Figure 5, the ISTM solutions of Example 3 at different values of α are presented. The sub-graphs (A) and (B) represents 3D and 2D plots of fractional order solutions of Example 3. The convergence of the fractional solutions towards integer solutions is observed.

FIGURE 6
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FIGURE 6. Exact solution (A)(B) ISTM solutions of example 4 at α=1. In Figure 6, the Exact and ISTM solutions of Example 4, at α=1 are plotted by using sub-graphs A and B respectively. The graphical representation has shown the closed contact between the exact and ISTM solutions of Example 4.

FIGURE 7
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FIGURE 7. (C) Error graph (D) ISTM solutions of example 4 at α=0,5. In Figure 7, the sub-graphs (C) and (D) represent the ISTM Error and solution graphs of Example 4 respectively. The error graph has confirmed the higher accuracy of ISTM.

Data Availability Statement

Publicly available datasets were analyzed in this study. This data can be found here: N/A.

Author Contributions

Conceptualization, HK and SM; Methodology, HL; Software, LM; Validation, DB and HK; Formal Analysis, SM; Investigation, HK; Resources, HK; Writing—Original Draft Preparation, SM; Writing—Review and Editing, HK; Visualization, DB; Supervision, HK, DB; Project Administration, HL; Funding Acquisition, HL and LM

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding

Key Project of Science and Technology Plan of Sichuan Provincial Science and Technology Department (2017JY0199), Project of Education Department of Sichuan Province (JG2018-736).

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Keywords: iterative shehu transform method, diffusion equations, caputo operator, mittag-leffler function, fractional differential equation

Citation: Liu H, Khan H, Mustafa S, Mou L and Baleanu D (2021) Fractional-Order Investigation of Diffusion Equations via Analytical Approach. Front. Phys. 8:568554. doi: 10.3389/fphy.2020.568554

Received: 10 June 2020; Accepted: 29 December 2020;
Published: 23 February 2021.

Edited by:

Andrea Gabrielli, Roma Tre University, Italy

Reviewed by:

Ervin Kaminski Lenzi, Universidade Estadual de Ponta Grossa, Brazil
Haci Mehmet Baskonus, Harran University, Turkey

Copyright © 2021 Liu, Khan, Mustafa, Mou and Baleanu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Hassan Khan, hassanmath@awkum.edu.pk

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