Different local atomic arrangements have been considered to model the Moiré patterns expected in these heterostructures. The magnetic exchange interactions between both ferromagnets  spacers in the design of synthetic graphene-based antiferromagnets. In the case of h–BN, d(Fe/Co) coupling. However, there is a larger contribution of local ferromagnetic interactions. Magnetic anisotropy energies were also calculated using a fully relativistic description, and show out–of–plane easy axis for all the configurations, with remarkable net values in the range from 1 to 4 meV.Following the recent synthesis of graphene–based antiferromagnetic ultrathin heterostructures made of Co and Fe, we analyse the effect of the spacer between both ferromagnetic materials. Using density functional calculations, we carried out an exhaustive study of the geometric, electronic and magnetic properties for intercalated single Co MLs on top of Ir(111) coupled to monolayered Fe through  Overall the interlayer distances are in reasonable agreement with previous theoretical works that include van der Waals corrections and report distances between graphene and Co in the range 2.0–3.3Å  and Ir(111)/Co/h–BN/Fe heterostructures. Due to the mismatch between graphene and Ir, the minimum size of the unit cell of these ultra-thin films would require at least ~600 atoms. Instead, we have taken a simplified model structure where a commensurable minimal unit cell is considered, and explored the properties of a selected subset of the possible vertical stacking geometries for Gr/h-BN over an intercalated Co ML that follows the epitaxial structure of Ir(111). Different adsorption sites of Fe atoms over the honeycomb lattice for graphene/h-BN have been considered  and antiparallel (AFM) alignments between Fe and Co magnetizations.We have carried out a theoretical study of the geometric, electronic and magnetic structures of Ir(111)/Co/ered See . In totah-BN) materials. However, in the ultrathin limit (one ML), the hybridization between ferromagnets and the spacer heavily distorts the electronic properties of the latter, and both spacers behave as spin–polarized metals. We explored the effect of thicker spacers with bilayer and trilayer graphene, and saw a oscillatory behaviour (antiferro/ferro) and a fast decay in the strength of the magnetic coupling, as expected for metallic spacers in a RKKY model. In terms of designing new synthetic magnetic heterostructures based on 2D materials, we conclude that only ML spacers provide strong magnetic couplings, of hundreds of meV.The two different spacers between the magnetic films were taken in order to search for different type of magnetic couplings, coming from semimetallic (graphene) or insulating , and non–collinear alignments between Fe and Co layers could be obtained.For all the configurations considered, we obtain a PMA (MAE positive and in the range of ~3 meV). It is mainly dominated by the strong contribution from the underlying cobalt ML, which is enhanced by the presence of the graphene/Although our calculations are based on a very simplified model based on commensurate lattices and not the real Moiré pattern, we believe that our simulations can provide some general guidelines for the design of synthetic magnetic heterostructures based on bidimensional materials, and give some clues on the expected properties that these could have. We expect that the final properties of the Moiré superstructure will be an averaging of the local properties here obtained, which are robust on well defined regions that will have similar stacking orderings as the one considered in the model. The agreement with the available experimental results obtained for Ir(111)/Co/Gr/Fe is remarkable, and points in this direction.


We design a quantum spin heat engine using spin polarized ballistic modes generated in a strained graphene monolayer doped with a magnetic impurity. We observe remarkably large efficiency and large thermoelectric figure of merit both for the charge as well as spin variants of the quantum heat engine. This suggests the use of this device as a highly efficient quantum heat engine for charge as well as spin based transport. Further, a comparison is drawn between the device characteristics of a graphene spin heat engine against a quantum spin Hall heat engine. The reason being edge modes because of their origin should give much better performance. In this respect we observe our graphene based spin heat engine can almost match the performance characteristics of a quantum spin Hall heat engine. Finally, we show that a pure spin current can be transported in our device in absence of any charge current. From being useful in schemes for removal of excess heat in nanosystems to novel nano heat engines which produce huge amounts of power they have been one of the most productive areas of research2. Graphene as a thermoelectric material has a very small thermoelectric figure of merit ZT around 0.1–0.01, which is much smaller than the most efficient thermoelectric material Bi2Te3, see refs4. This is due to its large thermal conductance and absence of any band gap. In some recent works, a moderate improvement of the thermoelectric figure of merit ZT is noticed in graphene based systems. This improved thermoelectric figure of merit ZT of around 2.5–3 has been observed in 2D graphene systems with disorder6 or isotopes6 or nanopores7 or by nano-patterning the graphene surface3. This thermoelectric figure of merit observed in 2D graphene system is still smaller than that of the heat engine based on spin wave ferromagnetic system, see ref.2. In one of our previous works, see ref.8 we designed a QHE based on monolayer graphene system to improve the overall performance and discussed the effect of strain. In ref.8 we have only discussed the charge thermoelectric properties of strained graphene, the spin thermoelectric properties are not examined. Here, we mainly concentrate on the interplay between the roles of strain and spin flip scattering due to the magnetic impurity. In this work we prescribe a recipe to design a quantum spin heat engine(QSHE) using spin polarized ballistic modes in strained graphene. We find giant thermoelectric factors of around 50 for both charge as well as spin based transport.The efficacy of quantum heat engines(QHE) at the nanoscale has been made more than obvious in the past half decade2 wherein both the spin as well as charge thermoelectric factors are calculated along with the power and efficiency of both charge as well as spin heat engines. In ref.9 charge/spin thermoelectric properties of a carbon atomic chain sandwiched between two ferromagnetic zigzag graphene nanoribbon is studied at various range of temperatures (from 0–400 K). In ref.10 the spin and charge thermoelectric figure of merits for a ferromagnetic graphene based QHE is calculated. Finally, in ref.11 the authors calculate the thermoelectric figure of merit as well as power output in a graphene based heat engine with spin polarized edge modes. However, what is unique to our work is that the same graphene based heat engine under strain and doped with a magnetic impurity can work as a highly efficient charge as well as spin heat engine. We also show that our device generates a charge power almost twice than what is seen in it’s closest competitor, see ref.11. In some of the recent works, see refs14 the possibility of graphene to work as spin caloritronic devices is also studied, where graphene nanoribbon devices are engineered to generate large spin currents on application of a temperature difference at the two opposite edges of the system. In our device too, it can be shown that pure spin currents can be generated on application of only temperature difference. In a previous work we had dealt in detail with a quantum spin Hall based QSHE15. The charge and spin thermoelectric properties of graphene nanoribbon has also been studied in a recent paper16 in the ballistic transport regime similar to us, but in their model they have spin-orbit coupling of Rashba type instead of a magnetic impurity. In ref.16 two types of spin currents are studied, one along the direction of applied thermal bias and the other one in the transverse direction, while in this work we studied the spin currents only in the direction of the thermal bias. In refs18 it has been shown that in presence of strong spin orbit coupling and exchange interaction due to the presence of magnetic impurities, quantum anomalous Hall effect can be observed in graphene. Since intrinsic spin orbit interaction of graphene is very small, in refs18 it has been introduced via a substrate and magnetic impurities. In ref.17 it has been shown that Rashba spin splitting of magnitude 225 meV can be observed if Nickel is used as substrate. Thus for the experimental realization of our model we can utilize a different substrate with low spin orbit interaction, such as Silicon or Germanium. We also choose the magnetic impurity such that spin orbit interaction introduced by it is minimum. In ref.18 it has been shown that when magnetic impurities are distributed all over the sample then a strong Rashba spin splitting results. In our case, on the other hand we only have a single magnetic impurity located at x = 0. Thus, we can safely neglect the spin orbit interaction in our system, see Fig. 21 the thermoelectric power of a graphene nanoribbon has also been studied in presence of a strong magnetic field. In these papers, along with the Seebeck coefficient, they have also studied the Nernst coefficient, which is the measure of charge current generated along the transverse direction. Further, in refs23 the graphene monolayer system and a single Dirac particle trapped in a infinite potential well are used to design the quantum analogue of classical Otto engine and classical Carnot engine respectively. While these quantum heat engines work as the cyclic heat engines, our model consists of strained graphene layer and works as a steady state quantum heat engine. The working principle of cyclic heat engine is that after a complete cycle all the parameters return back to their initial position via a reversible process, and since a reversible process take infinite time to complete the cycle, the output power generated in these heat engines are almost zero. For steady state heat engines the output power is finite and is generated via steady state flows of microscopic particles.There have been a few papers on marrying spin transport into heat engines, mention may be made of ref.In this work, we also compare the performance of charge/spin quantum heat engine based on monolayer graphene with that based on edge modes in quantum spin Hall systems. The reason behind this comparison is that while a graphene based QSHE relies on ballistic modes, a quantum spin Hall heat engine will rely on edge modes. Edge modes are observed at the edges of topological insulators , while the best place to see ballistic modes is monolayer graphene. Edge modes are different from ballistic modes in that the transmission probability for edge mode transport is unity, i.e., there is no back reflection of the edge modes when they encounter any impurity present within the sample, while for ballistic mode transport, transmission probability can be less than unity, i.e., ballistic modes are not completely immune to backscattering due to impurity present within the sample. This comparison will give a better perspective on application of edge modes verses ballistic modes in thermoelectrics.24. A bandgap or a conduction gap present in a sample can enhance the Seebeck coefficient and thus the performance of the quantum heat engine. It can be explained in this way. In presence of a conduction gap or a band gap the electrical conductance reduces but the Seebeck coefficient increases, since Seebeck coefficient is inversely proportional to the electrical conductance  is not broken, and electron-hole symmetry. When one of the contacts of a particular system is hotter than all other contacts in that system then a electron-hole pair created at that contact which traverses to other contacts carries the excess heat energy of that contact. Now, since both electron and holes in a pair are transmitting to the other contacts, one will not get any current. To get a finite current one has to break the electron-hole symmetry, which is only possible when the transmission function is energy dependent. This energy dependent transmission function will act as a rectifier, which creates an asymmetry between electron and hole transport. Thus, to get a better thermoelectric (TE) performance one has to have a conduction gap and specific energy dependent transmission function as well. In a related paper, see ref.25 it has been concluded that a delta like transmission function in energy helps in reaching the Carnot limit in those quantum heat engines. Since MoS2 and black phosphorus both have a band gap, and if they too satisfy the delta like transmission function in energy, then quantum heat engines based on these materials will also have a large Seebeck coefficient as well as large efficiency.The reason we aim to design a quantum spin heat engine(QSHE) in graphene is that the prospect for device realization is high. Since in graphene, electronic transport can be very easily tuned by a gate voltage alone. In our model graphene QSHE too, by optimizing the parameters, heat can be converted to a spin polarized charge current as well as a pure spin current similar to ref.The manuscript is arranged as follows in section 2 we delve into the theory needed to understand the quantum spin heat engine. Next in section 3 we introduce our model which consists of a strained mono-layer of graphene embedded with a magnetic impurity. In section 4 we discuss the results of our work with a few plots of the spin and charge Seebeck coefficients, of the charge/spin thermoelectric factors and of the efficiency and power of our model spin heat engine, we also deal with the a novel application of our spin heat engine to generate pure spin current and we delve deep into the causes behind the novel effects seen by plotting the bandstructure in presence of spin flip scattering and strain. Section 5 deals with the experimental realization of our proposed device. We conclude with an experimental realization of our proposed device in section 6 along with a table which compares the spin/charge efficiency, thermoelectric factors of our device with edge mode based quantum spin Hall heat engine.K/K′) polarized as well as spin (↑/↓) polarized27. The linear dependencies can be expressed as follows29-s’ electrons  respectively, and v is for K/K′ valley, Lij with i, j ∈ 1, 2 represents the Onsager coefficients for a two terminal thermo-electric system. The electric response due to a finite temperature difference ΔT across the graphene layer is denoted as the Seebeck coefficient while the heat current generated due to the applied bias voltage s) and valley(ν) degrees of freedom for electrons in graphene the charge(K/K′) can be written as2-The aim of our work as stated in the introduction is to design a quantum spin heat engine using a strained graphene layer embedded with a magnetic impurity. It goes without saying that our device acts as a quantum charge heat engine too. For this we begin by defining the thermoelectric properties of our graphene system in the linear transport regime- the electric and heat currents are linearly proportional to the applied biases be it electric or thermal. As is well known electrons in graphene can be both valley (K and K′) gives the total charge/spin Seebeck and Peltier co-efficients-31-G0 = (e2/ℏ)(W/π2), with W being the width of graphene layer in y− direction, s, in valley v.31 ϕ is the angle at which the electron is incident, ε is the energy of the electron, f is the Fermi-Dirac distribution, μ is the Fermi energy and s electrons through strained graphene for valley ν. To calculate the Onsager coefficients Jch) and spin(Jsp) currents as well as heat current (JQ), which can be calculated from Eq.  powerJQ > 0, gives-JQ > 0, gives-To calculate maximal efficiency for the charge transported we need to calculate 0 in Eq. , this wi0 in Eq. , this agAfter determining the expressions for the quantities (both charge as well as spin) like Seebeck coefficient, Thermoelectric figure of merit, maximum power output and efficiency of respective heat engines at maximum power, we plot them in section IV. We also discuss and analyze the aforesaid plots in the same section.x < L, see Fig. x = 0. The in-plane uniaxial strain impacts the hopping between nearest neighbors and is generally delineated via a gauge vector which takes opposing signs in the two valleys (K and K′) of graphene. In the Landau gauge, the vector potential corresponding to the strain is HK = ℏvf σ.(k − t′) and HK′ = ℏvf σ*.(k + t′). Strain is denoted as t = ℏvf t′ = Ay[Θ(x) − Θ(x − L)] with Θ the Heaviside step function and vF the Fermi velocity. The first term in Eq.  - the Pauli matrices that operate on the sub-lattices A or B and k =  the 2D wave vector. The second term in Eq.  or −1/2 (spin down). For better understanding of our model we have compared our delta potential magnetic impurity with a rectangular potential barrier magnetic impurity in Fig. x = 0. A solid black color line is shown at x = 0 in Fig. x−, but is uniform in the y− direction. A magnetic quantum dot doped with few Mn+ ions can be thought of as a magnetic impurity, see refs33. We assume it to have a finite width with a translational invariance in the y− direction. This can be understood with an analogy to a rectangular potential barrier in graphene. Klein tunneling in graphene is a 2D scattering problem, see ref.34. The Klein setup has a rectangular potential barrier between x = 0 and x = L with translational invariance in the y− direction, as shown in Fig. x− direction but doesn’t affect the transmission in y− direction because the transmitting particle cannot feel the potential change in the y− direction. As one reduces the length L of the potential barrier, it becomes similar to a delta potential located at x = 0, see ref.35. Similarly, a magnetic impurity can have a finite width between x = 0 and x = L with a translational invariance in the y− direction, as shown in Fig. 32. If one decreases the width L of the impurity, it reduces to a delta function like profile affecting the transmission in the x− direction but not in the y− direction, see Fig. 33 have a magnetic impurity embedded into a graphene monolayer very similar to us. The analysis as done in refs32 is used in this work also. In ref.32 a delta potential approximation of a rectangular barrier magnetic impurity in a graphene monolayer shows that for a range of incident angles from −π/6 to π/6 the difference between the transmissions through delta potential magnetic impurity and that of the rectangular barrier magnetic impurity is quite small. In ref.32 too, the delta potential magnetic impurity is an approximation for a magnetic quantum dot with spin.A graphene sheet is lying in the x-y plane, a strain is applied to the region 0 < entclass1pt{minimaMn+ ions, oriented by an external magnetic field and put in a specific state with spin S and spin magnetic moment in z-direction m, see refs33. It can be oriented such that only a particular state-defined by S, m is occupied. Two types of scattering can happen: 1. with spin-flip (same S but m → m ± 1) or 2. without spin-flip (same S as well as m) of magnetic impurity. The rest of the states would have zero occupation probability as shown in the analysis of the scattering of electrons due to the magnetic impurity in the next subsection, see also refs32.We consider a magnetic impurity as the prototype of a magnetic quantum dot doped with few E incident at the strained graphene interface at x = 0 at an incident angle ϕ. At the interface itself we also have a magnetic impurity. The incident electron thus can be scattered due to the strained region. Further, its spin can also be affected because of the magnetic impurity. The incident electron thus can be scattered as a spin up or down electron depending on the spin and magnetic moment of the magnetic impurity.To calculate the transmission probability and from it the Onsager coefficients and the thermoelectric factors we consider a spin-up electron with energy The wave function for A-sub-lattice in each region  for K- valley can be written as:x < 0-x < L-x > L-For x component of the wave-vector in strained region is qx is substituted with kx, wherein kx = Ecosϕ/ℏvF, and the phase factor in strained region is given by tanθ = (ky − t)/qx. χm is the eigen state of z− component of spin operator of magnetic impurity Sz with Szχm = mχm, m being the corresponding eigen-value. The spin flipping mechanism is considered elastic and the sum of the z− components of the spin magnetic moment of impurity(m) and of electron(m′ = ±1/2), i.e., M = m + m′ remains conserved before and after spin-flip scattering. Following ref.36 one obtains the boundary conditions at x = 0:x = L as-The s) and the spin of magnetic impurity (S), with sz with Sz are the z-components of the spin operator of electron and magnetic impurity, respectively. S±  = Sx ± iSy, where S+ and S− are the spin raising and spin lowering operators for magnetic impurity, and s±  = sx ± isy are the same for electrons.The spin flip process is attributed to the interaction between the spin of electron (x = 0 we get-x = L we get-After substituting the wave functions (30–35) in Eqs –39, at xα = J/(4ℏvf). Equations  and reflection amplitude (rs) with s = ↑, ↓ again in a nod to probability conservation satisfying |r↑|2 + |t↑|2 + |r↓|2 + |t↓|2 = 1 for K′ valley also. Since there is no inter valley scattering, our results remain identical for K′ valley after integrating over both energy and the incident angle. So we focus on the transmission probability v = K only  of magnetic impurity. We see that though different magnetic orientations have no effect on the charge conductance, the spin conductance increases as the magnitude of m increases, but it is unaffected by the direction of m. Decreasing the spin magnetic moment m of the magnetic impurity reduces the transmission probability of spin up electrons, but increases the transmission probability for spin down electrons by the same amount. Thus the sum of transmission probabilities of spin-up and spin-down electrons remains unchanged with decreasing m. The total charge conductance remains unaffected by the changing m, but the spin conductance increases as the difference between spin up current and spin down current increases. It can also be noted that both charge as well as spin conduction gaps shown in Fig. kx axis while in the unstrained region of graphene there is no shift. Thus, there is a energy gap created in the strained region of graphene. The conduction band is related to the energy gap in kx axis. Thus, there is always a finite transmission gap obtained even for small strain value in our device and shown in Fig. J is altered. The effect of the exchange interaction J on transmission probability of incident spin up and spin down electrons is same as the effect of magnetic moment m of the magnetic impurity on it. In Fig. J), however the spin conductance increases as shown in Fig. J of the magnetic impurity increases the transmission probability of either spin-up  electron depending on the magnetic moment m of the magnetic impurity and reduces it for the spin-down  electron. In this way the sum of the transmission probabilities of spin-up and spin-down electrons remains unchanged and so does the charge conductance. However, the difference between the transmission probabilities of spin-up and spin-down electrons increases showing a increase in spin conductance with exchange coupling J. If an electron is incident at the interface of strained and unstrained region, it is refracted to the strained region with a refraction angle θ = tan−1(ky − t)/qx in K valley. So, if one increases the strain t, electrons with incident angle 0 to π/2 will refract close to the normal to the interface between the two regions and thus their transmission probability increases, but electrons with incident angle 0 to (−π/2) will refract away from the normal to interface reducing the transmission probability more and thus reducing the overall transmission (after integrating over incident angle ϕ) in the the K valley. In the K′ valley, the electrons refract in the opposite direction to that of the K valley with a refraction angle θ = tan−1(ky + t)/qx, but overall transmission probability (after integrating over incident angle ϕ) reduces with strain and is always equal to the K valley unless a magnetic field is applied at the interface to create a valley polarization, see ref.37. Increasing strain decreases both the charge as well as spin conductances. Similar to Fig. z− direction (m) and strain on the charge and spin Seebeck coefficients. In Fig. m has no effect on the charge Seebeck coefficient, but it has a huge impact on the spin Seebeck coefficient. This can be understood as follows. With changing sign of the spin magnetic moment m of the magnetic impurity from positive to negative, the transmission probability of spin-up electrons decreases while that for spin-down electrons increases by the same amount. Thus the total transmission probability of spin-up and spin-down electrons remains same with decreasing m. So, the charge Seebeck coefficient remains unaffected with changing m but spin Seebeck coefficient decreases and changes its sign from positive to negative as seen in Fig. 31. Applying strain in a graphene device can shift the Dirac points in opposite direction by opening a conduction gap without opening a bandgap. This conduction gap increases with increasing strain and so also the charge/spin Seebeck coefficients.In Fig. m, i.e., Ssp|m = −Ssp|m−, unlike the spin conductance which is independent, since Gsp = |G↑ − G↓|. In Fig. J has no effect on charge Seebeck coefficient Sch at zero strain, while the spin Seebeck coefficient Ssp increases with J, as shown in Fig. J on Sch is negligible. One thing to note in Figs EF), i.e., Sch/sp(EF) = −Sch/sp(−EF) at zero strain. In presence of finite strain while Sch(EF) = −Sch(−EF), Ssp has no symmetry with respect to sign reversal of Fermi energy, in effect change of charge carriers from electrons to holes. All this is in contrast to the spin and charge conductances which are symmetric, Gch/sp(EF) = Gch/sp(−EF), to reversal of charge carriers.From Fig. Sch near the charge neutrality point or Dirac point is because the charge carriers switch from electrons to holes. The origin of second peak in Fig. 4. In presence of strain, in addition to this unique energy dependent density of states of graphene, an asymmetry is created in the transmission probability as function of energy and that gives rise to the second peak in Fig. 8 where a similar peak is observed due to strain in graphene. It should be noted that the position of the first peak is always fixed, i.e., close to the Dirac point but changing the parameters like length of the strained region one can change the position of the second peak and thus these two peaks may merge to form a single large peak, see Fig. The sign change seen in Fig. K, see Figs 38 and Fig. 5 of ref.39. Beyond 25–30 K range, the phonon contribution increases linearly with temperature, as shown in refs39. Thus, the phonon contribution to the thermal conductance can be neglected at the temperature range 20–30 K discussed in our work.Finally, we have neglected the phonon contribution in our calculations since the phonon contribution to the thermal conductance of graphene is quite small  at low temperatures 0–30 ZT|ch and ZT|sp). From Eq.  is proportional to the product of charge and spin Seebeck (Sch and Ssp) coefficients with charge conductance Gch, i.e., ZT|sp is proportional to the polarization of the product of conductance (G) and Seebeck coefficient (S), i.e., P′ and inversely proportional to the polarization of electrons, P, see Eq. (ZT|ch we need a large charge Seebeck coefficient (Sch) and large electrical charge conductance (Gch) of the electrons while for spin thermoelectric figure of merit, we need a large spin Seebeck coefficient (Ssp) and small spin conductances (Gsp = PGch) or small polarization P of the electrons.To get large efficiency for our charge and spin heat engines we need a large charge and spin thermoelectric figure of merit  and decreases the electrical charge conductance (Gch), so as a result ZT|ch increases with strain . On the other hand for spin transport spin Seebeck coefficient increases with increasing strain while spin conductance decreases (Gsp = PGch) such that a large ZT|sp results. ZT|sp increases with strain in the overall picture however Fermi energy where maximum peak is observed is at low strain due to dependencies on other parameters. ZT|ch takes values around 50 which is quite large and similar to those obtained in ref.2. Further, ZT|sp approaches 100 which is completely unheard of. These giant charge and spin thermoelectric factors are crucial for designing highly efficient quantum charge and spin heat engines and are one of the main novelties of this work. This large charge figure of merit can be explained as follows. We have defined the figure of merit in our paper as L0 = is the Lorentz number which is a constant. So, ZT|ch is t = 110 meV = 4%strain), a large Seebeck coefficient, as large as 14(kB/e) of ref.15 of our paper with 4% strain) can be generated. So, if we divide the square of Seebeck coefficient by the Lorentz number (L0 = 2.44 ×10−8 in SI unit) we will get ZT|ch. Similarly, we can explain the huge ZT|sp as due to the large spin Seebeck coefficient.In Fig. ZT|ch will give rise to a large efficiency at maximum power, ZTch the maximum charge power delivered by our QSHE is 0.02(kbΔT)2/h, which is quite small. This is the remarkable trade off between power and efficiency in a quantum heat engine, that when efficiency is maximum the corresponding power is minimum. That’s why, we choose a set of parameters where power and efficiency both are moderately large to give the optimal performance. With a certain set of parameters, we obtain T = 10 K, however, this large ZT|ch/sp value is reached only when the strain is large. Here, for calculating the charge/spin figure of merit we have neglected the phonon contribution to the thermal conductance. At temperature t = 30 K, this phonon contribution is small but still can reduce the ZT|ch/sp, if included in the calculation. However, at T = 30 K, when the phonon contribution is very small and can be neglected, we see that ZT|ch/sp are still large (~30). Here, it is to be noted that at small temperatures . The second peak appears when the charge Seebeck coefficient Sch dominates over the charge conductance Gch, this can be verified easily because the second peak increases with increasing strain. In Fig. EF). We see that c, this is also a very large value as compared to other similar heat engines. The efficiency at maximum charge power as derived from Eq.  for EF = 18 meV but at this Fermi energy the maximum power delivered is around 0.1(kBΔT)2/h. However, at Fermi energy close to 23.5 meV the efficiency although slightly lower at 0.16ηc the maximum power output is 0.16(kBΔT)2/h. We not only need high efficiency but we need to deliver large output power too, balancing these two needs implies operating the charge heat engine at EF = 23.5 meV will satisfy both our needs. Similarly, in Fig. Ssp, which can be seen at strain t = 50 meV. The second peak appears when the spin Seebeck coefficient Ssp dominates over the factor EF). We see that kBΔT)2/h. The efficiency at maximum spin power as derived from Eq. ZT|sp and P′. Since in our case ZT|sp takes quite large values its not surprising that we have a highly efficient spin heat engine in addition to a highly efficient charge based one too. Further, we see that the efficiency c for EF = 30 meV but at this Fermi energy the maximum spin power delivered is around 0.07(kBΔT)2/h. However, at Fermi energy close to 35 meV the efficiency although slightly lower at 0.1ηc the maximum spin power output is 0.1(kBΔT)2/h. As stated before, we not only need high efficiency but we need to deliver large output spin power too balancing these two needs implies that operating the spin heat engine at EF = 35 meV will satisfy both our needs. Next, in Fig. JQ as a function of Fermi energy. In Fig. J = 0. For the second case J = finite, but the spin flip probability of the magnetic impurity F = 0 (S = m = 5/2), i.e., it acts as a non-magnetic impurity. Finally, for the third case we study the heat current in presence of a magnetic impurity, i.e., J ≠ 0, F ≠ 0 . If the polarization P of the spin conductance is different from the polarization P′ of the product of Gch and Sch, then there will be a pure spin current in our device. In Fig. In our graphene QSHE, in presence of bias voltage and temperature difference, a pure spin current can be generated by optimizing the parameters. If we set the voltage bias J = 0), (2) in presence of magnetic impurity but without spin flip  and (3) in presence of both magnetic impurity and spin flip  for both unstrained and strained graphene in Figs x < 0 region and x > L region do not contribute. The wave function for A sublattice in normal region for K-valley is mentioned in Eq. iφ) in Eq. To better understand our results we plot the energy bands for 3 cases: (1) in absence of magnetic impurity (x < 0-40 Eq. For y < 0-y < L and y > L) in y-x plane. After putting bound state conditions, the bound state wave functions for A and B-sublattice in each region  for K-valley can be written as-For y < 0-y < L-y > Ly = 0-y = L-y = 0 we get-y = L we get-r↑, r↓, a↑, a↓, b↑, b↓, t↑, t↓. After eliminating these 8 unknowns from Eqs f is a large expression, we do not explicitly write it here. The solution of Eq. kx gives the bandstructure of our system. In Fig. kx in case of unstrained graphene (t = 0) for J = 0, flip and no flip process. We see that in all cases the energy band structure is identical. Similar to Fig. kx in case of strained graphene (t = 0.1 meV) in Fig. J = 0 and no spin-flip scattering. The extra number of states help in generating large charge/spin Seebeck coefficient. Since charge and spin thermoelectric properties are proportional to the square of the charge and spin Seebeck coefficient, they increase with increasing Seebeck coefficient. In this way, strain and magnetic impurity help to enhance the performance of our graphene spin heat engine.For mentclasspt{minima41 which initiated the field of straintronics in graphene and ref.42 for a recent review, as well as experimental papers, see refs44 which deal with uniaxial strain in monolayer graphene system. There should not be much difficulty in realizing strain in a graphene system. In addition, there are theoretical works which deal with effects of magnetic impurities on electronic transport in graphene, see refs46. In ref.32 it is shown that a delta potential approximation of a rectangular barrier magnetic impurity in graphene can be a very effective model of a magnetic quantum dot(a quantum dot with spin). For a range of incident angles from −π/6 to π/6, it is seen that the difference between the transmissions through delta potential magnetic impurity and that through a rectangular barrier magnetic impurity in graphene is quite small. The graphene based system in ref.32 is very similar to our set-up, and the problem too is solved similar to ours, only difference being that there is no strain in ref.32. In refs48 an extended line defect has been studied in a graphene nanostructure experimentally. These line defects can be replaced by a magnetic quantum dot doped with Mn+ ions to realize a magnetic impurity, see refs33. Ref.33 is an experimental work which shows how doping Mn+ ions into semiconductor quantum dots realizes magnetic quantum dots. Further, magnetic quantum dots have been experimentally realized in graphene recently, see ref.49. Since in the aforesaid papers, people have worked on similar systems, thus the applied aspect of our work is evidently realizable. The amount of strain applied in our system is very small. The maximum strain used in our system is 110 meV, which is equivalent to 4% strain in graphene. In pristine graphene, maximum 20% strain can be reached without opening a band gap. All the numerical values of different parameters are physically realizable and are used in other works also, see refs31.Our proposal of a quantum heat engine based on a strained monolayer graphene layer doped with a magnetic impurity is experimentally realizable. There are many theoretical, see ref. 50. Strain can also be introduced by stretching, compressing or suspending the central region of graphene layer only without affecting the unstrained region, see ref.51 In ref.51 only the central region of the graphene sample is suspended across a wide trench in a Silion substrate, generating a finite strain which is limited to the central region alone, see figure in Box. 1(a) (at page 573 of the ref.51). Since regions 1 and region 3 of the graphene sheet are not suspended, strain in these regions will be zero. In this way, one can change the in plane hopping amplitude for the central region of the graphene sample while it remains unchanged for the unstrained regions. In our model, strain is strictly applied to the central region of the graphene sample. However, experimentally it could be possible that the finite strain is not limited to the central region only. It can gradually decrease to zero as one moves from strained to unstrained region, see ref.31. In our model, we have finite and constant strain in the central region of graphene sample, while in regions 1 and 3 it is completely zero. This consideration of the sharp drop of strain potential at the boundary between two regions is for our convenience only. We can consider a small slope for strain between the strained and unstrained regions also. However, theoretical calculations predict that the tunneling probability for electrons will not be that affected whether the strain potential is perfectly sharp or has a small slope at the boundary between strained and unstrained regions. This has also been discussed in other works, see refs52. Moreover, in recent times significant advances have been made in controlling strain in a graphene sample via strain engineering, see ref.50.In a monolayer graphene sample, a local strain can be introduced by depositing the graphene sample onto a homogeneous substrate with different geometrical patterns drawn on it . These geometrical patterns are drawn only on the central region of the substrate, thus, creating a finite strain limited to the central region of the graphene sample. In the other regions, there are no geometrical patterns drawn thus creating no strain. These different geometrical patterns, drawn on the substrate, interact differently with the graphene sheet, generating different strain profiles, see ref.15. We see that the maximum charge power for our graphene QSHE is 0.16(kBΔT)2/h, which is less than that of the quantum spin Hall heat engine (maximum charge power of 0.8(kBΔT)2/h). However, efficiency at the maximum charge power in graphene QSHE is 0.48ηc, larger than that observed in quantum spin Hall heat engine, which is 0.28ηc. Further, maximum spin power for graphene QSHE is 0.1(kBΔT)2/h while efficiency at that spin power is 0.1ηc which are less than that of the quantum spin Hall heat engine. Thus from Table We have shown in this manuscript that a strained graphene layer, embedded with a magnetic impurity, can act both as a charge as well as a spin heat engine, with higher efficiency than other similar systems. In Table


Our study confirms that upon adjusting the graphene content it is possible to tune the structure and pore morphology of the polymer derived ceramics as per the requirements.Understanding the role of graphene in the thermal stability and pore morphology of polymer derived silicon oxycarbide is crucial for electrochemical energy storage and hydrogen storage applications. Here in this work, we report the synthesis of graphene nanoplatelets dispersed silicon oxycarbide ceramics by the polymer to ceramic synthesis route. Samples containing graphene and without graphene are subjected to different pyrolysis conditions and are characterized using FT-IR, XPS, Raman spectroscopy, XRD, FE-SEM, HR-TEM, and BET. The results show that the graphene dispersed in the ceramic has undergone structural distortions upon pyrolysis and resulted in the formation of nanoclusters of graphene and turbostratic graphene. The XRD results confirm that with the incorporation of higher wt.% of GNP there is resistance to crystallization even at an exceedingly high pyrolysis temperature. The pores are bimodal in nature with specific surface area ranging between 22 and 70 m For many of these applications, porous PDCs are considered to be advantageous than their dense counterpart. For instance, it was demonstrated by Dibandjo et al. that porous silicon oxycarbide exhibited a better electrochemical response in comparison to its dense counterpart for lithium storage applications7. The porosity in these ceramics is inherently developed during the synthesis and by proper control of the processing parameters, it is possible to tailor the pore morphologies as per the requirements. Recent two review papers published on porous PDCs summarizes the various processing strategies to be adopted for getting the proper microstructure9. Among the different pore morphologies, hierarchical porosity seems to have gained the highest attention10. In our study, we have adopted a simple method by which tunable hierarchical porosity can be attained through the proper control of the precursor chemistry. However, the usage of these mesoporous ceramics for energy storage applications such as in lithium-ion batteries is limited due to its low electrical conductivity of 3 × 10−9 S/cm11.In recent years there is an outburst of research in the synthesis and characterization of polymer derived ceramics (PDC) for various functional applications such as in energy storage, lithium-ion batteries, photocatalysis, thermoelectrics and drug delivery15. In one such study by David et al. graphene oxide – silicon oxycarbide PDC system was explored as a suitable anode material for lithium-ion batteries and has shown considerably high cycling efficiency with remarkable structural stability1. Despite the aforementioned literature, there is no significant work reported so far on the addition of GNP into the silicon oxycarbide and its effect on the structural stability and pore morphology of the PDC. GNP is one to a few atomic layer thick material and can sustain remarkable current densities along with exceptional thermal and mechanical properties17. Hence, these GNP can be envisaged as suitable nano-fillers for these ceramics. The present work, therefore, tries to establish the influence of GNP in the polymeric precursor mixture and its effect on the pyrolyzed samples, both in amorphous and crystalline forms. Through this study we have tried to demonstrate the effect of GNP in terms of the different phases in the pyrolyzed ceramic samples, nature of the graphene left after pyrolysis, its impact on the turbostratic graphene in the ceramic and finally, the resulting effect on the pore morphology of the ceramic. This study also tries to reflect on the balance between having a high specific surface area (SSA) and turbostratic graphene content in the ceramic which are essential requirements for any functional application. Moreover, it is expected to give direction towards synthesizing a suitable material for potential electrochemical energy storage applications such as in lithium-ion batteries wherein a right mixture of amorphous and crystalline material with controlled porosity and graphene is expected to yield better results.In this context, further enhancement of functional properties in PDCs can be achieved by the addition of conductive nano-fillers such as carbon nanotubes, graphene oxide and graphene nanoplatelets (GNP). Recent studies have shown that the addition of nanofillers like multi-walled carbon nanotubes and graphene oxide dispersoids could lead to an enhancement of electrical conductivity by three to four orders of magnitude in these ceramics−1, 2655 cm−1 and 2688 cm−1 corresponds to that of G, 2D1 and 2D2 peaks of GNP and it could be inferred from their intensity ratio (I2D/IG ~ 0.23) that it is a few layered graphene. In addition, the presence of a single sharp D (disorder induced) peak at 1332 cm−1 indicates that the defects are present in the GNP18. In order to establish the structural stability of GNP upon exposure to high temperature, these powders were subjected to heat-treatment at 1500 °C in Ar atmosphere. The Raman spectrum of the heat-treated GNP is shown in the same figure and the peaks closely match with that of the as-received GNP ensuring its structural stability . Further, from the Fourier transform infrared spectroscopy (FT-IR) the absence of peaks corresponding to C-H (2967 cm−1) and Si-CH3 (1268 cm−1) and the presence of Si-O-Si (1100 cm−1) and Si-C (800 cm−1) peaks in the pyrolyzed samples suggests the progress in polymer to ceramic conversion  spectrum, peaks were observed at 284.28, 286.31, 288.33 eV and are assigned to Si-C (SiC4), C=O, and C-O, respectively. Again, the highest intensity for the Si-C peak indicates towards completion of the pyrolysis process and formation of the silicon oxycarbide. Similarly, for O (1s), the peaks at 531.61, 532.62, 529.28 and 534.94 eV correspond to Si-O, Si-O-Si, C-O, and C=O, respectively.A commercially available GNP was used as the nano-filler and its structure is characterized using Raman spectroscopy and is shown in Fig. ion Fig. . X-ray pion Fig. . The ele20 and (ii) presence of defects in the free carbon or turbostratic graphene produced during the polymer to ceramic conversion16. For further understanding, the peaks were deconvoluted  and D + G band are also present in the pyrolyzed samples. The presence of these bands and their position is strongly dependent on the structural integrity of the ceramic.Similar to GNP, the silicon oxycarbide ceramics with and without GNP pyrolyzed at 1500 °C also have peaks corresponding to D band and G band in their respective Raman spectrum Fig. . Howeverted Fig.  and the 2 are not so prominent in the XRD of the 1000 & 1250 °C pyrolyzed samples suggesting the predominant amorphous nature of the ceramic. In Fig. 15. Further, we can observe a decrease in peak intensity corresponding to SiC peaks for 6 wt.% GNP modified silicon oxycarbide suggesting crystallization is influenced by the presence of higher carbon content in the form of GNP. For these pyrolyzed ceramics the crystallite size of the β-SiC tends to vary from ~16 Ǻ to 19 Ǻ.The effect of pyrolysis temperature on the structural evolution of the GNP modified ceramics can be observed from the X-ray diffractogram (XRD) shown in Fig. 1. Further, the sample containing GNP with layers folded can be pictured in Fig. 3(c)21. The arrows in indigo indicate the amorphous silicon oxycarbide matrix and the rectangle in blue  characterization was carried out to visualize the structure of GNP, free carbon and their distribution in the pyrolyzed sample. The dark areas observed in Fig. lue Fig.  indicate10. A detailed Brunauer, Emmett and Teller (BET) study further confirm this. The adsorption and desorption behavior of the samples established through BET is shown in Fig. 2 adsorption isotherms inferring the mesoporous nature of the pores. Further, the microporosity is inferred through the coinciding adsorption and desorption curves till P/P0 ratios of 0.4–0.5 and the mesoporosity through the hysteresis curves beyond P/P0 ratios of 0.4–0.5. The results are consistent with the work carried out by Vakifahmetoglu et al.10. Our BET study also indicates an overall decrease in SSA with increase in pyrolysis temperature from 1000 to 1250 °C. However, SSA tend to be higher for the SiOC1500 sample. In case of GNP modified ceramics, SSA seem to decrease with increase in the pyrolysis temperature. In addition, samples containing GNP exhibited higher SSA compared to the samples without GNP at both 1000 °C and 1250 °C. However, the trend does not seem to hold good for the samples pyrolyzed at 1500 °C which have undergone crystallization  images shown in Fig. 2 hybridized carbon and the presence of D peak confirms the existence of defects possibly in the form of sp3 hybridized carbon and grain boundaries. However, after dispersing it in the polymeric mixture and subsequent pyrolysis the graphene structure revealed through Raman seems to be different. This could be associated to the presence of nanodomains of free carbon in the pyrolyzed ceramics. It has been reported in the PDC literature that pyrolysis of these C-rich ceramics can result in the formation of nanodomains of free carbon even before the phase separation process gets initiated. This free carbon could be essentially in the form of turbostratic carbon or graphene like sheets23. However, we are unable to observe the D and G peaks in the Raman spectrum for the 1000 °C and 1250 °C GNP dispersed pyrolyzed samples due to the presence of the strong background fluorescence of the amorphous ceramic24 [Refer to supplementary Fig. 2 crystallites. The selected area diffraction (SAD) pattern shown in the inset of Fig. 1.The Raman spectroscopy of the GNP reveals a few layered structure as seen in the results section. The G band is due to the bond stretching of spa) and the point defect separation distance [LD] in the pyrolyzed samples is determined using the equation developed by Cancado et al.26 and are given by equations For the 1500 °C pyrolyzed samples significant overlap of the D and G bands along with the broadening of peaks was observed in the Raman spectra. This signifies that though GNP seems to be thermally stable, defects seem to have increased due to thermal distortions. Also, it could be due to the presence of a higher concentration of free carbon or turbostratic graphene domains. The cluster size of the graphene sheets  by phase separation and (ii) the phase separated SiO2 reacting with the existing turbostratic graphene and forming SiC. This suggests that there should be an increase in the intensity of the peak of SiC for 6wt.% GNP modified ceramic. However, we have not observed an increase in the peak intensity for SiC crystallites. We believe that the only way this could have happened is the decrease in the formation of SiC by phase separation, suggesting resistance to crystallization. There are literature reports which suggests that the presence of high volume fraction of carbon can inhibit crystallization and growth of SiC30. However, further studies are required to establish this.In the case of SiOC1500 GNP modified systems, the cluster size is found to remain same (13–15 nm) with increase in GNP weight fraction. Correspondingly, the separation distance between the defects is also found to remain same (~10 nm). A similar trend in the response of cluster size with carbon nano-fiber weight fraction is reported in the work carried out by Mazo 22° Fig. 28. This The effect of GNP’s on the evolution of pores in these ceramics was studied using BET analysis. From Table In the present work, various characterization techniques were used to study the effect of GNP on the structural evolution, pore size distribution, and its morphology in the silicon oxycarbide ceramics. The Raman spectroscopy studies coupled with XRD and HR-TEM confirms that there are two types of graphene structures existing in these GNP modified PDCs. Our study suggests that the phase separation and crystallization in these PDCs is hindered at higher weight fractions of GNP. Moreover, the presence of GNP seems to have a different influence on the pore size distribution for the amorphous and crystalline ceramics. In amorphous systems, the presence of GNP resulted in an increase in SSA, whereas the reverse was observed to be true in crystalline PDC. Hence, the present work gives direction towards the synthesis of GNP dispersed PDC materials which can have the appropriate combination of porosity, pore size, SSA and balance of amorphous and crystalline phases as per the requirement.3)3SiO{(CH3)HSiO}nSi(CH3)3, viscosity: 15–40 mPa.s (20 °C), CAS Number 63148-57-2, Sigma Aldrich, USA] for getting the basic structure of ceramic, vinyl terminated polydimethylsiloxane  as a sacrificial pore former, cyclic 2,4,6,8-tetramethyl-2,4,6,8 tetravinlycyclotetrasiloxane  for increasing the crosslinking density. Hydrotalcite , was used in the as-received condition for aligning the pores. Platinum (0)-1,3-divinyl-1,1,3,3-tetramethyldisiloxane complex solution in xylene, Pt2%,  was used as the catalyst for the crosslinking reactions. Graphene  with the specific surface area (SSA) of 300 m2/g was taken for dispersing in the polymeric precursor mixture. All materials are used without further purification.To synthesize silicon oxycarbide, three polymeric precursors were chosen: a linear polymethylhydrosiloxane [PHMS, , PDMS (3.75 g) and TMTVS (2.5 g) along with LDH (2.5 g). The detailed synthesis procedure of Si-O-C PDC is as mentioned in−1 is the BWF coupling coefficient32. X-ray diffraction (XRD) was carried out using Rigaku - Ultima IV (Japan) with Cu: Kα (λ = 0.154 nm) to establish the effect of graphene on the various phases formed in pyrolyzed samples, conformance of the crystallization and effect of graphene on crystallization of the PDC. All the peaks were fitted using Voigt function and the crystallite sizes were determined using the Scherrer equation from the full width half maximum (β). High-resolution transmission electron microscopy (HR-TEM) was done using JEOL 3010 (USA) with a UHR pole piece operating at an accelerating voltage 300 kV. The samples were pulverized for the HR-TEM analysis. Field emission – Scanning Electron Microscope (FE-SEM) was carried out using FEI ApreoS (USA) at low vacuum mode and 50 Pa pressure. All the samples were polished following the standard metallurgical practice and ultrasonicated before carrying out FE-SEM. The images were taken using a secondary electron detector. Brunauer, Emmett and Teller  analysis was used for determining the SSA and Barrett-Joyner-Halenda (BJH) analysis for the determination of pore size distribution in the pyrolyzed samples. Type IV isotherms are used for the analysis of BJH plots. All the samples were pulverized before the BET and BJH analysis.The completion of polymer to ceramic conversion was established through Fourier transform- infrared spectroscopy (FT-IR) . The FTIR analysis was carried out on the samples pyrolyzed at 1000 °C. X-ray photoelectron spectroscopy (XPS) capable of depth profiling by Ar etching was carried out using Omicron Nanotechnology (UK) to determine the surface elemental composition and local environment. Raman spectroscopy was carried out using UniRAM micro-Raman mapping system (Japan) with a laser of wavelength 532 nm. Data acquisition was carried out for an exposure time of 30 s. Ferrari and Robertson have suggested an alternate Raman spectrum fitting method using Breit–Wigner–Fano (BWF) profile for G Peak and Lorentzian for D, 2D and D + G Peak. The position of G Peak is shifted in this method and is calculated using equation Supplementary Figures


Two-dimensional graphene plateletes with unique mechanical, electrical and thermo-physical properties could attract more attention for their employed as reinforcements in the production of new metal matrix nanocomposites (MMNCs), due to superior characteristics, such as being lightweight, high strength and high performance. Over the last years, due to the rapid advances of nanotechnology, increasing demand for the development of advanced MMNCs for various applications, such as structural engineering and functional device applications, has been generated. The purpose of this work is to review recent research into the development in the powder-based production, property characterization and application of magnesium, aluminum, copper, nickel, titanium and iron matrix nanocomposites reinforced with graphene. These include a comparison between the properties of graphene and another well-known carbonaceous reinforcement (carbon nanotube), following by powder-based processing strategies of MMNCs above, their mechanical and tribological properties and their electrical and thermal conductivities. The effects of graphene distribution in the metal matrices and the types of interfacial bonding are also discussed. Fundamentals and the structure–property relationship of such novel nanocomposites have also been discussed and reported. Composite materials contain two or more distinct constituents which are engineered or naturally occurring, with remarkably various properties  ,2,3,4,5.Moreover, it has been found that MMCs reinforced by particles give competitive economical and isotropic characteristics, while those reinforced by continuous fibre offer the highest strength. Given that fact, to strengthen the metallic matrices, CFs can be replaced by inexpensive graphite particulates, especially in the case of MMCs developed for sliding bearing and electrical brush applications ,18. To oFurthermore, by decreasing the size of reinforcement (to nano-size), it is possible to improve some of the weak properties of metal matrix nanocomposites (MMNCs), like poor ductility, elongation, etc. ,25,26,27In recent years, several studies have been focused on carbonaceous nanomaterials, like graphene and carbon nanotubes (CNTs), as an important category of novel materials for various applications, such as structural and functional ones. This increasing interest in their applications is mainly because of their simultaneous exceptional mechanical properties and excellent electrical and thermal conductivities . TherefoThere are some motivations to develop MMNCs reinforced by graphene. It was found that several factors from the inherent characteristics of graphene pertaining to its dispersion and the interface of matrix/graphene play key roles in the strengthening of MMNCs reinforced by graphene. Indeed, the introduction of graphene into a metallic matrix and synthesizing a homogeneous, dispersed structure with common production processes remain open to researchers as a challenge. Those challenges are mainly due to the significant difference in the density of graphene and metallic matrices, larger interfacial bonding than carbon nanotubes and a reaction at the interface of matrix and reinforcement due to the reactivity of some metallic materials ,68,69. A2- hybridized carbon atoms which has a high packing density in a honeycomb lattice. Graphene has been attracting worldwide attention due to some of its unique properties. It is known as the strongest material measured so far, the most stretchable crystal, the stiffest material and the most thermally conductive material [Graphene is a single atomic layer of spmaterial ,71. Grapmaterial . Researcmaterial . Howevermaterial ,75, chemmaterial ,77, and material ,79. Thermaterial ,81.As can be observed in Generally speaking, graphene can be synthesized by two various methods, including top-down and bottom-up methods. The bottom-up technique consists of the unzipping of carbon nanotubes, epitaxial growth technique  and chemNevertheless, according to the literature, so far, the development of the dispersion graphene strengthened MMNCs with no damage in the intrinsic structures is the most significant challenge. The most essential characteristics of graphene are listed in The story of MMNCs reinforced by carbonaceous nanomaterial started with MMNCS reinforced by carbon nanotube. Indeed, there is a growing body of literature that has studied carbon nanotubes since their discovery in 1991 by Iijima . Carbon CNTs have unique characteristics—mechanical and physical characteristics that make them very interesting materials. Therefore, they would be a promising candidate for the reinforcing phase in MMNCs, offering several advantages, such as inherent stability at high temperatures, superior thermal and electrical conductivity coming from the metallic matrices and enhanced performance of MMNCs in industrials parts. Nonetheless, it is very challenging to incorporate CNTs into metallic matrices due to their tendency to form agglomerates within the metallic matrices. In addition, owing to a significant discrepancy in the surface tensions of carbon nanotubes and metals, the wetting of carbon nanotubes by molten metals is poor, and accordingly, results in the formation of a poor interfacial bonding .Despite the superior mechanical features of SWNTs, they are not yet extensively employed as reinforcement due to their expensive production and purification methods. However, MWNTs are composed of some centred layers, and they are easier to be produced ,90.In recent years, with the progress of nanotechnology, the cost of MWNTs, in particular, those of an industrial grade, has been noticeably decreased. Accordingly, to manufacture the MMNCs with favorable physical and mechanical features, carbonaceous nanofillers with affordable prices, are essential reinforcements. The characteristics of carbonaceous reinforcements are compared in According to the latest findings in the literature, to forecast and evaluate the mechanical performance of graphene, both experimental approaches and theoretical simulations have been used; e.g., numerical simulation tools, such as equivalent-continuum, quantum mechanical and atomistic modelling . The You2 were prepared by Lin et al. through the centrifugation technique, and achieved the best elastic modulus, of ~13.5 GPa [Experimentally, Lee et al. have determined the Young’s modulus (1.02 TPa) and intrinsic tensile strength  of single-layer graphene by employing the nanoindentation of the atomic force microscope (AFM) . Further13.5 GPa .A list of practical Young’s modulus and tensile strength of different carbonaceous nanomaterials is shown in −1·K−1) for SLG, which was prepared by mechanical cleavage at ambient temperature [−1·K−1 at ambient temperature [In carbonaceous nanomaterials, thermal energy is transported by phonons’ conduction. The thermal conductivity (k) of single-layer graphene (SLG) was measured by Baladin et al. through confocal micro-Raman spectroscopic measurements. They reported extremely high thermal conductivity , thermomechanical processing and powder metallurgy (PM) have been employed to produce metallic monolithic alloys and/or composite materials ,124,125.As expected, obtaining a homogeneous dispersion of filler by simply mixing carbonaceous nanomaterials with metal powders is entirely poor. However, it is possible to get a better dispersion of reinforcement particles by using high energy milling methods, such as ball milling and mechanical alloying. Since a long-duration ball milling process can damage the crystallinity of carbonaceous materials, the processing steps should be carefully carried out to avoid introducing any defects in these materials . Morsi eMechanical alloying (MA) is known as a solid state method to process the materials in the powder form at ambient temperature and produce MMNCs with an appropriate distribution of reinforcement particles and a fine microstructure . In addiIn order to disperse the bundled CNTs, the organic surfactant can be utilized alternatively, whereas in the case of graphene, no surfactant is necessary ,136.After the mixing, consolidation is the key step in the fabrication of MMNCs. One of the advanced powder-based manufacturing methods of MMNCs is the LPBF process, which is one of the most important AM processes . In factOn the other hand, to obtain denser products through the conventional sintering, a long time of processing and a high temperature are required, whereas low-temperature processing and a short sintering time are offered by using SPS for consolidating nanocomposite powders ,142. As Moreover, it is possible to achieve ultrafine or submicron-grains in the MMNCs nanocomposites reinforced by graphene by using severe plastic deformation (SPD) processes, such as equal-channel angular pressing (ECAP) ,148. ECAIn general, it is proven that in MMNCs, the strenghening effect can be obtained via different strengthening mechanisms, such as load transfer, Orowan looping, thermal expansion coefficient mismatching and Hall–Petch strengthening (grain refinement) ,152,153.The load transfer strengthenig effect is the first possible mechanism for strengthening in MMNCs. In this mechanism, load transfer is from the soft matrix to a high strength reinforcement, and this mechanism depends on the interface between the matrix and reinforcing particles. In principle, stronger interfacial bonding could result in high load transfer, and accordingly increase the final strength of the nanocomposite. However, it was reported that in the MMNs consisting of low reinforcement content, the load transfer effect does not contribute significantly in the strengthening of MMNCs .Orowan looping is another important strengthening mechanism which is based on the restriction of dislocation movement by nano-scale reinforcement . In factIn addition, the significant difference between the thermal expansion coefficient of metal matrices and reinforcing particles, in particular graphene, can result in the prismatic punching of dislocations at the interface, consequently leading to the strengthening of the nanocomposite .Grain refinement is one of the significant effects of the reinforcement addition and it relies on the particle size and volume fraction on nanoparticles, so that the grain size decreases either by increasing the volume fraction of reinforcement or decreasing the size of reinforcement .2O3, SiC, CNTs, diamond, graphene and graphite. In order to produce aluminum matrix nanocomposites, two common methods have been employed which are reinforced by particles on a large scale: One is powder metallurgy process (solid state), and another one is casting (liquid state). In the literature, several efforts have been carried out to produce AMNCs through powder metallurgy for investigating their mechanical characteristics [2O3 and Al–SiC via powder metallurgy method and casting [2O3 by SPS [4C by SPS and reactive infiltration [Aluminum matrix nanocomposites (AMNCs) are known as one of the main metal matrix nanocomposites, which commonly utilized in different applications, such as aerospace and transportation, while they seldom used for electronic packaging applications . The superistics ,160,161. casting ; Al–Al2O3 by SPS ; Al nano3 by SPS ; Al–B4C ltration ,165; Al–ltration ; Al–MWNTltration ; and Al–ltration ,168,169.Since the strengthening effect of various reinforcements on AMNCs is a key factor in their structural applications, extensive research has focused on this subject  although, its values were more than the monolithic alloy and less than the reinforced nanocomposite with 0.5–3 wt.% graphene. By comparison between The variation of thermal conductivity and the Vickers hardness of Al-GNPs nanocomposites in the presence of graphene have been studied by Saboori et al. . They re4C3, as a consequence of poor controlling of the early synthesizing conditions, intensive deterioration of the mechanical characteristics of the nanocomposites occurred [Recently, Saboori et al.  have faboccurred .Lately, 1 wt.% GNPs reinforced 2009Al nanocomposites were synthesized via a combination of PM and multi-pass friction stir processing (FSP) by Zhang et al. . Their mChen et al.  reported2. They have also reported that graphene nanoplatelets have a significant strengthening effect on the Mg-matrix nanocomposite [In addition, as can be observed in the TEM image , for GNPomposite .Rashad et al. ,181,182 This improvement of ductility in that work was explained by the level of porosity in the fabricated pure Mg and nanocomposites . It is aThe effect of carbon nanotubes and graphene on the mechanical characteristic of pure Mg have been studied by Rashad et al. . They reIn another work , AZ61 maRecently, Meng et al.  producedAs reported in the literature, Mg-Al-GNPs nanocomposites showed better mechanical characteristics in comparison with the Mg-Al-CNT nanocomposites. These improved mechanical characteristics were explained by the high specific surface area, better nanofiller matrix adhesion ascending from the crumpled surface and the 2D structure of graphene nanoplatelets . MoreoveFor the first time, in 2019, AZ91D Mg alloy-GNPs nanocomposites were produced via a thixomolding process  by Chen Graphene-reinforced copper matrix nanocomposites were produced approximately at the same time as graphene-reinforced aluminum matrix nanocomposites. Chen et al.  fabricatLi et al.  studied The mechanical and wear characteristics of copper-based nanocomposites containing varying content of graphene nanosheets (GNSs) and graphite (Gr) have been compared by Li et al. . They foRecently, other researchers  have fabSince copper and graphene nanoplates have various densities, one of the issues to the homogeneous distribution of GNPs in the Cu-matrix is the production of GNPs–Cu nanocomposites. For this reason, in 2019, Shao et al.  fabricatSome researchers compared the electrical conductivity of GNPs-copper nanocomposites after the hot isostatic press and as-sintered ones. They revealed that the electrical conductivity of nanocomposites considerably increases after HIP, which causes a decrease of the void content of GNPs–Cu nanocomposites. The electrical conductivity of GNPs–Cu nanocomposites produced by various methods is summarized in 3Al alloy [A noticeable amount of research has been aimed to investigate the effect of embedding graphene into the MMCs. The main applications of those nanocomposites, including their use as photo-catalysts, and in transformation materials, biosensors, energy storage, and so on. Those metal matrix nanocomposites consist of Ag-doped graphene-silver matrix nanocomposites , graphenAl alloy , graphenAl alloy , GNNs–AgAl alloy  and otheIn recent years, MMNCs have been considered potential materials to be employed in different sophisticated industrial applications. Therefore, more research and learning has been carried out to explore the advances in their structures and possible applications. Indeed, over the last decade, a growing body of literature on MMNCs has shown that these materials, in particular reinforced by graphene, show great potential to be used in a range of engineering applications and lightweight alloys. Indeed, owing to their unique properties, such as high strength and toughness at high temperatures and low density, MMNCs are recognized as favourable materials to be employed in applications where conventional engineering materials, such as steel, are used. Although MMNCs often have low ductility and interior fracture toughness, they present remarkably higher stiffness and mechanical strength compared to matrix alloys. Therefore, selecting suitable reinforcement, characteristics and production techniques play vital roles in the resulting MMNCs .As mentioned earlier, graphene-reinforced MMNCs have shown excellent features, such as high specific strength, good wear resistance, good thermal conductivity, excellent mechanical and optical properties, low thermal expansion coefficients and excellent corrosion resistance. Consequently, these nanocomposites are mainly utilized to make multifunctional products, and are used in some industries, including the automobile, sports, aerospace, chemical and electronics industries. For example, copper is the most suitable material to be employed in high-end applications like integrated circuits, electric switches and electronic packages, mainly due to its unique properties like high electrical and thermal conductivity, fatigue resistance, workability and corrosion resistance. Nonetheless, its poor mechanical properties, together with its high CTE limit its applications. Salvo et al. and Saboori et al. have shown that through the addition of graphene it would be possible to simultaneously enhance the mechanical, thermal and electrical conductivities of the Cu/GNPs nanocomposite, while reducing its CTE, making this nanocomposite the most suitable material to be used in the electric switches and electronic packages ,192. DorDespite all the efforts that have been undertaken to develop new nanocomposite materials reinforced by graphene, still the production of these new materials in the industrial scale is faced by several challenges, like the uniform dispersion of graphene within the metallic matrix and interfacial bonding between graphene/metallic matrix.Owing to the unique characteristics, such as a high aspect ratio, an exceptional high elastic modulus and strength, and superior electrical and thermal conductivity, graphene could attract more attention to be utilized in the production of MMCs as a reinforcement to improve their mechanical, thermo-physical and wear properties.It is found that the production of these nanocomposites is faced with several challenges, such as the distribution of graphene, undesirable reaction, poor interfacial bonding and preferred orientation of graphene during the fabrication step.It is very interesting to point out that, according to the literature, some of the issues can be related to the nature of starting materials, whereas the rest can be attributed to the production process. Those related to the production process can often be addressed by altering the fabrication technique or by employing post-processing methods. More problematic, are the issues attributed to the matrix’s composition and reinforcement composition, its stability and the distribution of particulates, especially if they are in the nano-scale range.The majority of the literature has been concentrated on the production, and some studies have targeted the mechanical performance, thermophysical and self-lubricating characteristics.AM techniques, that are layer-wise manufacturing processes, are rapidly growing in the fabrication of MMNCs.In general, it is revealed that the mechanical performance of MMCs was significantly improved through the addition of graphene.The in-depth microstructural analysis demonstrated that the most effective strengthening mechanisms in the MMCs reinforced by graphene phenomena are a mismatch in the thermal expansion of the matrix and graphene and an Orowan looping mechanism.Despite the mechanical properties and microstructural analysis of MMCs reinforced by graphene that has been investigated intensively, their tribology is rarely considered and studied.The available investigations have shown that graphene can significantly decrease the wear rates and friction coefficients of MMCs with respect to the monolithic material.The improvement in the tribological features of MMCs, as well as the mechanical and thermophysical properties, strongly depend on the final graphene content.At higher graphene contents, graphene tends to form big agglomerates that leave some defects, like porosity, in the MMCs after fabrication, and accordingly deteriorate the final properties of MMCs.There is a critical limit for the final graphene content, until which the properties of MMCs can be improved, whereas at higher graphene contents, all the properties, such as thermal conductivity, electrical conductivity, mechanical properties and tribological behavior, are deteriorated. In addition to the graphene content, its other characteristics, such as the size of reinforcement, and spatial distribution, have shown to effect mechanical and tribological properties.It should be noted that these topics still bring a marked challenge to the materials scientists, and it would be worth mentioning that the production of metal matrix nanocomposites with a uniform distribution of graphene, strong interfacial bonding, without unfavorable reactions and with better isotropic properties is still a challenging topic.Each metallic material has some poor characteristics that limit its industrial applications. Theoretically and also on the lab-scale, it was found that through the addition of graphene, it would be possible to address those weakness and accordingly broad their application.Despite all the efforts that have been undertaken in the development of new MMNCs reinforced by graphene, the industrialization of these materials are faced with several challenges, and need more attempts.In this review paper, we have thoroughly reviewed recent research into the development in the powder-based production, property characterization and application of magnesium, aluminum, copper, nickel, titanium and iron matrix nanocomposites reinforced with graphene. According to the review results, the conclusions can be drawn as follows:


Tardbp gene, which encodes the C-terminal region of TDP-43. Homozygous TDP-∆C mice showed embryonic lethality, indicating that the N-terminal domain of TDP-43 alone is not sufficient for normal development. In contrast, heterozygous TDP-∆C mice developed normally but exhibited age-dependent mild motor dysfunction with a loss of C-boutons, large cholinergic synaptic terminals on spinal α-motor neurons. TDP-∆C protein broadly perturbed gene expression in the spinal cords of aged heterozygous TDP-∆C mice, including downregulation of Notch1 mRNA. Moreover, the level of Notch1 mRNA was suppressed both by TDP-43 depletion and TDP-∆C expression in Neuro2a cells. Decreased Notch1 mRNA expression in aged TDP-∆C mice was associated with the age-dependent motor dysfunction and loss of Akt surviving signal. Our findings indicate that the N-terminal region of TDP-43 derived from TDP-∆C induces the age-dependent motor dysfunction associated with impaired Notch1-Akt axis in mice.Intracellular mislocalization of TAR DNA-binding protein 43 (TDP-43), a nuclear DNA/RNA-binding protein involved in RNA metabolism, is a pathological hallmark of amyotrophic lateral sclerosis (ALS). Although the aggregation-prone, TDP-43 C-terminal domain is widely considered as a key component of TDP-43 pathology in ALS, recent studies including ours suggest that TDP-43 N-terminal fragments (TDP-∆C) may also contribute to the motor dysfunction in ALS. However, the specific pathological functions of TDP-43 N-terminal fragments in mice have not been elucidated. Here, we established TDP-∆C knock-in mice missing a part of exon 6 of murine The online version of this article (10.1186/s40478-019-0776-5) contains supplementary material, which is available to authorized users. Amyotrophic lateral sclerosis (ALS) is an adult-onset neurodegenerative disease characterized by a progressive loss of upper and lower motor neurons in the spinal cord, brain stem, and cerebral cortex, leading ultimately to fatal skeletal muscle paralysis . AberranTARDBP, have been identified in familial and sporadic ALS, suggesting that TDP-43 dysfunction leads to motor neuron degeneration [TDP-43 is a ubiquitously expressed DNA/RNA-binding protein shuttling between nucleus and cytoplasm, and plays a critical role in multiple aspects of RNA metabolism such as splicing, stability, transport, translation, and microRNA maturation , 27. TDPneration , 33, 37.TDP-43 mutations are located in the C-terminal domain [Most known ALS-linked l domain , 37. In l domain , 24, 35,l domain , 25, 35.l domain . Therefol domain . In the l domain . These rTardbp gene region encoding the C-terminal domain (a part of exon6) is eliminated. Heterozygous TDP-ΔC mice exhibited mild age-dependent motor dysfunction with a loss of C-boutons, large cholinergic synaptic terminals on motor neurons, and suppression of Notch1 − Akt signaling. Suppression of Notch1 mRNA was induced both by TDP-43 depletion and TDP-∆C expression. Collectively, these results suggest that N-terminal fragments of TDP-43 also contribute to ALS pathology associated with impaired Notch1-Akt signaling pathway.To examine the role of N-terminal TDP-43 fragments in vivo, we established TDP-ΔC knock-in mice (TDP-∆C mice), in which Tardbp genomic DNA was isolated from C57BL/6 N mouse. The gene targeting vector was designed to replace a part of its exon 6, encoding amino acid 274–414 of murine TDP-43, with 3 × FLAG tag to delete C-terminal portion of TDP-43. We used the genomic fragment spanning from exon 2 to intron 5 and the fragment of 3′-UTR of exon 6 (both the arms are approximately 6 kb) for constructing targeting vectors, respectively. A neomycin resistant gene (neor) gene cassette with FRT sequences and diphtheria toxin (DTA) cassette were also inserted for positive and negative selection, respectively. The gene targeting was performed by using embryonic stem (ES) cells derived from C57BL/6 N (RENKA) as described elsewhere [Murine lsewhere . The corRotarod tests were performed as previously reported . In brieFollowing primary antibodies were used in this study: anti-choline acetyl transferase (ChAT) , anti-Kv2.1(K89/34) , anti-TDP-43(3H8)  anti-TDP-43(A260) , anti-FLAG M2 , anti-glial fibrillary acidic protein (GFAP) , anti-Iba1 , anti-fibrillarin , anti-heat shock protein 110 (Hsp110) , anti-phospho Akt (Ser473) , anti-pan Akt , anti-β-actin . Anti-TDP-43  was raised against a chemically synthesized N-terminal peptide of human TDP-43 a.a. 1–10 conjugated to keyhole limpet hemocyanin (KLH), and rabbit sera following the immunization was used at 1:200 for immunoblotting.Immunofluorescence analyses were performed as described elsewhere , 44. BriEscherichia coli HST02 (Takara Bio) to express with C-terminal EGFP tag. Site-directed mutagenesis on TDP-43 cDNA was performed according to the instruction of QuikChange site-directed mutagenesis kit . Mouse neuroblastoma Neuro2a (RRID: CVCL_0470) cells were maintained in Dulbecco’s Modified Eagle’s’ Medium (DMEM) containing 4.5 g/L glucose supplemented with 10%(v/v) fetal bovine serum (FBS), 100 U/mL penicillin, and 100 μg/mL streptomycin  at 37 °C in a humidified chamber containing 5% CO2. The cells were differentiated in DMEM supplemented with 2%(v/v) FBS and 2 mM N6,2′-O-dibutyryladenosine-3′,5′- cyclic monophosphate  for indicated times. Transfection was performed using Lipofectamine 2000 reagent according to the manufacturer’s instruction (Thermo Fisher).The full-length or ΔC (a.a. 1–273) human TDP-43 cDNA was inserted into pEGFP-N1 vector  using seamless ligation cloning extract (SLiCE) , 51 from15 primer. Quantitative reverse transcription (RT)-PCR was performed using SYBR Premix Ex Taq II (Takara Bio) according to the manufacturer’s protocol in Thermal Cycler Dice Real Time System II (Takara Bio). Relative mRNA expression was calculated by standard curve method normalized to β-actin gene (Actb) and relative to the control samples. All samples were run in duplicate. The primers that were used in this study are listed as follows:Total RNA of mouse spinal cords was isolated with Trizol reagent , followed by further purification using RNeasy Mini Kit  according to the manufacturer’s instruction. The concentration of total RNA was determined by a spectrophotometer , and RNA quality was assessed with the RNA integrity determined by microfluidics-based capillary electrophoresis (RNA integrity number (RIN) ≧ 8.0) . cDNA was synthesized from 1 μg of the purified RNA using PrimeScript II 1st strand Synthesis Kit (Takara Bio) and an oligo-(dT)Notch1; 5′-TGGATGACCTAGGCAAGTC-3′ and 5′-TTCTGCATGTCCTTGTTGG-3′, for Hes1; 5′-TGCCAGCTGATATAATGGAG-3′ and 5′-CTTTGATGACTTTCTGTGCTC-3′, for Pten; 5′-AAGGGAGTCACAATTCCCA-3′ and 5′-ACTGAGGATTGCAAGTTCC-3′, for quantifying mRNA levels of β-actin; 5′-GCTATGTTGCTCTAGACTTCG-3′ and 5′-GGATTCCATACCCAAGAAGG-3′.for specific detection of mRNA levels of endogenous wild-type TDP-43; 5′-AAAAGGAAAATGGATGAGACAGATG-3′ and 5′-AACTGAGCAGGATCTGAAAGACTATTT-3′, for quantifying mRNA levels of both TDP-ΔC and endogenous wild-type TDP-43; 5′-ATGATAAGGTTGCCCAGTC-3′ and 5′-TACTGTTACCAAACCCACC-3′, for 2, 0.5 mM dithiothreitol (DTT), 0.4%(v/v) PMSF, pH 7.4), and incubate for 15 min on ice. After centrifugation at 600×g, 4 °C for 5 min, the pellet was resuspended in ice-cold hypertonic buffer , 30%(v/v) glycerol, 0.5 mM DTT, 0.4%(v/v) PMSF, pH 7.4), and incubated for 30 min at 4 °C with gentle agitation to induce osmotic shock. After centrifugation at 18,000×g, 4 °C for 30 min, the resultant supernatant was collected as a nuclear fraction.Tissues were fractionated as previously reported  with sliTissues from control or TDP-∆C mice were sonicated in ice-cold lysis buffer , 1%(v/v) Triton X-100) supplemented with protease inhibitor cocktail (Roche). The lysates were centrifuged at 15,000×g, 4 °C for 5 min to remove insoluble debris. Total protein concentration was measured using Bio-rad protein assay kit as described in manufacturer’s instructions . Aliquots of 20 μg proteins were analyzed by sodium dodecyl sulfate- polyacrylamide electrophoresis (SDS-PAGE), and transferred to a polyvinylidene difluoride membrane . After blocking with 2% Bovine Serum Albumin (BSA) in TBS-T  Tween-20, pH 7.4), the membrane was incubated with the primary antibodies diluted in TBS , followed by incubation with horseradish peroxidase (HRP)-conjugated anti-rabbit  or anti-mouse  secondary antibodies. The membranes were visualized with Immobilon Crescendo Western HRP substrate  according to the manufacturer’s protocol. Densitometric analyses were performed by using an image analyzer LAS-4000 mini  with the equipped software .Microarray analyses were performed using purified total RNA of the 700 days-old TDP-∆C mouse spinal cords or their littermate non-transgenic controls. cRNAs were prepared using Low Input Quick-Amp Labeling Kit (Agilent) according to the manufacturer’s instruction, and were hybridized with mouse SurePrint G3 mouse GE microarray 8 × 60 K Ver.2.0 chips (Agilent). Data were subsequently normalized and analyzed using GeneSpring 13.0 software (Agilent). Pathway analyses were conducted using the Single Experiment Pathway analysis feature in GeneSpring 13.0 (Agilent). The moderated t-test was utilized, and 1.2-fold cut-off value was used to select significantly changed transcripts.t-test, for comparison between 2 groups, or one-way ANOVA followed by the post-hoc Tukey’s multiple comparison t-test, for comparison among more than 3 groups, respectively. All the statistical analyzes were carried out using GraphPad Prism software .Time-course of rotarod score was analyzed by two-way ANOVA and Mann-Whitney non-parametric u-test. All the data from immunofluorescence, semi-quantitative immunoblotting and quantitative RT-PCR were analyzed by an unpaired The previous studies identified various N-terminal TDP-43 fragments with different length of the remaining C-terminal domain produced by the calpain-dependent cleavage , 47. AmoIn TDP-∆C mice, the expression pattern of TDP-ΔC proteins across various tissues including the central nervous system was similar to the one of wild-type TDP-43 protein Fig. a, b. To To examine whether there were any motor phenotypes in TDP-ΔC mice, we performed a rotarod test monthly from 2 to 20 months of age Fig. a. AlthouWe then examined whether the aberrant subcellular localization of TDP-∆C is involved in the synaptic loss observed in aged TDP-∆C mice. In TDP-∆C protein, both nuclear localization signal (NLS) and nuclear export signal (NES) are retained, which may be responsible for their subcellular localization in each compartment Figs. a, 4a. Inq-value < 0.05 in moderate t-test)  induced mutagenesis [TDP-∆C perturbed the expression levels of around 4,000 genes in mouse spinal cords; unexpectedly, however, a limited number of these genes are regulated by TDP-43 according to the studies screening for its neuronal RNA targets , 30, 45.strategy  or Tardbagenesis . In thesagenesis , 39. Furagenesis , 46.Pten ameliorated the repeat-mediated toxicity [Among deregulated genes in aged TDP-∆C mouse spinal cord, we identified downregulation of Notch1 − Akt signaling genes during age-dependent motor dysfunction. Moreover, we found that the levels of pAkt and total Akt gradually decreased with age in the nervous tissue of TDP-∆C mice. Although direct evidence for the link between chronic downregulation of pAkt and age-dependent motor dysfunction in TDP-∆C mice was not provided in this study, there are several studies suggesting the potential role of impaired Akt signaling in ALS pathomechanisms. Indeed, reduced Notch1 signaling was also observed in a C9orf72-linked ALS model . The Ptetoxicity . Moreovetoxicity , 42. We toxicity , most ofGene ablation of the TDP-43 C-terminal domain in mice (TDP-∆C mice) induced age-dependent motor dysfunction associated with loss of cholinergic synapses on spinal α-motor neurons. This age-dependent motor impairment was also associated with suppression of Notch1-Akt signaling pathway. Our data uncovered a detrimental role of N-terminal TDP-43 fragments in ALS pathology in mice, associated with suppression of Akt surviving signal.Additional file 1:Figure S1. Complete deletion of C-terminal domain from TDP-43 induced severe neurotoxicity in cultured neuronal cells. Figure S2. Anti-TDP-43(3H8) recognizes C-terminal domain of TDP-43. Figure S3. No gender differences were found in rotarod scores in aged WT and TDP-∆C mice. Figure S4. Neuro-muscular junction (NMJ) was not affected in aged TDP-∆C mice. (PDF 893 kb)Additional file 2:Table S1. Genes upregulated (> 1.2 fold) in 700-day-old TDP-∆C mouse spinal cord. (XLSX 499 kb)Additional file 3:Table S2. Genes downregulated (> − 1.2 fold) in 700-day-old TDP-∆C mouse spinal cord. (XLSX 41 kb)Additional file 4:Table S3. Affected genes (> 1.2 or < − 1.2 fold) among known TDP-43 regulatory targets in 700-day-old TDP-∆C mouse spinal cord. (XLSX 20 kb)