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First-principles Study And High-throughput Prediction On The Transport Properties Of Some Thermoelectric Materials

Posted on:2021-04-07Degree:DoctorType:Dissertation
Country:ChinaCandidate:Z Z ZhouFull Text:PDF
GTID:1481306290484344Subject:Materials Physics and Chemistry
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The increasingly serious energy crisis and drastic climate change have driven the need for developing environmentally friendly technology for power generation.Thermoelectric(TE)module has been regarded as one of the most promising alternatives which can harvest and recover waste heat and directly convert it into electrical energy.The conversion efficiency of a TE material is determined by a dimensionless figure of merit ZT =S2?T/?,where T,S,?,and ? are the absolute temperature,Seebeck coefficient,electrical conductivity,and thermal conductivity(including electronic and phonon contributions),respectively.However,the intercoupling between the transport coefficients make it difficult to significantly improve the TE performance.In this thesis,we give a first-principles study on the electronic,phonon,and thermoelectric transport coefficients of several bulk and two-dimensional materials.In addition,using compressed sensing technique,we propose physically meaningful descriptors to efficiently predict the relaxation time of tetradymite compounds.The main content of the thesis includes:The TE transport properties of quaternary tetradymite BiSbSeTe2 are studied by combining first-principles approach and Boltzmann transport theory.Unlike the binary counterpart Bi2Te3,we observe a pair of Rashba splitting bands caused by the absence of inversion center.Such unique characteristic can lead to a large Seebeck coefficient even at relatively high carrier concentration.Besides,we find an ultralow lattice thermal conductivity,especially along the interlayer direction,which should be traced to the extremely small phonon relaxation time mainly rooted from the mixed covalent bonds.Consequently,a considerable ZT value of 2.0 can be realized at 500 K,indicating that the unique lattice structure of quaternary BiSbSeTe2 induced by isoelectronic substitution is an advantage to achieve high TE performance.We demonstrate through high-level first-principles approach and accurate solution of Boltzmann transport equation that an ultrahigh n-type power factor of 13.8 m W m-1 K-2 and a highest ZT value of 2.2 can be achieved in the heavy-fermion UN2 compound at 700 K.Such excellent TE performance arises from the large degeneracy of the heavy conduction band coupled with weak electron-phonon interaction,which is governed by the strong Coulomb correlation among the partially filled U-5f electrons of the face-centered cubic structure.Collectively,our theoretical study suggests that the energetic UN2 is a promising alternative to efficient radioisotope power conversion,and also uncovers an underexplored area for TE research.We present a comparative first-principles study on the TE transport properties of graphene-like BP,BAs,and BSb monolayer.It is found that the strong bond anharmonicity in BAs and BSb monolayers would dramatically suppress the phonon relaxation time but hardly influences that of electrons.As a result,both systems exhibit comparable power factors with that of BP monolayer but much lower lattice thermal conductivities.Accordingly,a peak ZT value above 3.0 can be found in both BAs and BSb monolayers at optimized carrier concentration.On the other hand,the TE performance of BP monolayer is greatly suppressed by its large lattice thermal conductivity,which can be dramatically decreased by constructing a bilayer structure owing to the presence of van der Waals interactions.Consequently,a maximum p-type ZT value of 1.8 can be obtained along the x-direction at 1200 K,which is amazingly high for systems only consisting of light elements.Moreover,we find almost identical p-and n-type ZT of 1.6 in the y-direction,which is very desirable in the fabrication of TE modules with comparative efficiencies.We design a hybrid graphene/h-BN superlattice monolayer and investigate its TE properties within the framework of density functional theory and Boltzmann transport equations.Compared with that of pristine graphene,the lattice thermal conductivity of such superlattice structure is more than two orders of magnitude lower owing to the significantly increased phonon scattering originated from the mixed covalent bonds.Besides,the obvious valley anisotropy near the Fermi level leads to an ultrahigh power factor along the zigzag direction,which gives an n-type ZT as high as 2.5 at 1100 K.Furthermore,it is interesting to find that the TE performance of p-type system can be increased to be comparable with that of n-type system by appropriate substitution of nitrogen atom with phosphorus,which could suppress the lattice thermal conductivity but nearly have no influence on the hole transport.Based on first-principles method taking into account the quasiparticle GW correction and Boltzmann transport theory,we demonstrate that the giant power factor of the Zr Se3 monolayer should be attributed to the grooved bands near the conduction band edge.Combined with the low lattice thermal conductivity obtained via solving the phonon Boltzmann transport equation,a large n-type ZT value of 2.4 can be obtained at 800 K in the ZrSe3 monolayer,indicating that the systems with unique grooved bands may be potential TE materials.By adopting a recently developed data analytics approach named SISSO(Sure Independence Screening and Sparsifying Operator),we propose an efficient and physically interpretable descriptor to predict the carrier relaxation time,using tetradymites as prototypical examples.Without any input from first-principles calculation,our descriptor contains only several elemental properties of the constituent atoms,and could be utilized to fast and reliably predict the relaxation time of a substantial number of tetradymites compounds with arbitrary stoichiometry.
Keywords/Search Tags:first-principles, Boltzmann transport theory, electron-phonon coupling, thermoelectric materials, two-dimensional materials, compressed sensing, high-throughput prediction
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