{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T19:39:16Z","timestamp":1784230756988,"version":"3.55.0"},"reference-count":89,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2024,11,2]],"date-time":"2024-11-02T00:00:00Z","timestamp":1730505600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000181","name":"U.S. Air Force Office of Scientific Research (AFOSR)","doi-asserted-by":"publisher","award":["FA2386-21-1-4060"],"award-info":[{"award-number":["FA2386-21-1-4060"]}],"id":[{"id":"10.13039\/100000181","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Materials"],"abstract":"<jats:p>We performed machine learning (ML) simulations and density functional theory (DFT) calculations to search for materials with low lattice thermal conductivity, \u03baL. Several cadmium (Cd) compounds containing elements from the alkali metal and carbon groups including A2CdX (A = Li, Na, and K; X = Pb, Sn, and Ge) are predicted by our ML models to exhibit very low \u03baL values (&lt;1.0 W\/mK), rendering these materials suitable for potential thermal management and insulation applications. Further DFT calculations of electronic and transport properties indicate that the figure of merit, ZT, for the thermoelectric performance can exceed 1.0 in compounds such as K2CdPb, K2CdSn, and K2CdGe, which are therefore also promising thermoelectric materials.<\/jats:p>","DOI":"10.3390\/ma17215372","type":"journal-article","created":{"date-parts":[[2024,11,4]],"date-time":"2024-11-04T10:57:20Z","timestamp":1730717840000},"page":"5372","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Machine Learning and First-Principle Predictions of Materials with Low Lattice Thermal Conductivity"],"prefix":"10.3390","volume":"17","author":[{"given":"Chia-Min","family":"Lin","sequence":"first","affiliation":[{"name":"Department of Physics, University of Alabama at Birmingham, Birmingham, AL 35294, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abishek","family":"Khatri","sequence":"additional","affiliation":[{"name":"Department of Physics, University of Alabama at Birmingham, Birmingham, AL 35294, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4653-0408","authenticated-orcid":false,"given":"Da","family":"Yan","sequence":"additional","affiliation":[{"name":"Department of Computer Sciences, Indiana University Bloomington, Bloomington, IN 47405, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9931-615X","authenticated-orcid":false,"given":"Cheng-Chien","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Physics, University of Alabama at Birmingham, Birmingham, AL 35294, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"eaak9997","DOI":"10.1126\/science.aak9997","article-title":"Advances in thermoelectric materials research: Looking back and moving forward","volume":"357","author":"He","year":"2017","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.mtphys.2017.06.001","article-title":"New trends, strategies and opportunities in thermoelectric materials: A perspective","volume":"1","author":"Liu","year":"2017","journal-title":"Mater. Today Phys."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"021303","DOI":"10.1063\/1.5021094","article-title":"A practical field guide to thermoelectrics: Fundamentals, synthesis, and characterization","volume":"5","author":"Zevalkink","year":"2018","journal-title":"Appl. Phys. Rev."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"180902","DOI":"10.1063\/1.5092525","article-title":"New horizons in thermoelectric materials: Correlated electrons, organic transport, machine learning, and more","volume":"125","author":"Urban","year":"2019","journal-title":"J. Appl. Phys."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"12642","DOI":"10.1007\/s10853-020-04949-0","article-title":"Review of current high-ZT thermoelectric materials","volume":"55","author":"Wei","year":"2020","journal-title":"J. Mater. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"6170","DOI":"10.1002\/er.5313","article-title":"Inorganic thermoelectric materials: A review","volume":"44","author":"Hasan","year":"2020","journal-title":"Int. J. Energy Res."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Zoui, M.A., Bentouba, S., Stocholm, J.G., and Bourouis, M. (2020). A review on thermoelectric generators: Progress and applications. Energies, 13.","DOI":"10.3390\/en13143606"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1016\/j.egyr.2019.12.011","article-title":"A comprehensive review of Thermoelectric Generators: Technologies and common applications","volume":"6","author":"Jaziri","year":"2020","journal-title":"Energy Rep."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"13902","DOI":"10.1021\/ja507945h","article-title":"High thermoelectric performance realized in a BiCuSeO system by improving carrier mobility through 3D modulation doping","volume":"136","author":"Pei","year":"2014","journal-title":"J. Am. Chem. Soc."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"10604","DOI":"10.1039\/C5TC01731A","article-title":"Enhanced thermoelectric performance of n-type Cu0.008Bi2Te2.7Se0.3 by band engineering","volume":"3","author":"Lee","year":"2015","journal-title":"J. Mater. Chem. C"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"408","DOI":"10.1021\/cm502570b","article-title":"Increasing the thermoelectric figure of merit of tetrahedrites by co-doping with nickel and zinc","volume":"27","author":"Lu","year":"2015","journal-title":"Chem. Mater."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3234","DOI":"10.1038\/s41467-021-23569-z","article-title":"Entropy engineering promotes thermoelectric performance in p-type chalcogenides","volume":"12","author":"Jiang","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"105303","DOI":"10.1016\/j.mssp.2020.105303","article-title":"Review of experimental approaches for improving zT of thermoelectric materials","volume":"121","author":"Ma","year":"2021","journal-title":"Mater. Sci. Semicond. Process."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"10099","DOI":"10.1021\/jacs.2c02017","article-title":"Insights into low thermal conductivity in inorganic materials for thermoelectrics","volume":"144","author":"Ghosh","year":"2022","journal-title":"J. Am. Chem. Soc."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"16002","DOI":"10.1209\/0295-5075\/acdb98","article-title":"XMoSiN2 (X = S, Se, Te): A novel 2D Janus semiconductor with ultra-high carrier mobility and excellent thermoelectric performance","volume":"143","author":"Ding","year":"2023","journal-title":"Europhys. Lett."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"3559","DOI":"10.1039\/D1EE00442E","article-title":"Charting lattice thermal conductivity for inorganic crystals and discovering rare earth chalcogenides for thermoelectrics","volume":"14","author":"Zhu","year":"2021","journal-title":"Energy Environ. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1021\/acs.jpca.0c08103","article-title":"Lattice thermal conductivity prediction using symbolic regression and machine learning","volume":"125","author":"Loftis","year":"2020","journal-title":"J. Phys. Chem. A"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"110938","DOI":"10.1016\/j.commatsci.2021.110938","article-title":"Lattice thermal conductivity of half-Heuslers with density functional theory and machine learning: Enhancing predictivity by active sampling with principal component analysis","volume":"202","author":"Tomic","year":"2022","journal-title":"Comput. Mater. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1005","DOI":"10.1088\/0370-1328\/77\/5\/309","article-title":"The law of Wiedemann and Franz","volume":"77","author":"Chester","year":"1961","journal-title":"Proc. Phys. Soc."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"205901","DOI":"10.1103\/PhysRevLett.115.205901","article-title":"Prediction of low-thermal-conductivity compounds with first-principles anharmonic lattice-dynamics calculations and Bayesian optimization","volume":"115","author":"Seko","year":"2015","journal-title":"Phys. Rev. Lett."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"3926","DOI":"10.1038\/s41467-021-24208-3","article-title":"High thermoelectric figure of merit of porous Si nanowires from 300 to 700 K","volume":"12","author":"Yang","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"18189","DOI":"10.1039\/D1CP02871E","article-title":"First-principles study of strain effect on the thermoelectric properties of LaP and LaAs","volume":"23","author":"Lin","year":"2021","journal-title":"Phys. Chem. Chem. Phys."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"014053","DOI":"10.1103\/PhysRevApplied.18.014053","article-title":"Enhanced high-temperature thermoelectric performance by strain engineering in BiOCl","volume":"18","author":"Wu","year":"2022","journal-title":"Phys. Rev. Appl."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"12573","DOI":"10.1039\/D2RA00805J","article-title":"Pressure-driven thermoelectric properties of defect chalcopyrite structured ZnGa2Te4: Ab initio study","volume":"12","author":"Govindaraj","year":"2022","journal-title":"RSC Adv."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"164404","DOI":"10.1016\/j.jallcom.2022.164404","article-title":"Large enhancement of thermoelectric properties of CoSb3 tuned by uniaxial strain","volume":"908","author":"Qi","year":"2022","journal-title":"J. Alloys Compd."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"104106","DOI":"10.1103\/PhysRevB.109.104106","article-title":"Strain controlled thermal regulator realized in two-dimensional black and blue phosphorene in-plane heterostructure","volume":"109","author":"Xia","year":"2024","journal-title":"Phys. Rev. B"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"17053","DOI":"10.1038\/natrevmats.2017.53","article-title":"Computationally guided discovery of thermoelectric materials","volume":"2","author":"Gorai","year":"2017","journal-title":"Nat. Rev. Mater."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"085401","DOI":"10.1103\/PhysRevMaterials.3.085401","article-title":"Computational prediction of lattice thermal conductivity: A comparison of molecular dynamics and Boltzmann transport approaches","volume":"3","author":"Puligheddu","year":"2019","journal-title":"Phys. Rev. Mater."},{"key":"ref_29","first-page":"041029","article-title":"High-throughput study of lattice thermal conductivity in binary rocksalt and zinc blende compounds including higher-order anharmonicity","volume":"10","author":"Xia","year":"2020","journal-title":"Phys. Rev. X"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2108532","DOI":"10.1002\/adfm.202108532","article-title":"Accelerated discovery and design of ultralow lattice thermal conductivity materials using chemical bonding principles","volume":"32","author":"He","year":"2022","journal-title":"Adv. Funct. Mater."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"e2302541120","DOI":"10.1073\/pnas.2302541120","article-title":"A unified understanding of minimum lattice thermal conductivity","volume":"120","author":"Xia","year":"2023","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1021\/accountsmr.3c00089","article-title":"Multilayer Approach for Ultralow Lattice Thermal Conductivity in Low-Dimensional Solids","volume":"5","author":"Ma","year":"2024","journal-title":"Accounts Mater. Res."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2911","DOI":"10.1021\/cm400893e","article-title":"Data-driven review of thermoelectric materials: Performance and resource considerations","volume":"25","author":"Gaultois","year":"2013","journal-title":"Chem. Mater."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1002\/jcc.25067","article-title":"Prediction of seebeck coefficient for compounds without restriction to fixed stoichiometry: A machine learning approach","volume":"39","author":"Furmanchuk","year":"2018","journal-title":"J. Comput. Chem."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"475501","DOI":"10.1088\/1361-648X\/aba06b","article-title":"Data-driven discovery of 3D and 2D thermoelectric materials","volume":"32","author":"Choudhary","year":"2020","journal-title":"J. Phys. Condens. Matter"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1906041","DOI":"10.1002\/adfm.201906041","article-title":"Machine learning approaches for thermoelectric materials research","volume":"30","author":"Wang","year":"2020","journal-title":"Adv. Funct. Mater."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"315301","DOI":"10.1088\/1361-6463\/ab898e","article-title":"A high-throughput descriptor for prediction of lattice thermal conductivity of half-Heusler compounds","volume":"53","author":"Liu","year":"2020","journal-title":"J. Phys. D Appl. Phys."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1038\/s41524-021-00585-7","article-title":"Machine learning and evolutionary prediction of superhard BCN compounds","volume":"7","author":"Chen","year":"2021","journal-title":"NPJ Comput. Mater."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"190902","DOI":"10.1063\/5.0054532","article-title":"Data-driven thermoelectric modeling: Current challenges and prospects","volume":"130","author":"Mbaye","year":"2021","journal-title":"J. Appl. Phys."},{"key":"ref_40","first-page":"20","article-title":"Machine learning regression guided thermoelectric materials discovery\u2014A review","volume":"14","author":"Han","year":"2021","journal-title":"ES Mater. Manuf."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"An, Y. (2022). Machine Learning in Materials Informatics: Methods and Applications, ACS Publications.","DOI":"10.1021\/bk-2022-1416"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1808","DOI":"10.1021\/acs.jpclett.2c03073","article-title":"A critical review of machine learning techniques on thermoelectric materials","volume":"14","author":"Wang","year":"2023","journal-title":"J. Phys. Chem. Lett."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"157947","DOI":"10.1016\/j.apsusc.2023.157947","article-title":"Machine learning accelerated design of 2D covalent organic frame materials for thermoelectrics","volume":"638","author":"Wu","year":"2023","journal-title":"Appl. Surf. Sci."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1038\/s41524-023-01063-y","article-title":"Accelerating materials-space exploration for thermal insulators by mapping materials properties via artificial intelligence","volume":"9","author":"Purcell","year":"2023","journal-title":"NPJ Comput. Mater."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"e21","DOI":"10.1002\/mgea.21","article-title":"The MatHub-3d first-principles repository and the applications on thermoelectrics","volume":"2","author":"Liu","year":"2024","journal-title":"Mater. Genome Eng. Adv."},{"key":"ref_46","first-page":"100604","article-title":"A review on recent developments of thermoelectric materials for room-temperature applications","volume":"37","author":"Soleimani","year":"2020","journal-title":"Sustain. Energy Technol. Assess."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"368","DOI":"10.1016\/j.commatsci.2015.11.006","article-title":"TE Design Lab: A virtual laboratory for thermoelectric material design","volume":"112","author":"Gorai","year":"2016","journal-title":"Comput. Mater. Sci."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.commatsci.2018.05.018","article-title":"Matminer: An open source toolkit for materials data mining","volume":"152","author":"Ward","year":"2018","journal-title":"Comput. Mater. Sci."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"109155","DOI":"10.1016\/j.commatsci.2019.109155","article-title":"Machine learning models for the lattice thermal conductivity prediction of inorganic materials","volume":"170","author":"Chen","year":"2019","journal-title":"Comput. Mater. Sci."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1046","DOI":"10.1103\/PhysRev.113.1046","article-title":"Model for lattice thermal conductivity at low temperatures","volume":"113","author":"Callaway","year":"1959","journal-title":"Phys. Rev."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1016\/0022-3697(73)90092-9","article-title":"Nonmetallic crystals with high thermal conductivity","volume":"34","author":"Slack","year":"1973","journal-title":"J. Phys. Chem. Solids"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"174514","DOI":"10.1103\/PhysRevB.108.174514","article-title":"Machine learning the relationship between Debye temperature and superconducting transition temperature","volume":"108","author":"Smith","year":"2023","journal-title":"Phys. Rev. B"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"832","DOI":"10.1109\/34.709601","article-title":"The random subspace method for constructing decision forests","volume":"20","author":"Ho","year":"1998","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_55","first-page":"2825","article-title":"Scikit-learn: Machine learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/0927-0256(96)00008-0","article-title":"Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set","volume":"6","author":"Kresse","year":"1996","journal-title":"Comput. Mater. Sci."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"11169","DOI":"10.1103\/PhysRevB.54.11169","article-title":"Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set","volume":"54","author":"Kresse","year":"1996","journal-title":"Phys. Rev. B"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"17953","DOI":"10.1103\/PhysRevB.50.17953","article-title":"Projector augmented-wave method","volume":"50","year":"1994","journal-title":"Phys. Rev. B"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1758","DOI":"10.1103\/PhysRevB.59.1758","article-title":"From ultrasoft pseudopotentials to the projector augmented-wave method","volume":"59","author":"Kresse","year":"1999","journal-title":"Phys. Rev. B"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"3865","DOI":"10.1103\/PhysRevLett.77.3865","article-title":"Generalized gradient approximation made simple","volume":"77","author":"Perdew","year":"1996","journal-title":"Phys. Rev. Lett."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"5188","DOI":"10.1103\/PhysRevB.13.5188","article-title":"Special points for Brillouin-zone integrations","volume":"13","author":"Monkhorst","year":"1976","journal-title":"Phys. Rev. B"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.cpc.2018.05.010","article-title":"BoltzTraP2, a program for interpolating band structures and calculating semi-classical transport coefficients","volume":"231","author":"Madsen","year":"2018","journal-title":"Comput. Phys. Commun."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.scriptamat.2015.07.021","article-title":"First principles phonon calculations in materials science","volume":"108","author":"Togo","year":"2015","journal-title":"Scr. Mater."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"094306","DOI":"10.1103\/PhysRevB.91.094306","article-title":"Distributions of phonon lifetimes in Brillouin zones","volume":"91","author":"Togo","year":"2015","journal-title":"Phys. Rev. B"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"353001","DOI":"10.1088\/1361-648X\/acd831","article-title":"Implementation strategies in phonopy and phono3py","volume":"35","author":"Togo","year":"2023","journal-title":"J. Phys. Condens. Matter"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"1272","DOI":"10.1107\/S0021889811038970","article-title":"VESTA 3 for three-dimensional visualization of crystal, volumetric and morphology data","volume":"44","author":"Momma","year":"2011","journal-title":"J. Appl. Crystallogr."},{"key":"ref_67","unstructured":"(2024, August 08). Periodic Trend Plotter. Available online: https:\/\/github.com\/Andrew-S-Rosen\/periodic_trends."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"4305","DOI":"10.1002\/ange.202013923","article-title":"Evidence of highly anharmonic soft lattice vibrations in a Zintl rattler","volume":"133","author":"Dutta","year":"2021","journal-title":"Angew. Chem."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"1705617","DOI":"10.1002\/adma.201705617","article-title":"Manipulation of phonon transport in thermoelectrics","volume":"30","author":"Chen","year":"2018","journal-title":"Adv. Mater."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.mtphys.2018.02.005","article-title":"Anharmoncity and low thermal conductivity in thermoelectrics","volume":"4","author":"Chang","year":"2018","journal-title":"Mater. Today Phys."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"624","DOI":"10.1021\/cm901956r","article-title":"Zintl chemistry for designing high efficiency thermoelectric materials","volume":"22","author":"Toberer","year":"2010","journal-title":"Chem. Mater."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"9121","DOI":"10.1039\/c2ee22378c","article-title":"Thermoelectric properties of Sr3GaSb3\u2014A chain-forming Zintl compound","volume":"5","author":"Zevalkink","year":"2012","journal-title":"Energy Environ. Sci."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"13269","DOI":"10.1039\/C8TC03492C","article-title":"Low lattice thermal conductivity and promising thermoelectric figure of merit of Zintl type TlInTe2","volume":"6","author":"Ding","year":"2018","journal-title":"J. Mater. Chem. C"},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"1800904","DOI":"10.1002\/pssa.201800904","article-title":"A review of strategies for developing promising thermoelectric materials by controlling thermal conduction","volume":"216","author":"Yin","year":"2019","journal-title":"Phys. Status Solidi A"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1016\/j.jallcom.2019.07.147","article-title":"Promising materials for thermoelectric applications","volume":"806","author":"Cai","year":"2019","journal-title":"J. Alloys Compd."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"100480","DOI":"10.1016\/j.mtphys.2021.100480","article-title":"Unveiling the origins of low lattice thermal conductivity in 122-phase Zintl compounds","volume":"21","author":"Guo","year":"2021","journal-title":"Mater. Today Phys."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"235213","DOI":"10.1103\/PhysRevB.108.235213","article-title":"Acoustic phonon softening enhances phonon scattering in Zintl-phase II-IV compounds","volume":"108","author":"Wang","year":"2023","journal-title":"Phys. Rev. B"},{"key":"ref_78","unstructured":"Tran\u00e5s, R., L\u00f8vvik, O.M., and Berland, K. (2023). Lattice Thermal Conductivity from First Principles and Active Learning with Gaussian Process Regression. arXiv."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"16917","DOI":"10.1039\/C5CP02344K","article-title":"High thermopower and ultra low thermal conductivity in Cd-based Zintl phase compounds","volume":"17","author":"Pandey","year":"2015","journal-title":"Phys. Chem. Chem. Phys."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"5146","DOI":"10.1021\/acsaem.2c00484","article-title":"Remarkable Thermoelectric Performance in K2CdPb Crystals with 1D Building Blocks via Structure Particularity and Bond Heterogeneity","volume":"5","author":"Zhang","year":"2022","journal-title":"ACS Appl. Energy Mater."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"9188","DOI":"10.1002\/ange.202014222","article-title":"Ultralow lattice thermal conductivity at room temperature in Cu4TiSe4","volume":"133","author":"Koley","year":"2021","journal-title":"Angew. Chem."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"105984","DOI":"10.1016\/j.mssp.2021.105984","article-title":"Ultra-low lattice thermal conductivity and high thermoelectric efficiency in Cs2SnX6 (X = Br, I): A DFT study","volume":"133","author":"Fallah","year":"2021","journal-title":"Mater. Sci. Semicond. Process."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"1017","DOI":"10.1126\/science.abh1619","article-title":"Low thermal conductivity in a modular inorganic material with bonding anisotropy and mismatch","volume":"373","author":"Gibson","year":"2021","journal-title":"Science"},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"32453","DOI":"10.1021\/acsami.3c05602","article-title":"Extremely Low Lattice Thermal Conductivity Leading to Superior Thermoelectric Performance in Cu4TiSe4","volume":"15","author":"Zhang","year":"2023","journal-title":"ACS Appl. Mater. Interfaces"},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"A1143","DOI":"10.1103\/PhysRev.133.A1143","article-title":"Electronic transport in semimetallic cerium sulfide","volume":"133","author":"Cutler","year":"1964","journal-title":"Phys. Rev."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1038\/nmat2090","article-title":"Complex thermoelectric materials","volume":"7","author":"Snyder","year":"2008","journal-title":"Nat. Mater."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"A1058","DOI":"10.1103\/PhysRev.134.A1058","article-title":"Thermal conductivity of silicon and germanium from 3 K to the melting point","volume":"134","author":"Glassbrenner","year":"1964","journal-title":"Phys. Rev."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"014004","DOI":"10.1103\/PhysRevApplied.3.014004","article-title":"Connecting thermoelectric performance and topological-insulator behavior: Bi2Te3 and Bi2Te2Se from first principles","volume":"3","author":"Shi","year":"2015","journal-title":"Phys. Rev. Appl."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"16566","DOI":"10.1039\/C6CP02057G","article-title":"Investigation of the bipolar effect in the thermoelectric material CaMg2Bi2 using a first-principles study","volume":"18","author":"Gong","year":"2016","journal-title":"Phys. Chem. Chem. Phys."}],"container-title":["Materials"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1996-1944\/17\/21\/5372\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:27:24Z","timestamp":1760113644000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1996-1944\/17\/21\/5372"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,2]]},"references-count":89,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2024,11]]}},"alternative-id":["ma17215372"],"URL":"https:\/\/doi.org\/10.3390\/ma17215372","relation":{},"ISSN":["1996-1944"],"issn-type":[{"value":"1996-1944","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,2]]}}}