TMDCs show excellent performance in enhancing bio and gas sensing signals because of their metallic and semi-conducting electrical capabilities, tunable band gap, large specific surface area etc.
They are promising candidates for diverse applications including wearable and implantable biosensors/gas sensor devices including electronic skin (e-skin), home security, air- and health-monitoring, advanced optical and quantum computing. Linear (to a lesser extent nonlinear) optical responses of TMDCs play a key role in their optimizations for the above applications.
Optical properties such as absorption, gain and photoluminescence are typically measured by experimentalists as a means of characterizing TMDCs in different environments. SimuLase_TMDC offers a rigorous and predictive means of a priori computing these quantities independent of their being fabricated or measured. Given such high sensitivity of monolayer TMDCs to external influences (substrate, bi-layer, heterostructure, gas or bio molecule etc), a Graphical User Interface (GUI) driven compute engine facilitates fast tracking to a desired targeted solution.
Built on top of density-functional theory (DFT) inputs and a Poisson solver to compute environmental influences, the full many body Semiconductor Dirac Bloch equations are solved in the compute module, enabling the user to provide their own DFT generated material inputs. The highly optimized and fully parallelized many-body code includes higher order pair correlations, Auger processes etc, effects, that while much less influential and appearing at higher order in conventional semiconductors, profoundly modify the computed TMDC optical properties.
In the Design phase, a user interactively constructs a structure from a range of bulk materials and monolayer, bilayer, hetero bilayer or multilayer TMDC materials. The greatly enhanced linear and nonlinear response of TMDC materials, subjected to environmental influence, will strongly modify the optical response to an incident field. The software module has built-in TMDC materials classes of various types for common TMDC materials extracted from one effective particle Density Functional theory (DFT) calculations. Users may extend the SimuLase material database by importing their own DFT calculations to create new custom materials.
In the Simulate phase, the designed structure is numerically simulated using our propitiatory computation engine which solves the full many body Semiconductor Dirac Bloch equations. The user determines the computational requirements of this phase by selecting from a range of predefined simulation models of varying accuracy. The Standard model includes all Coulomb effects, excitonic resonances, bandgap renormalizations, microscopic scattering, and higher excitonic correlations. The available reduced models require considerably less computation by either neglecting Coulomb effects, other physical process or reduced spectral resolution.
In the Analyze phase, the accumulated data from one or more device simulation is visualized and compared. The user can extract of all of the relevant optical properties of a structure, compare different structures and generate high-level publication quality graphical images. The Analyze video walks the user through the many options.
The SimuLase for 2D structures simulation framework can be divided into three general functionalities. In the Design phase, a user needs to set up a structure such as a single monolayer, bilayer, hetero bilayer or multilayer TMDC material. The greatly enhanced linear and nonlinear response of that material subjected to some environmental influence will strongly modify the optical response to an incident field. The software module has built-in materials classes of various types for common TMDC materials extracted from one effective particle Density Functional theory (DFT) calculations. The great flexibility of software means that a user may choose to run their own DFT for their selected materials and input it to SimuLase.
Once the material structure is defined, the next step is to Simulate this structure. This is the compute intensive phase and will depend on the level of complexity of the overall structure, the level of modeling assumed and the resolution needed. As the simulation will likely consume the most computer resources, the user is offered the choice of three pathways, of increasing computational complexity as discussed in the Simulate video.
Finally, after running one or more material systems, the accumulated data will need to be Analyzed. The user can extract of all of the relevant optical properties of a structure, compare different structures and generate high-level publication quality graphical images. The Analyze video walks the user through the many options.
References:
[1] L. Meckbach,J. Hader, U. Huttner, J. Neuhaus, J. T. Steiner,T . Stroucken ,J. V. Moloney and S. W. Koch. “Ultrafast band-gap renormalization and build-up of optical gain in monolayer MoTe2, Phys. Rev. B, 101, 075401 (2020).
[2] Joerg Hader, Josefine Neuhaus, Jerome V Moloney and Stephan W. Koch, “On the importance of electron–electron and electron–phonon scatterings and energy renormalizations during carrier relaxation in monolayer transition-metal dichalcogenides”, J. Phys. Condens. Matter, 34, 285601 (2022).
In a standard semiconductor, the Γ point in the bandstructure represents the energetically lowest state of the conduction band (highest of the valence band) and corresponds to the optically active state responsible for absorption and lasing.
The surface plots of the 2D bandstructure of monolayer MoTe2 on the right for the conduction (top) and valence (bottom) bands show immediately that the Γ point is of no particular significance in a 2D material.
Indeed, it is the energetically highest point in the conduction band. Instead, triply degenerate new high symmetry points appear well separated from the Γ point. A line plot shown on the right starting at Γ and traversing Σ, K, M, K’, Λ and back to Γ, is particularly illuminating.
Clearly direct bandgaps exist at the triply degenerate K and K’ points and these are potential candidates for optical absorption and lasing. Each of the bands are further split into 2 spin bands (blue and red). These can be independently excited with differently polarized optical fields. Hence the emergence of potential applications in valleytronics and spintronics. Further applications include biosensing, biomedical applications, gas sensing, optical communication, laser sources, photodectors etc.
The figure above encapsulates the unique aspects of quasi-2D materials and offers a stark contrast with the situation encountered in a conventional II-V or II-VI semiconductor.
A cut through the high symmetry points of the 2D bandstructure shows 4 local minima in the conduction band at Σ, K, K’ and Λ while the corresponding hole band cut displays only 2 local maxima at the K and K’ points. Clearly direct bandgaps exist at the triply degenerate K and K’ points.
Unlike conventional semiconductors, these quasi-2D materials display prominent room temperature exciton absorption peaks that undergo huge spectral shift due to a few order of magnitude stronger (in-plane) Coulomb potential and sensitivity to external influences through Van der Waals out-of-plane forces.
