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Transient behavior in quasi-atomic layer etching of silicon dioxide and silicon nitride in fluorocarbon plasmas
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Atomic Layer Etching of Silicon Using a Conventional ICP Etch Chamber for Failure Analysis Applications.
Abstract not provided.
Atomic Precision Processing of Two-Dimensional Materials for Next-Generation Microelectronics
The growth of the information era economy is driving the pursuit of advanced materials for microelectronics, spurred by exploration into “Beyond CMOS” and “More than Moore” paradigms. Atomically thin 2D materials, such as transition metal dichalcogenides (TMDCs), show great potential for next-generation microelectronics due to their properties and defect engineering capabilities. This perspective delves into atomic precision processing (APP) techniques like atomic layer deposition (ALD), epitaxy, atomic layer etching (ALE), and atomic precision advanced manufacturing (APAM) for the fabrication and modification of 2D materials, essential for future semiconductor devices. Additive APP methods like ALD and epitaxy provide precise control over composition, crystallinity, and thickness at the atomic scale, facilitating high-performance device integration. Subtractive APP techniques, such as ALE, focus on atomic-scale etching control for 2D material functionality and manufacturing. In APAM, modification techniques aim at atomic-scale defect control, offering tailored device functions and improved performance. Achieving optimal performance and energy efficiency in 2D material-based microelectronics requires a comprehensive approach encompassing fundamental understanding, process modeling, and high-throughput metrology. Finally, the outlook for APP in 2D materials is promising, with ongoing developments poised to impact manufacturing and fundamental materials science. Integration with advanced metrology and codesign frameworks will accelerate the realization of next-generation microelectronics enabled by 2D materials.
Methods to deposit and etch controlled thin layers of transition metal dichalcogenides
Transition metal dichalcogenides (TMDs) are deposited by atomic layer deposition as thin layers on a substrate. The TMDs may be grown on oxide substrates and may have a tunable TMD-oxide interface. The TMD may be etched using an atomic layer etching technique.
Modification of a force field for molecular dynamics simulations of silicon etching by chlorine atoms
Here, a modified classical molecular dynamics (MD) force field is presented for the interaction between silicon (Si) and chlorine (Cl). The original version of the force field is shown to significantly overestimate the probability of Si etching by thermal Cl atoms. However, the modified force field corrects this problem and results in generally good agreement with experimental data. Further, it is shown that while the modification of the force field improves the prediction of Si spontaneous etching with Cl atoms, it does not degrade predictions of atomic-layer etching of Si with Cl[Formula: see text] molecules.
Molecular Layer Etching of Metalcone Films Using Lithium Organic Salts and Trimethylaluminum
Advances in semiconductor device manufacturing are limited by our ability to precisely add and remove thin layers of material in multistep fabrication processes. Recent reports on atomic layer etching (ALE) have provided the means for the precise removal of inorganic thin films deposited by atomic layer deposition (ALD), opening new avenues for nanoscale device design. Here, we report on a new technique for the precise removal of metal organic thin films deposited by molecular layer deposition (MLD), which we term molecular layer etching. This etching process employs sequential exposures of lithium organic salt (LOS) and trimethylaluminum (TMA) precursors to produce self-limiting etching behavior. We employ quartz crystal microbalance experiments to demonstrate (i) etching of alucone films preloaded with LOS upon TMA exposures and (ii) layer-by-layer etching of alucone films using alternating exposures of LOS and TMA. We also identify the selectivity of these etching mechanisms. We probe the mechanism for the layer-by-layer etching of alucone using a quartz crystal microbalance and Fourier transform infrared spectroscopy and identify that the etching proceeds via heterolytic cleaving of Al-O bonds in alucone upon LOS exposure followed by methylation to produce volatile species upon TMA exposure. The etching process results in the removal of 0.4 nm/cycle of alucone at 160 °C and up to 3.6 nm/cycle of alucone at 266 °C in ex situ etching experiments on silicon wafers. This halogen-free etching process enables etching of MLD films and provides new fabrication pathways for the control of material geometries at the nanoscale.
Deep potential molecular dynamics simulations of low-temperature plasma-surface interactions
Machine learning approaches to potential generation for molecular dynamics (MD) simulations of low-temperature plasma-surface interactions could greatly extend the range of chemical systems that can be modeled. Empirical potentials are difficult to generalize to complex combinations of multiple elements with interactions that might include covalent, ionic, and metallic bonds. This work demonstrates that a specific machine learning approach, Deep Potential Molecular Dynamics (DeepMD), can generate potentials that provide a good model of plasma etching in the Si-Cl-Ar system. Comparisons are made between MD results using DeepMD models and empirical potentials, as well as experimental measurements. Pure Si properties predicted by the DeepMD model are in reasonable agreement with experimental results. Simulations of Si bombardment by Ar + ions demonstrate the ability of the DeepMD method to predict sputtering yields as well as the depth of the amorphous-crystalline interface. Etch yields as a function of flux ratio and ion energy for simultaneous Cl 2 and Ar + impacts are in good agreement with previous simulation results and experiment. Predictions of etch yields and etch products during plasma-assisted atomic layer etching of Si-Cl 2 -Ar are shown to be in good agreement with MD predictions using empirical potentials and with experiment. Finally, good agreement was also seen with measurements for the spontaneous etching of Si by Cl atoms at 300 K. Further, the demonstration that DeepMD can reproduce results from MD simulations using empirical potentials is a necessary condition to future efforts to extend the method to a much wider range of systems for which empirical potentials may be difficult or impossible to obtain.
Etching with electron beam-generated plasmas: Selectivity versus ion energy in silicon-based films
In the ideal case, plasma-enhanced atomic layer etching enables the ability to not only remove one monolayer of material but also leave adjacent layers undamaged. This dual mandate requires fine control over the flux of species to ensure efficacy, while maintaining an often arduously low ion energy. Electron beam-generated plasmas are well-suited for etching at low ion energies as they are generally characterized by highly charged particle densities (10 10 –10 11 cm –3 ) and low electron temperatures (<1.0 eV), which provide the ability to deliver a large flux of ions whose energies are <5 eV. Raising the ion energy with substrate biasing thus enables process control over an energy range that extends down to values commensurate with the bond strength of most material systems. In this work, we discuss silicon nitride etching using pulsed, electron beam-generated plasmas produced in argon-SF6 backgrounds. We pay particular attention to the etch rates and selectivity versus oxidized silicon nitride and polycrystalline silicon as a function of ion energy from a few eV up to 50 eV. Here, we find the blanket etch rate of Si 3 N 4 to be in the range of 1 A/s, with selectivities (versus SiO 2 and poly-Si) greater than 10:1 when ion energies are below 30 eV.
Surrogate models to optimize plasma-assisted atomic layer deposition in high aspect ratio features
In this work, we explore surrogate models to optimize plasma enhanced atomic layer deposition (PEALD) in high aspect ratio features. In plasma-based processes such as PEALD and atomic layer etching (ALE), surface recombination can dominate the reactivity of plasma species with the surface, which can lead to unfeasibly long exposure times to achieve full conformality inside nanostructures like high aspect ratio vias. Using a synthetic dataset based on simulations of PEALD, we train artificial neural networks to predict saturation times based on cross section thickness data obtained for partially coated conditions. The results obtained show that just two experiments in undersaturated conditions contain enough information to predict saturation times within 10% of the ground truth. A surrogate model trained to determine whether surface recombination dominates the plasma–surface interactions in a PEALD process achieves 99% accuracy. This demonstrates that machine learning can provide a new pathway to accelerate the optimization of PEALD processes in areas such as microelectronics. Our approach can be easily extended to ALE and more complex structures.
Particle-in-cell modeling of electron beam generated plasma
Plasmas generated using energetic electron beams are well known for their low electron temperature (T e ) and plasma potential, which makes them attractive for atomic-precision plasma processing applications such as atomic layer etch and deposition. A 2-dimensional particle-in-cell model for an electron beam-generated plasma in argon confined by a constant applied magnetic field is described here in this article. Plasma production primarily occurs in the path of the beam electrons in the center of the chamber. The resulting plasma spreads out in the chamber through non-ambipolar diffusion with a short-circuiting effect allowing unequal electron and ion fluxes to different regions of the bounding conductive chamber walls. The cross-field transport of the electrons (and thus the steady-state characteristics of the plasma) are strongly impacted by the magnetic field. T e is anisotropic in the electron beam region, but low and isotropic away from the plasma production zone. The plasma density increases and the plasma becomes more confined near the region of production when the magnetic field strengthens. The magnetic field reduces both electron physical and energy transport perpendicular to the magnetic field. T e is uniform along the magnetic field lines and slowly decreases perpendicular to it. Electrons are less energetic in the sheath regions where the sheath electric field repels and confines the low-energy electrons from the bulk plasma. Even though electron and ion densities are similar in the bulk plasma due to quasi-neutrality, electron and ion fluxes on the grounded chamber walls are unequal at most locations. Electron confinement by the magnetic field weakens with increasing pressure, and the plasma spread out farther from the electron beam region.
External charge compensation in etched gallium nitride measured by x-ray photoelectron spectroscopy
Electronic states at GaN surfaces and at regrowth and heteroepitaxy interfaces inhibit electronic device performance. Understanding electronic state configuration at the GaN surface is, therefore, crucial for the development of GaN-based devices, which are currently of considerable interest in power electronic applications. GaN and other wurtzite III-nitrides possess large spontaneous polarization along the c-axis, producing a bound sheet charge at the surface, which affects the electronic state configuration through the formation of internal and external compensation charges. Defects induced by conventional plasma-based dry etching methods may inhibit the internal screening of this bound charge and thus increase the concentration of external charged states. The surface band bending of n-type Ga-face GaN (0001) was measured with x-ray photoelectron spectroscopy after inductively coupled plasma etching to investigate the impact of dry etching on external charge compensation. GaN samples were etched using inductively coupled plasma with varying rf power and a novel plasma-enhanced atomic layer etching method using an oxidation, fluorination, and ligand-exchange mechanism. The band bending varied from 0.0 to 0.8 ± 0.1 eV for the samples measured.
Rethinking surface reactions in nanoscale dry processes toward atomic precision and beyond: a physics and chemistry perspective
In this review, we discuss the progress of emerging dry processes with atomic precision. Researchers in the field of plasma processing and surface science have addressed the increasingly challenging demands of material selectivity by utilization of synergistic enhancement of etching or deposition. The discussion encompasses major challenges in the plasma science and technology community. Here, the focus of the review is advances in atomic layer etching and area-selective deposition with activation or deactivation, especially in terms of materials scaling and variety. Control of high-aspect-ratio feature fabrication in semiconductor manufacturing and etched shapes of interior features at the nanoscale are needed. Issues related to profile distortion have received much attention. State-of-the-art techniques used in semiconductor manufacturing are reviewed and future challenges are outlined.
Evolution of photoresist layer structure and surface morphology under fluorocarbon‐based plasma exposure
Abstract Ion bombardment of photoresist materials during plasma etching results in the formation of a surface dense amorphous carbon (DAC) layer that contributes to both etch resistance and the development of surface roughness. Real‐time ellipsometric measurements/analysis reveals that a C 4 F 8 ‐containing plasma interacts with an Ar‐plasma‐formed DAC layer to produce a modified DAC/fluorocarbon (FC) layer by FC deposition/diffusion of fluorine into the surface. The depletion of the DAC layer via modification and ion bombardment causes the etch rate of the bulk layer to increase. As the modified surface layer is formed, a noticeable decrease in surface roughness decrease is observed. These findings provide an understanding of the mechanisms of atomic layer etching processes in photoresist materials.
A neural master equation framework for multiscale modeling of molecular processes: application to atomic-scale plasma processes
Plasma-surface interactions (PSI) play a crucial role in microelectronics fabrication; however, their multiscale nature and array of complex, often unknown interactions make computational modeling of PSIs extremely difficult. To this end, we propose a general neural master equation (NME) framework that uses master equations to describe the dynamics of a molecular process, wherein neural networks learned from atomistic simulations represent unknown transitions between different system states. By leveraging the physics-based structure of master equations and data-driven state transitions, the NME framework promotes generalizability and physics interpretability, and can bridge disparate length and time scales. The framework is demonstrated for multiscale modeling of Si atomic layer etching and reactive ion etching, where the learned NME-based surface kinetic models exhibit good predictive and extrapolative capabilities for predicting experimentally relevant observables as a function of process parameters. The NME-based surface kinetic models obey physical constraints, which are violated in models based on neural ordinary differential equations. The proposed NME framework for multiscale modeling of molecular processes can pave the way for the discovery of new chemistries and materials in atomic-scale plasma processes.
Reactor scale simulations of ALD and ALE: Ideal and non-ideal self-limited processes in a cylindrical and a 300 mm wafer cross-flow reactor
Here, we have developed a simulation tool to model self-limited processes such as atomic layer deposition (ALD) and atomic layer etching inside reactors of arbitrary geometry as well the output of in situ quartz crystal microbalance and mass spectrometry. We have applied this model to two standard types of cross-flow reactors: a cylindrical tube reactor and a model 300 mm wafer reactor, and explored both ideal and nonideal self-limited kinetics. The model results are in agreement with experimental results and analytic expressions obtained using a simple plug-flow model for the cylindrical tube reactor. We also extended the simulations to consider two nonideal self-limited processes: soft-saturating processes characterized by a slow reaction pathway and processes where surface by-products can compete with the precursor for the same pool of adsorption sites. Our results show that it is possible to have a self-limited process with saturated yet inhomogeneous growth profiles due to the competition of reactor by-products. This is in agreement with experimental observations for titanium dioxide ALD from titanium tetraisopropoxide and titanium tetrachloride precursors.
Operando XPS in reactive plasmas: The importance of the wall reactions
In this article, advancements in differential pumping and electron optics over the past few decades have enabled x-ray photoelectron spectroscopy (XPS) measurements at (near-)ambient pressures, bridging the pressure gap for characterizing realistic sample chemistries. Recently, we have demonstrated the capabilities of an ambient pressure XPS setup for in situ plasma environment measurements, allowing plasma-surface interactions to be studied in operando rather than using the traditional before-and-after analysis approach. This new “plasma-XPS” technique facilitates the identification of reaction intermediates critical for understanding plasma-assisted surface processes relevant to semiconductor nanomanufacturing, such as physical vapor deposition, etching, atomic layer deposition, and many other plasma applications. In this paper, we apply the plasma-XPS approach to monitor real-time surface chemical changes on a model Ag(111) single crystal exposed to oxidizing and reducing plasmas. We correlate surface-sensitive data with concurrent gas-phase XPS measurements and residual gas mass-spectrum analysis of species generated during plasma exposure, highlighting the significant role of plasma-induced chamber wall reactions. Ultimately, we demonstrate that plasma-XPS provides comprehensive insights into both surface and gas-phase chemistry, establishing it as a versatile and dynamic characterization tool with broad applications in microelectronics research. Finally, we outline potential enhancements and future metrology directions to advance plasma-XPS investigations further.