Resistive switching in high-density nanodevices fabricated by block copolymer self-assembly

Periodic Arrays of Dopants in Silicon by Ultralow Energy Implantation of Phosphorus Ions through a Block Copolymer Thin Film

In this work, block copolymer lithography and ultralow energy ion implantation are combined to obtain nanovolumes with high concentrations of phosphorus atoms periodically disposed over a macroscopic area in a p-type silicon substrate. The high dose of implanted dopants grants a local amorphization of the silicon substrate. In this condition, phosphorus is activated by solid phase epitaxial regrowth (SPER) of the implanted region with a relatively low temperature thermal treatment preventing diffusion of phosphorus atoms and preserving their spatial localization. Surface morphology of the sample (AFM, SEM), crystallinity of the silicon substrate (UV Raman), and position of the phosphorus atoms (STEM- EDX, ToF-SIMS) are monitored during the process. Electrostatic potential (KPFM) and the conductivity (C-AFM) maps of the sample surface upon dopant activation are compatible with simulated I-V characteristics, suggesting the presence of an array of not ideal but working p-n nanojunctions. The proposed approach paves the way for further investigations on the possibility to modulate the dopant distribution within a silicon substrate at the nanoscale by changing the characteristic dimension of the self-assembled BCP film.

Block copolymer self-assembly to pattern gold nanodots for site-specific placement of DNA origami and attachment of nanomaterials

Directed placement of DNA origami could play a key role in future integrated nanoelectronic devices. Here we demonstrated the site-selective attachment of DNA origami on gold dots formed using a pattern transfer method through block copolymer self-assembly. First, a random copolymer brush layer is grafted on the Si surface and then poly (styrene-b-methylmethacrylate) block copolymer is spin-coated to give a hexagonal nanoarray after annealing. UV irradiation followed by acetic acid etching is used to remove the PMMA, creating cylindrical holes and then oxygen plasma etching removes the random copolymer layer inside those holes. Next, metal evaporation, followed by lift-off creates a gold dot array. We evaluated different ligand functionalization of Au dots, as well as DNA hybridization to attach DNA origami to the nanodots. DNA-coated Au nanorods are assembled on the DNA origami as a step towards creating nanowires and to facilitate electron microscopy characterization of the attachment of DNA origami on these Au nanodots. The DNA hybridization approach showed better DNA attachment to Au nanodots than localization by electrostatic interaction. This work contributes to the understanding of DNA-templated assembly, nanomaterials, and block copolymer nanolithography. Furthermore, the work shows potential for creating DNA-templated nanodevices and their placement in ordered arrays in future nanoelectronics.

Liquid Phase Infiltration of Block Copolymers

Novel materials with defined composition and structures at the nanoscale are increasingly desired in several research fields spanning a wide range of applications. The development of new approaches of synthesis that provide such control is therefore required in order to relate the material properties to its functionalities. Self-assembling materials such as block copolymers (BCPs), in combination with liquid phase infiltration (LPI) processes, represent an ideal strategy for the synthesis of inorganic materials into even more complex and functional features. This review provides an overview of the mechanism involved in the LPI, outlining the role of the different polymer infiltration parameters on the resulting material properties. We report newly developed methodologies that extend the LPI to the realisation of multicomponent and 3D inorganic nanostructures. Finally, the recently reported implementation of LPI into different applications such as photonics, plasmonics and electronics are highlighted.

Fabrication of Nanodevices Through Block Copolymer Self-Assembly

Block copolymer (BCP) self-assembly, as a novel bottom-up patterning technique, has received increasing attention in the manufacture of nanodevices because of its significant advantages of high resolution, high throughput, low cost, and simple processing. BCP self-assembly provides a very powerful approach to constructing diverse nanoscale templates and patterns that meet large-scale manufacturing practices. For the past 20 years, the self-assembly of BCPs has been extensively employed to produce a range of nanodevices, such as nonvolatile memory, bit-patterned media (BPM), fin field-effect transistors (FinFETs), photonic nanodevices, solar cells, biological and chemical sensors, and ultrafiltration membranes, providing a variety of configurations for high-density integration and cost-efficient manufacturing. In this review, we summarize the recent progress in the fabrication of nanodevices using the templates of BCP self-assembly, and present current challenges and future opportunities.

Templating Functional Materials Using Self-Assembled Block Copolymer Thin-Film for Nanodevices

The nanomorphologies and nanoarchitectures that can be synthesized using block copolymer (BCP) thin-film self-assembly have inspired a variety of new applications, which offer various advantages, such as, small device footprint, low operational power and enhanced device performance. Imperative for these applications, however, is the ability to transform these small polymeric patterns into useful inorganic structures. BCP-templated inorganic nanostructures have shown the potential for use as active materials in various electronic device applications, including, field-effect transistors, photodetectors, gas sensors and many more. This article reviews various strategies that have been implemented in the past decade to fabricate devices at nanoscale using block copolymer thin films.

Defining Swelling Kinetics in Block Copolymer Thin Films: The Critical Role of Temperature and Vapour Pressure Ramp

We studied the kinetics of swelling in high-χ lamellar-forming poly(styrene)-block- poly(lactic acid) (PS-b-PLA) block copolymer (BCP) by varying the heating rate and monitoring the solvent vapour pressure and the substrate temperature in situ during solvo-thermal vapour annealing (STVA) in an oven, and analysing the resulting morphology. Our results demonstrate that there is not only a solvent vapour pressure threshold (120 kPa), but also that the rate of reaching this pressure threshold has a significant effect on the microphase separation and the resulting morphologies. To study the heating rate effect, identical films were annealed in a tetrahydrofuran (THF) vapour environment under three different ramp regimes, low (rT<1 °C/min), medium (24 °C/min), for 60, 90 and 120 min, respectively, while the solvent vapour pressure and the substrate temperature were measured in real time. The translational order improved significantly with increasing the heating rate. The solvent mass uptake calculated for the different ramp regimes during annealing is linearly proportional to time, indicating that the swelling kinetics followed Case II diffusion. Two stages of the swelling behaviour were observed: (i) diffusion at the initial stages of swelling and (ii) stress relaxation, controlled at later stages. Films with a faster rate of increase in vapour pressure (rP>2 kPa/min) reached the pressure threshold value at an early stage of the swelling and attained a good phase separation. According to our results, highly ordered patterns are only obtained when the volume fraction of the solvent exceeds the polymer volume fraction, i.e., (φs≥φp), during the swelling process, and below this threshold value (φs=0.5), the films did not obtain a good structural order, even at longer annealing times.

Self-Aligned Assembly of a Poly(2-vinylpyridine)-b-Polystyrene-b-Poly(2-vinylpyridine) Triblock Copolymer on Graphene Nanoribbons

Directed self-assembly (DSA) of block copolymers is one of the most promising patterning techniques for patterning sub-10 nm features. However, at such small feature sizes, it is becoming increasingly difficult to fabricate the guiding pattern for the DSA process, and it is necessary to explore alternative guiding methods for DSA to achieve long-range ordered alignment. Here, we report the self-aligned assembly of a triblock copolymer, poly(2-vinylpyridine)-b-polystyrene-b-poly(2-vinylpyridine) (P2VP-b-PS-b-P2VP) on neutral graphene nanoribbons with the gap consisting of a P2VP-preferential silicon oxide (SiO₂) substrate via solvent vapor annealing. The assembled P2VP-b-PS-b-P2VP demonstrated long-range, one-dimensional alignment on the graphene substrate in a direction perpendicular to the boundary of the graphene and substrate with a half-pitch size of 8 nm, which greatly alleviates the lithography resolution required for traditional chemoepitaxy DSA. A wide processing window is demonstrated with the gap between graphene stripes varying from 10 to 100 nm, overcoming the restriction on widths of guiding patterns to have commensurate domain spacing. When the gap was reduced to 10 nm, P2VP-b-PS-b-P2VP formed a straight-line pattern on both the graphene and the substrate. Monte Carlo simulations showed that the self-aligned assembly of the triblock copolymer on the graphene nanoribbons is guided at the boundary of parallel and perpendicular lamellae on graphene and SiO₂, respectively. Simulations also indicate that the swelling of a system allows for rapid rearrangement of chains and quickly anneal any misaligned grains and defects. The effect of the interaction strength between SiO₂ and P2VP on the self-assembly is systematically investigated in simulations.

Solvent Vapor Annealing, Defect Analysis, and Optimization of Self-Assembly of Block Copolymers Using Machine Learning Approaches

Self-assembly of block copolymers (BCPs) is an alternative patterning technique that promises high resolution and density multiplication with lower costs. The defectivity of the resulting nanopatterns remains too high for many applications in microelectronics and is exacerbated by small variations of processing parameters, such as film thickness, and fluctuations of solvent vapor pressure and temperature, among others. In this work, a solvent vapor annealing (SVA) flow-controlled system is combined with design of experiments (DOE) and machine learning (ML) approaches. The SVA flow-controlled system enables precise optimization of the conditions of self-assembly of the high Flory-Huggins interaction parameter (χ) hexagonal dot-array forming BCP, poly(styrene-b-dimethylsiloxane) (PS-b-PDMS). The defects within the resulting patterns at various length scales are then characterized and quantified. The results show that the defectivity of the resulting nanopatterned surfaces is highly dependent upon very small variations of the initial film thicknesses of the BCP, as well as the degree of swelling under the SVA conditions. These parameters also significantly contribute to the quality of the resulting pattern with respect to grain coarsening, as well as the formation of different macroscale phases (single and double layers and wetting layers). The results of qualitative and quantitative defect analyses are then compiled into a single figure of merit (FOM) and are mapped across the experimental parameter space using ML approaches, which enable the identification of the narrow region of optimum conditions for SVA for a given BCP. The result of these analyses is a faster and less resource intensive route toward the production of low-defectivity BCP dot arrays via rational determination of the ideal combination of processing factors. The DOE and machine learning-enabled approach is generalizable to the scale-up of self-assembly-based nanopatterning for applications in electronic microfabrication.

Recent Advances in Sequential Infiltration Synthesis (SIS) of Block Copolymers (BCPs)

In the continuous downscaling of device features, the microelectronics industry is facing the intrinsic limits of conventional lithographic techniques. The development of new synthetic approaches for large-scale nanopatterned materials with enhanced performances is therefore required in the pursuit of the fabrication of next-generation devices. Self-assembled materials as block copolymers (BCPs) provide great control on the definition of nanopatterns, promising to be ideal candidates as templates for the selective incorporation of a variety of inorganic materials when combined with sequential infiltration synthesis (SIS). In this review, we report the latest advances in nanostructured inorganic materials synthesized by infiltration of self-assembled BCPs. We report a comprehensive description of the chemical and physical characterization techniques used for in situ studies of the process mechanism and ex situ measurements of the resulting properties of infiltrated polymers. Finally, emerging optical and electrical properties of such materials are discussed.

Thermodynamics and ordering kinetics in asymmetric PS-b-PMMA block copolymer thin films

The ordering kinetics of standing cylinder-forming polystyrene-block-poly(methyl methacrylate) block copolymers (molecular weight: 39 kg mol^-1) close to the order-disorder transition is experimentally investigated following the temporal evolution of the correlation length at different annealing temperatures. The growth exponent of the grain-coarsening process is determined to be 1/2, signature of a curvature-driven ordering mechanism. The measured activation enthalpy and the resulting Meyer-Neldel temperature for this specific copolymer along with the data already known for PS-b-PMMA block copolymers in strong segregation limit allow investigation of the interplay between the ordering kinetics and the thermodynamic driving force during the grain coarsening. These findings unveil various phenomena concomitantly occurring during the thermally activated ordering kinetics at segmental, single chain, and collective levels.

Automated solvent vapor annealing with nanometer scale control of film swelling for block copolymer thin films

Molecular self-assembly of block copolymers has been pursued as a next generation high-resolution, low-cost lithography technique. Solvent vapor annealing is a promising way of achieving self-assembled patterns from polymers with high interaction parameters, χ, or high molecular weights. Compared to thermal annealing, the assembly in a solvated state can be much faster, but the film swelling process is typically challenging to control and reproduce. We report the design and implementation of an automated solvent annealing system that addresses these issues. In this system the film swelling is controlled via local heating or cooling, which enables exceptionally fast and precise modulation of the swelling. The swelling of the polymer films follows preprogrammed annealing profiles with the help of a feedback loop that compares and tunes the film thickness with respect to the set point. The system therefore enables complex annealing profiles such as rapid cyclic swelling and deswelling. We show that the orientation of the pattern morphology and the amount of lattice defects are influenced by the used annealing profile. We demonstrate that optimized profiles significantly shorten the annealing time (<15 min) of high-χ and high-molecular weight poly(styrene-b-2-vinylpyridine).

Stimulated Ionic Telegraph Noise in Filamentary Memristive Devices

Random telegraph noise is a widely investigated phenomenon affecting the reliability of the reading operation of the class of memristive devices whose operation relies on formation and dissolution of conductive filaments. The trap and the release of electrons into and from defects surrounding the filament produce current fluctuations at low read voltages. In this work, telegraphic resistance variations are intentionally stimulated through pulse trains in HfO₂-based memristive devices. The stimulated noise results from the re-arrangement of ionic defects constituting the filament responsible for the switching. Therefore, the stimulated noise has an ionic origin in contrast to the electronic nature of conventional telegraph noise. The stimulated noise is interpreted as raising from a dynamic equilibrium establishing from the tendencies of ionic drift and diffusion acting on the edges of conductive filament. We present a model that accounts for the observed increase of noise amplitude with the average device resistance. This work provides the demonstration and the physical foundation for the intentional stimulation of ionic telegraph noise which, on one hand, affects the programming operations performed with trains of identical pulses, as for neuromorphic computing, and on the other hand, it can open opportunities for applications relying on stochastic processes in nanoscaled devices.

Extended memory lifetime in spiking neural networks employing memristive synapses with nonlinear conductance dynamics

Spiking neural networks (SNNs) employing memristive synapses are capable of life-long online learning. Because of their ability to process and classify large amounts of data in real-time using compact and low-power electronic systems, they promise a substantial technology breakthrough. However, the critical issue that memristor-based SNNs have to face is the fundamental limitation in their memory capacity due to finite resolution of the synaptic elements, which leads to the replacement of old memories with new ones and to a finite memory lifetime. In this study we demonstrate that the nonlinear conductance dynamics of memristive devices can be exploited to improve the memory lifetime of a network. The network is simulated on the basis of a spiking neuron model of mixed-signal digital-analogue sub-threshold neuromorphic CMOS circuits, and on memristive synapse models derived from the experimental nonlinear conductance dynamics of resistive memory devices when stimulated by trains of identical pulses. The network learning circuits implement a spike-based plasticity rule compatible with both spike-timing and rate-based learning rules. In order to get an insight on the memory lifetime of the network, we analyse the learning dynamics in the context of a classical benchmark of neural network learning, that is hand-written digit classification. In the proposed architecture, the memory lifetime and the performance of the network are improved for memristive synapses with nonlinear dynamics with respect to linear synapses with similar resolution. These results demonstrate the importance of following holistic approaches that combine the study of theoretical learning models with the development of neuromorphic CMOS SNNs with memristive devices used to implement life-long on-chip learning.

Resistive switching control for conductive Si-nanocrystals embedded in Si/SiO2 multilayers

In this paper, we report on the enhanced control of resistive switching in multilayer Si/SiO₂ structures, which permit the formation of Si nanocrystals with a typical size of 5.88 nm and overall good shape homogeneity. The deposition of a different number of Si and SiO₂ bilayers (6, 8 and 10) allowed control of SET/RESET voltages in negative bias ranges 4.5-10 V and 6.3-13 V for six- and ten-bilayer devices, respectively. The corresponding resistance ratio between ON/OFF states varied in the ranges 10⁷-10⁵ for the aforementioned number of bilayers. Based on the result of XPS measurements, we suggest that the resistive switching in the studied system occurs due to the formation and annihilation of Si-Si and Si-O bonds, which serve as conductive pathways and isolating material, respectively.

Hierarchical Order in Dewetted Block Copolymer Thin Films on Chemically Patterned Surfaces

We investigated the dewetting process on flat and chemically patterned surfaces of ultrathin films (thickness between 2 and 15 nm) of a cylinder forming polystyrene- block-poly(methyl methacrylate) (PS- b-PMMA) spin coated on poly(styrene- r-methyl methacrylate) random copolymers (RCPs). When the PS- b-PMMA film dewets on a 2 nm-thick RCP layer, the ordering of the hexagonally packed PMMA cylinders in the dewetted structures extends over distances far exceeding the correlation length obtained in continuous block copolymer (BCP) films. As a result, micrometer-sized circular droplets featuring defectless single grains of self-assembled PS- b-PMMA with PMMA cylinders perpendicularly oriented with respect to the substrate are generated and randomly distributed on the substrate. Additionally, alignment of the droplets along micrometric lines was achieved by performing the dewetting process on large-scale chemically patterned stripes of 2 nm thick RCP films by laser lithography. By properly adjusting the periodicity of the chemical pattern, it was possible to tune and select the geometrical characteristics of the dewetted droplets in terms of maximum thickness, contact angle and diameter while maintaining the defectless single grain perpendicular cylinder morphology of the circular droplets.

Evidence of soft bound behaviour in analogue memristive devices for neuromorphic computing

The development of devices that can modulate their conductance under the application of electrical stimuli constitutes a fundamental step towards the realization of synaptic connectivity in neural networks. Optimization of synaptic functionality requires the understanding of the analogue conductance update under different programming conditions. Moreover, properties of physical devices such as bounded conductance values and state-dependent modulation should be considered as they affect storage capacity and performance of the network. This work provides a study of the conductance dynamics produced by identical pulses as a function of the programming parameters in an HfO2 memristive device. The application of a phenomenological model that considers a soft approach to the conductance boundaries allows the identification of different operation regimes and to quantify conductance modulation in the analogue region. Device non-linear switching kinetics is recognized as the physical origin of the transition between different dynamics and motivates the crucial trade-off between degree of analog modulation and memory window. Different kinetics for the processes of conductance increase and decrease account for device programming asymmetry. The identification of programming trade-off together with an evaluation of device variations provide a guideline for the optimization of the analogue programming in view of hardware implementation of neural networks.

Magnetization switching in high-density magnetic nanodots by a fine-tune sputtering process on a large-area diblock copolymer mask

Ordered magnetic nanodot arrays with extremely high density provide unique properties to the growing field of nanotechnology. To overcome the size limitations of conventional lithography, a fine-tuned sputtering deposition process on mesoporous polymeric template fabricated by diblock copolymer self-assembly is herein proposed to fabricate uniform and densely spaced nanometer-scale magnetic dot arrays. This process was successfully exploited to pattern, over a large area, sputtered Ni₈₀Fe₂₀ and Co thin films with thicknesses of 10 and 13 nm, respectively. Carefully tuned sputter-etching at a suitable glancing angle was performed to selectively remove the magnetic material deposited on top of the polymeric template, producing nanodot arrays (dot diameter about 17 nm). A detailed study of magnetization reversal at room temperature as a function of sputter-etching time, together with morphology investigations, was performed to confirm the synthesis of long-range ordered arrays displaying functional magnetic properties. Magnetic hysteresis loops of the obtained nanodot arrays were measured at different temperatures and interpreted via micromagnetic simulations to explore the role of dipole-dipole magnetostatic interactions between dots and the effect of magnetocrystalline anisotropy. The agreement between measurements and numerical modelling results indicates the use of the proposed synthesis technique as an innovative process in the design of large-area nanoscale arrays of functional magnetic elements.

Role of Al doping in the filament disruption in HfO2 resistance switches

Resistance switching devices, whose operation is driven by formation (SET) and dissolution (RESET) of conductive paths shorting and disconnecting the two metal electrodes, have recently received great attention and a deep general comprehension of their operation has been achieved. However, the link between switching characteristics and material properties is still quite weak. In particular, doping of the switching oxide layer has often been investigated only for looking at performance upgrade and rarely for a meticulous investigation of the switching mechanism. In this paper, the impact of Al doping of HfO₂ devices on their switching operations, retention loss mechanisms and random telegraph noise traces is investigated. In addition, phenomenological modeling of the switching operation is performed for device employing both undoped and doped HfO₂. We demonstrate that Al doping influences the filament disruption process during the RESET operation and, in particular, it contributes in preventing an efficient restoration of the oxide with respect to undoped devices.

Toward Lateral Length Standards at the Nanoscale Based on Diblock Copolymers

The self-assembly (SA) of diblock copolymers (DBCs) based on phase separation into different morphologies of small and high-density features is widely investigated as a patterning and nanofabrication technique. The integration of conventional top-down approaches with the bottom-up SA of DBCs enables the possibility to address the gap in nanostructured lateral length standards for nanometrology, consequently supporting miniaturization processes in device fabrication. On this topic, we studied the pattern characteristic dimensions (i.e., center-to-center distance L₀ and diameter D) of a cylinder-forming polystyrene-b-poly( methyl methacrylate) PS-b-PMMA (54 kg mol^-1, styrene fraction 70%) DBC when confined within periodic SiO₂ trenches of different widths (W, ranging between 75 and 600 nm) and fixed length (l, 5.7 μm). The characteristic dimensions of the PMMA cylinder structure in the confined configurations were compared with those obtained on a flat surface (L₀ = 27.8 ± 0.5 nm, D = 13.0 ± 1.0 nm). The analysis of D as a function of W evolution indicates that the eccentricity of the PMMA cylinders decreases as a result of the deformation of the cylinder in the direction perpendicular to the trenches. The center-to-center distance in the direction parallel to the long side of the trenches (L_0l) is equal to L₀ measured on the flat surface, whereas the one along the short side (L_0w) is subjected to an appreciable variation (ΔL_0w = 5 nm) depending on W. The possibility of finely tuning L_0w maintaining constant L_0l paves the way to the realization of a DBC-based transfer standard for lateral length calibration with periods in the critical range between 20 and 50 nm wherein no commercial transfer standards are available. A prototype transfer standard with cylindrical holes was used to calibrate the linear correction factor c(Δx')_xx' of an atomic force microscope for a scan length of Δx' = 1 μm. The relative standard uncertainty of the correction factor was only 1.3%, and the second-order nonlinear correction was found to be significant.

Analog Memristive Synapse in Spiking Networks Implementing Unsupervised Learning

Emerging brain-inspired architectures call for devices that can emulate the functionality of biological synapses in order to implement new efficient computational schemes able to solve ill-posed problems. Various devices and solutions are still under investigation and, in this respect, a challenge is opened to the researchers in the field. Indeed, the optimal candidate is a device able to reproduce the complete functionality of a synapse, i.e., the typical synaptic process underlying learning in biological systems (activity-dependent synaptic plasticity). This implies a device able to change its resistance (synaptic strength, or weight) upon proper electrical stimuli (synaptic activity) and showing several stable resistive states throughout its dynamic range (analog behavior). Moreover, it should be able to perform spike timing dependent plasticity (STDP), an associative homosynaptic plasticity learning rule based on the delay time between the two firing neurons the synapse is connected to. This rule is a fundamental learning protocol in state-of-art networks, because it allows unsupervised learning. Notwithstanding this fact, STDP-based unsupervised learning has been proposed several times mainly for binary synapses rather than multilevel synapses composed of many binary memristors. This paper proposes an HfO₂-based analog memristor as a synaptic element which performs STDP within a small spiking neuromorphic network operating unsupervised learning for character recognition. The trained network is able to recognize five characters even in case incomplete or noisy images are displayed and it is robust to a device-to-device variability of up to ±30%.

Rapid ordering of block copolymer thin films

Block-copolymers self-assemble into diverse morphologies, where nanoscale order can be finely tuned via block architecture and processing conditions. However, the ultimate usage of these materials in real-world applications may be hampered by the extremely long thermal annealing times-hours or days-required to achieve good order. Here, we provide an overview of the fundamentals of block-copolymer self-assembly kinetics, and review the techniques that have been demonstrated to influence, and enhance, these ordering kinetics. We discuss the inherent tradeoffs between oven annealing, solvent annealing, microwave annealing, zone annealing, and other directed self-assembly methods; including an assessment of spatial and temporal characteristics. We also review both real-space and reciprocal-space analysis techniques for quantifying order in these systems.

Strategies for Inorganic Incorporation using Neat Block Copolymer Thin Films for Etch Mask Function and Nanotechnological Application

Block copolymers (BCPs) and their directed self-assembly (DSA) has emerged as a realizable complementary tool to aid optical patterning of device elements for future integrated circuit advancements. Methods to enhance BCP etch contrast for DSA application and further potential applications of inorganic nanomaterial features (e.g., semiconductor, dielectric, metal and metal oxide) are examined. Strategies to modify, infiltrate and controllably deposit inorganic materials by utilizing neat self-assembled BCP thin films open a rich design space to fabricate functional features in the nanoscale regime. An understanding and overview on innovative ways for the selective inclusion/infiltration or deposition of inorganic moieties in microphase separated BCP nanopatterns is provided. Early initial inclusion methods in the field and exciting contemporary reports to further augment etch contrast in BCPs for pattern transfer application are described. Specifically, the use of evaporation and sputtering methods, atomic layer deposition, sequential infiltration synthesis, metal-salt inclusion and aqueous metal reduction methodologies forming isolated nanofeatures are highlighted in di-BCP systems. Functionalities and newly reported uses for electronic and non-electronic technologies based on the inherent properties of incorporated inorganic nanostructures using di-BCP templates are highlighted. We outline the potential for extension of incorporation methods to triblock copolymer features for more diverse applications. Challenges and emerging areas of interest for inorganic infiltration of BCPs are also discussed.

Solvothermal Vapor Annealing of Lamellar Poly(styrene)-block-poly(d,l-lactide) Block Copolymer Thin Films for Directed Self-Assembly Application

Solvothermal vapor annealing (STVA) was employed to induce microphase separation in a lamellar forming block copolymer (BCP) thin film containing a readily degradable block. Directed self-assembly of poly(styrene)-block-poly(d,l-lactide) (PS-b-PLA) BCP films using topographically patterned silicon nitride was demonstrated with alignment over macroscopic areas. Interestingly, we observed lamellar patterns aligned parallel as well as perpendicular (perpendicular microdomains to substrate in both cases) to the topography of the graphoepitaxial guiding patterns. PS-b-PLA BCP microphase separated with a high degree of order in an atmosphere of tetrahydrofuran (THF) at an elevated vapor pressure (at approximately 40-60 °C). Grazing incidence small-angle X-ray scattering (GISAXS) measurements of PS-b-PLA films reveal the through-film uniformity of perpendicular microdomains after STVA. Perpendicular lamellar orientation was observed on both hydrophilic and relatively hydrophobic surfaces with a domain spacing (L0) of ∼32.5 nm. The rapid removal of the PLA microdomains is demonstrated using a mild basic solution for the development of a well-defined PS mask template. GISAXS data reveal the through-film uniformity is retained following wet etching. The experimental results in this article demonstrate highly oriented PS-b-PLA microdomains after a short annealing period and facile PLA removal to form porous on-chip etch masks for nanolithography application.

Conductance tomography of conductive filaments in intrinsic silicon-rich silica RRAM

We present results from an imaging study of filamentary conduction in silicon suboxide resistive RAM devices. We used a conductive atomic force microscope to etch through devices while measuring current, allowing us to produce tomograms of conductive filaments. To our knowledge this is the first report of such measurements in an intrinsic resistance switching material.

Excellent nonlinearity of a selection device based on anti-series connected Zener diodes for ultrahigh-density bipolar RRAM arrays

A crossbar array is usually used for the high-density application of a resistive random access memory (RRAM) device. However, the cross-talk interference limits the increase in the integration density. In this paper, anti-series connected Zener diodes as a selection device are proposed for bipolar RRAM arrays. Simulation results show that, by using the anti-series connected Zener diodes as a selection device, the readout margin is sufficiently improved compared to that obtained without a selection device or with anti-parallel connected diodes as the selection device. The maximum size of the crossbar arrays with anti-series connected Zener diodes as a selection device over 1 TB is estimated by theoretical simulation. In addition, the feasibility of using the anti-series connected Zener diodes as a selection device for bipolar RRAM is demonstrated experimentally. These results indicate that anti-series connected Zener diodes as a selection device opens up great opportunities to realize ultrahigh-density bipolar RRAM arrays.