• Skip to primary navigation
  • Skip to main content
  • Skip to primary sidebar
  • About REMIND
  • Research
  • Publications
  • People
  • News
  • Opportunities
  • Contact Us

Reconfigurable Electronic Materials Inspired by Nonlinear Neuron Dynamics

Texas A&M University College of Engineering

Publications

Tuning the Spin Transition and Carrier Type in Rare-Earth Cobaltates via Compositional Complexity

Alan Zhang, Sangheon Oh, Byoung Ki Choi, Eli Rotenberg, Timothy D. Brown, Catalin D. Spataru, Eli Kinigstein, Jinghua Guo, Joshua D. Sugar, Elena Salagre, Arantzazu Mascaraque, Enrique G. Michel, Alison C. Shad, Jacklyn Zhu, Matthew D. Witman, Suhas Kumar, A. Alec Talin, Elliot J. Fuller

Tuning the Spin Transition and Carrier Type in Rare-Earth Cobaltates via Compositional Complexity

August 23, 2024

There is growing interest in material candidates with properties that can be engineered beyond traditional design limits. Compositionally complex oxides (CCO), often called high entropy oxides, are excellent candidates, wherein a lattice site shares more than four cations, forming single-phase solid solutions with unique properties. However, the nature of compositional complexity in dictating properties remains unclear, with characteristics that are difficult to calculate from first principles. Here, compositional complexity is demonstrated as a tunable parameter in a spin-transition oxide semiconductor La1− x(Nd, Sm, Gd, Y)x/4CoO3, by varying the population x of rare earth cations over 0.00≤ x≤ 0.80. Across the series, increasing complexity is revealed to systematically improve crystallinity, increase the amount of electron versus hole carriers, and tune the spin transition temperature and on-off ratio. At high a population (x = 0.8), Seebeck measurements indicate a crossover from hole-majority to electron-majority conduction without the introduction of conventional electron donors, and tunable complexity is proposed as new method to dope semiconductors. First principles calculations combined with angle resolved photoemission reveal an unconventional doping mechanism of lattice distortions leading to asymmetric hole localization over electrons. Thus, tunable complexity is demonstrated as a facile knob to improve crystallinity, tune electronic transitions, and to dope semiconductors beyond traditional means.

Revealing Complete Atomic-Scale Switching Pathways in van der Waals Ferroelectrics

Xinyan Li, Chuqiao Shi, Kenna Ashen, Nannan Mao, Saagar Kolachina, Tianyi Zhang, Ramamoorthy Ramesh, Jing Kong, Xiaofeng Qian, Yimo Han

Revealing Complete Atomic-Scale Switching Pathways in van der Waals Ferroelectrics

October 3, 2025

Two-dimensional (2D) van der Waals (vdW) materials hold the potential for ultrascaled ferroelectric (FE) devices due to their silicon compatibility and robust polarization down to atomic scale. However, the inherently weak vdW interactions enable facile sliding between layers, introducing complexities beyond those encountered in conventional ferroelectric materials and presenting substantial challenges in uncovering intricate switching pathways. Here, we combine atomic-resolution imaging under in situ electrical biasing conditions with first-principles calculations to unravel the atomic-scale switching mechanisms in SnSe, a vdW group IV monochalcogenide. Our results uncover the coexistence of a consecutive 90° switching pathway and a direct 180° switching pathway from antiferroelectric (AFE) to FE order in this vdW system. Atomic-scale investigations and strain analysis reveal that the switching processes simultaneously induce interlayer sliding and compressive strain, while the lattice remains coherent despite the presence of multidomain structures. These findings elucidate vdW ferroelectric switching dynamics at atomic scale and lay the foundation for the rational design of 2D ferroelectric nanodevices.

Graphlet Decomposition Using Random-Walk Memristors

Kyung Seok Woo; Nestor Ghenzi; A. Alec Talin; Hyungjun Park; Sangheon Oh; Cheol Seong Hwang

Graphlet Decomposition Using Random-Walk Memristors

February 18, 2025

Although memristor crossbars are a promising post-CMOS solution for computing, sneak currents and stochastic switching are two persistent challenges that impede their practical implementation. Here, we show how both issues can, in fact, be taken advantage for energy efficient computing. Using sneak paths to represent graphlets and stochasticity in hybrid volatile-nonvolatile memristors to mimic random walks, we perform graphlet decomposition and analysis, which are computationally hard problem with various applications, such as social networking and genome slicing.

Origin of Stabilization of Ligand-Centered Mixed Valence Ruthenium Azopyridine Complexes: DFT Insights for Neuromorphic Applications

A. Avilés, S. Perez Beltran, M. Ghotbi, A. J. Ferguson, J. L. Blackburn, M. Y. Darensbourg, P. B. Balbuena

Origin of Stabilization of Ligand-Centered Mixed Valence Ruthenium Azopyridine Complexes: DFT Insights for Neuromorphic Applications

June 10, 2025

Redox-driven conductance changes are critical processes in molecular- and coordination-complex-based memristive thin films and devices that are envisioned for neuromorphic technologies, but fundamental mechanisms of conductance switching are not fully understood. Here, we explore charge disproportionation (CD) processes in [RuIIL2](PF6)2 molecular systems that intrinsically involve interfragment charge transfer (IFCT). Using a combination of ab initio molecular dynamics simulation (AIMD), time-dependent density functional theory (TD-DFT), and density functional theory (DFT) calculations, we investigate the electron transfer mechanisms and the roles of temperature and cell volumetric expansion in facilitating the counterion movements and electronic transitions required for low-cost IFCT and charge redistribution. A detailed analysis of the density of states and TD-DFT calculations highlights that unpaired electrons play a crucial role in low-energy transitions, with the azo (N═N) groups of the ligand serving as the primary sites for electronic transport between molecular fragments, further stabilizing the asymmetric state. Localization of added electrons on azo ligands occurs with negligible change at the Ru centers, supported by atomic volume expansions up to +4.74 bohr3, and goes along with a progressive reduction of the HOMO–LUMO gap across redox states, suggesting enhanced conductivity. The TD-DFT analysis reveals a dominant IFCT excitation at 2082.76 nm in the doubly reduced (22) state, while a stabilization energy of 1.20 eV of the asymmetric (13) state relative to the symmetric (22) state is predicted by constrained DFT. Periodic DFT and AIMD simulations emulating a molecular film show that the stabilization of the asymmetric state, relative to a symmetric one, translates in net charge separation values (order of ∼0.33 e) that are strongly linked to increased counterion mobility (average counterion displacements exceeding 0.7 Å per atom during CD events) and the involvement of azo groups in electron redistribution. These findings, which align with previously reported experimental and computational data, provide key insights into the IFCT mechanisms and electronic transport facilitated by azo groups, with important implications for redox-driven memristive and neuromorphic technologies.

Mechanisms enabling reconfigurability and long-term retention in vanadium oxide electrochemical memory

B. T. Zutter, S. Oh, T. D. Brown, J. Anderson, S. Perez Beltran, S. Bishop, P. Finnegan, A. Ievlev, Y. Li, J. Sugar, H-E Lai, B. A. Arenas Blanco, A. Lopez-Meza, S. Kumar, E. J. Fuller, R. S. Williams, P. B. Balbuena, A. A. Talin

Mechanisms enabling reconfigurability and long-term retention in vanadium oxide electrochemical memory

August 6, 2025

Phase coexistence in nanoscale electrochemical random-access memory (ECRAM) has recently been demonstrated to enable both information storage and extraordinary reconfigurability. These proof-of-principle demonstrations have left the mechanistic details of such a process unresolved. Particularly, the mechanisms that stabilize the multiple phases, and the underlying processes behind sustained memory retention, remain unclear, and are necessary to design such devices. Here we report microscale ECRAM devices composed of V⁢O𝑥, which enables us to directly probe the active region in an operando fashion using optical techniques. Using Raman mapping, we show the phase coexistence driven by the electrochemical injection of O vacancies to be spatially uniform (i.e., with no filaments). The stability was observed to be unusually long, with 1% loss over 14 years in ambient conditions. First-principles calculations of the oxygen vacancy formation energies in V⁢O𝑥 further support the thermodynamic coexistence of multiple V⁢O𝑥 phases and clarify the origin of the observed long-term retention in the ECRAM devices. Further, we demonstrate single devices that can be voltage programmed to exhibit synaptic, neuronal, and reconfigurable logic gate functionalities. Therefore, we not only uncover the phase coexistence mechanism that may help device design, but also demonstrate the circuit-level applications of reconfigurability.

Materials Selection Principles for Designing Electro-Thermal Neurons

Fatme Jardali, Jenny L. Chong, Yeonju Yu, R. Stanley Williams, Suhas Kumar, Patrick J. Shamberger, Timothy D. Brown

Materials Selection Principles for Designing Electro-Thermal Neurons

August 6, 2025

Artificial neurons exhibiting volatile threshold switching and action potential-like oscillations are crucial for brain-inspired computing. While Complimentary Metal-Oxide-Semiconductor (CMOS)-based strategies require hundreds of transistors to simulate each neuron, neuronal oscillations arise spontaneously in individual electro-thermal devices due to nonlinearities like the Mott transition in VO2. Despite improved understanding of the physics, quantitative connections between neuronal performance and material properties remain under-explored, preventing predictive neuron design and rational materials selection. In this work, a physics-aware forward design methodology is developed for interrogating a wide palette of materials with properties varying by orders of magnitude, and their performance (high frequency, high dynamical reconfigurability and low power) under external circuit and device geometry constraints is assessed. The space of viable materials is identified to be much larger than previously recognized, with candidates from a range of materials classes, including Ge, GaP and MoS2. CMOS-compatible performance (such as 100 GHz oscillating frequencies) can be achieved with CMOS-compatible node sizes (≈10 nm). Finally, combinations of material properties yielding desired neuronal performance under uncertain design constraints are considered. This work solidifies forward design principles for electro-thermal neuron devices, a necessary pre-condition for inverse design from desired neuronal performance to required materials properties.

Localized Conduction Channels in Memristors

Kyung Seok Woo, R. Stanley Williams, Suhas Kumar

Localized Conduction Channels in Memristors

December 19, 2024

Since the early 2000s, the impending end of Moore’s scaling, as the physical limits to shrinking transistors have been approached, has fueled interest in improving the functionality and efficiency of integrated circuits by employing memristors or two-terminal resistive switches. Formation (or avoidance) of localized conducting channels in many memristors, often called “filaments”, has been established as the basis for their operation. While we understand some qualitative aspects of the physical and thermodynamic origins of conduction localization, there are not yet quantitative models that allow us to predict when they will form or how large they will be. Here we compile observations and explanations of channel formation that have appeared in the literature since the 1930s, show how many of these seemingly unrelated pieces fit together, and outline what is needed to complete the puzzle. This understanding will be a necessary predictive component for the design and fabrication of post-Moore’s-era electronics.

Electrically-Driven Metal-Insulator Transitions Emerging from Localizing Current Density and Temperature

Adelaide Bradicich, Yeonju Yu, Timothy D. Brown, Fatme Jardali, Suhas Kumar, R. Stanley Williams, Patrick J. Shamberger

Electrically-Driven Metal-Insulator Transitions Emerging from Localizing Current Density and Temperature

March 27, 2025

Negative differential resistance (NDR) is a key electronic response enabling two-terminal artificial neurons that can be achieved through different physical phenomena, including phase-homogeneous current density and temperature (electro-thermal) localizations and spatially-localized metal-insulator phase transitions (MITs). These two effects have been observed to occur sequentially in select electrically-biased transition metal oxides. However, it is unknown why and under what conditions localizing behaviors precede MITs, particularly as a function of device length scale. To this end, the interplay between phase-homogeneous electro-thermal localizations and MITs is investigated in a 3D multiphysics simulation of a lateral thin film device, using the material properties of the prototype MIT material VO2. These findings demonstrate that the MIT is nucleated through dynamically localizing current density and temperature. A critical device width (≈0.7 µm in this study) is identified, below which both the electrically-induced electro-thermal and phase inhomogeneities cease to appear. It is demonstrated that the formation of spatial inhomogeneities directly relates to device dimensions, and demonstrate the decoupling of NDR from the MIT through device scaling relationships. These results provide insight into the material phenomena underlying the material’s electrical responses, clarifying conditions under which spatial inhomogeneities form in electrically-biased MIT materials.

Memristors with Tunable Volatility for Reconfigurable Neuromorphic Computing

Kyung Seok Woo, Hyungjun Park, Nestor Ghenzi, A Alec Talin, Taeyoung Jeong, Jung-Hae Choi, Sangheon Oh, Yoon Ho Jang, Janguk Han, R Stanley Williams, Suhas Kumar, Cheol Seong Hwang

Memristors with Tunable Volatility for Reconfigurable Neuromorphic Computing

June 19, 2024

Neuromorphic computing promises an energy-efficient alternative to traditional digital processors in handling data-heavy tasks, primarily driven by the development of both volatile (neuronal) and nonvolatile (synaptic) resistive switches or memristors. However, despite their energy efficiency, memristor-based technologies presently lack functional tunability, thus limiting their competitiveness with arbitrarily programmable (general purpose) digital computers. This work introduces a two-terminal bilayer memristor, which can be tuned among neuronal, synaptic, and hybrid behaviors. The varying behaviors are accessed via facile control over the filament formed within the memristor, enabled by the interplay between the two active ionic species (oxygen vacancies and metal cations). This solution is unlike single-species ion migration employed in most other memristors, which makes their behavior difficult to control. By reconfiguring a single crossbar array of hybrid memristors, two different applications that usually require distinct types of devices are demonstrated – reprogrammable heterogeneous reservoir computing and arbitrary non-Euclidean graph networks. Thus, this work outlines a potential path toward functionally reconfigurable postdigital computers.

Tunable stochastic memristors for energy-efficient encryption and computing

Kyung Seok Woo, Janguk Han, Su-in Yi, Luke Thomas, Hyungjun Park, Suhas Kumar, Cheol Seong Hwang

Tunable stochastic memristors for energy-efficient encryption and computing

April 15, 2024

Information security and computing, two critical technological challenges for post-digital computation, pose opposing requirements – security (encryption) requires a source of unpredictability, while computing generally requires predictability. Each of these contrasting requirements presently necessitates distinct conventional Si-based hardware units with power-hungry overheads. This work demonstrates Cu0.3Te0.7/HfO2 (‘CuTeHO’) ion-migration-driven memristors that satisfy the contrasting requirements. Under specific operating biases, CuTeHO memristors generate truly random and physically unclonable functions, while under other biases, they perform universal Boolean logic. Using these computing primitives, this work experimentally demonstrates a single system that performs cryptographic key generation, universal Boolean logic operations, and encryption/decryption. Circuit-based calculations reveal the energy and latency advantages of the CuTeHO memristors in these operations. This work illustrates the functional flexibility of memristors in implementing operations with varying component-level requirements.

  • 1
  • Go to page 2
  • Go to page 3
  • Go to page 4
  • Go to Next Page »

Google Scholar link

View all publications on our Google Scholar profile.

Recent Publications

  • Tuning the Spin Transition and Carrier Type in Rare-Earth Cobaltates via Compositional Complexity
  • Revealing Complete Atomic-Scale Switching Pathways in van der Waals Ferroelectrics
  • Graphlet Decomposition Using Random-Walk Memristors
  • Origin of Stabilization of Ligand-Centered Mixed Valence Ruthenium Azopyridine Complexes: DFT Insights for Neuromorphic Applications
  • Mechanisms enabling reconfigurability and long-term retention in vanadium oxide electrochemical memory

© 2016–2026 Reconfigurable Electronic Materials Inspired by Nonlinear Neuron Dynamics Log in

Texas A&M Engineering Experiment Station Logo
  • College of Engineering
  • twitter
  • State of Texas
  • Open Records
  • Risk, Fraud & Misconduct Hotline
  • Statewide Search
  • Site Links & Policies
  • Accommodations
  • Environmental Health, Safety & Security
  • Employment