About

Professor Bilge Yildiz is a faculty member at MIT in the Department of Materials Science and Engineering and the Department of Nuclear Science and Engineering. Her research focuses on laying the scientific groundwork to enable next-generation electrochemical devices for energy conversion and information processing. She and her research-lab colleagues work on a variety of projects centered on the movement of charged atoms in materials. The scientific insights derived from her research guide the design of novel materials for brain-inspired energy-efficient computing, efficient and durable fuel cells, electrolytic water splitting, and solid-state batteries. Her approach combines computational and experimental analyses of electronic structure, defect mobility, and composition, utilizing in situ scanning probe and X-ray spectroscopy alongside first-principles calculations and atomistic simulations.

Research topics

• Computer Science
• Materials science
• Chemistry
• Nanotechnology
• Physics
• Engineering
• Electrical engineering
• Artificial Intelligence
• Engineering physics
• Optics
• Biology
• Inorganic chemistry
• Optoelectronics
• Systems engineering
• Thermodynamics
• Physical chemistry
• Computer architecture
• Chemical engineering
• Condensed matter physics
• Chemical physics
• Neuroscience

Selected publications

• Hydrogen‐Induced Electronic Modulation at MoS ₂ /SiO ₂ Interfaces

  Advanced Electronic Materials · 2026-05-15

  articleOpen accessSenior authorCorresponding

  ABSTRACT Two‐dimensional (2D) transition metal dichalcogenides (TMDs) are being explored in electronic and optoelectronic applications, including electrochemical random‐access memories (ECRAMs). ECRAMs are three‐terminal electrochemical neuromorphic devices in which a gate bias inserts or extracts ions (e.g., H + ) into or from a channel through a solid electrolyte, thereby modulating its conductivity. In thin‐film oxide channels, post‐pulse ion diffusion into the channel depth gives rise to a slow transient in obtaining the stable conductance state. Monolayer 2D TMD channels eliminate channel depth and could remove this contribution to transient, accelerating device programming. However, whether H insertion can modulate conductivity in 2D TMD channels remains to be determined. Here, we assess hydrogen incorporation at monolayer MoS 2 /SiO 2 interfaces using atomistic simulations with varying SiO 2 surface terminations. In the absence of sulfur vacancies, H favors incorporation on the SiO 2 surface when dangling bonds are present, leaving MoS 2 electronically decoupled from H. Once the oxide surface is saturated, H adsorbs onto or incorporates into MoS 2 , acting as an n‐type dopant. With sulfur vacancies, H stably incorporates into the vacancy and produces a similar n‐type effect. We experimentally verified these predictions in protonic ECRAM devices with monolayer MoS 2 channels: hydrogen insertion increased conductance, while hydrogen extraction decreased it, consistent with electron doping. Our findings confirm that H can modulate the conductivity of 2D monolayer MoS 2 channel at the interface with oxide electrolytes in ECRAMs and provide the underlying mechanisms.

  PublisherDOI

• Effect of protons on polaron mobility in transition metal oxides

  Physical Review Materials · 2026-03-09 · 1 citations

  articleSenior author

  Understanding polaron mobility in transition metal oxides is essential for advancing materials in proton-based electrochemical random access memory (ECRAM) neuromorphic devices. Using first-principles calculations, the authors quantify how protons affect polaron migration barriers in promising ECRAM channel materials WO${}_{3}$, V${}_{2}$O${}_{5}$, and MoO${}_{3}$. Beyond electrostatic attraction, which promotes proton-polaron pairing and increases migration barriers, protons also influence polaron transport directionality. By forming hydrogen bonds that distort metal-oxygen-metal linkages, they affect orbital overlap between metal sites and modulate migration barriers along these pathways. These results highlight a nontrivial role of protons in polaron transport and provide guidance for designing energy-efficient electrochemical devices.

  PublisherDOI

• HfO ₂ -based memristive synapses with asymmetrically extended p-n heterointerfaces for highly energy-efficient neuromorphic hardware

  Science Advances · 2026-03-20

  articleOpen access

  The escalating energy consumption of existing artificial intelligence hardware has become a serious global issue that demands immediate action. Neuromorphic computing offers promises to drastically reduce this footprint. Here, we introduce multicomponent p-type Hf(Sr,Ti)O 2 thin films for energy-efficient, resistive switching–based neuromorphic devices. We demonstrate interfacial memristors with ultralow switching currents (≤~10 −8 A), exceptional cycle-to-cycle and device-to-device uniformities, and retention >10 5 s. They reveal hundreds of ultralow conductance levels with a modulation range of >50 (without reaching any saturation) and reproducibly satisfy unsupervised learning rules. This performance originates from incorporating a self-assembled p-n heterointerface between p-type Hf(Sr,Ti)O 2 and n-type TiO x N y , resulting in a fully depleted space-charge layer asymmetrically extended into Hf(Sr,Ti)O 2 , a large built-in potential, and extremely low saturation current density under reverse bias. Ultralow conductance modulation is controlled by tuning p-n heterointerface’s energy-barrier height through electro-ionic charge migration. This materials-engineering strategy addresses energy consumption and variability in existing memristors, opening a pathway toward energy-efficient neuromorphic computing systems.

  PublisherDOI

• Atomistic Simulations of Ion Intercalation in 2D Channel Materials for Fast Conductivity Modulation in Electrochemical Random-Access Memory Devices

  ECS Meeting Abstracts · 2025-07-11

  articleSenior author

  Electrochemical ionic synapses (EIS), also known as electrochemical random-access memory (ECRAM), have emerged as a novel type of programmable resistor for crossbar arrays—one of the most promising architectures for implementing energy-efficient artificial neural networks [1-3]. EIS devices comprise three key functional layers: an ion reservoir, a solid electrolyte, and a channel. Through voltage-driven intercalation of mobile ions (e.g., H⁺, Li⁺, or Mg²⁺), the electronic conductivity of the channel can be finely modulated, enabling precise control over the resistance state of the device [4,5]. The operating speed and energy efficiency of EIS devices critically depend on ion mobility in the electrolyte and channel materials, as well as interfacial transfer properties. Mixed ionic and electronic conducting oxides, such as WO₃, MoO₃, and V₂O₅, have been previously investigated as channel materials [6]. However, their bulk nature necessitates 3D ion redistribution, leading to undesirably long conductivity settling times. In contrast, 2D materials, including monolayers of transition metal dichalcogenides (TMDs; e.g., MoS₂ and WS₂) and transition metal oxides (e.g., MoO₃), offer a promising alternative [7], but the interfacial ion diffusion characteristics and their impact on conductivity remain underexplored. In this work, we employ Density Functional Theory (DFT) to study H intercalation and diffusion at interfaces between solid electrolytes (e.g., SiO₂) and 2D channel materials. We identify the most stable intercalation sites, migration pathways, and the resulting effects of intercalation on the electronic structure of the channel. Additionally, we explore the influence of various SiO₂ surface terminations, including oxygen-terminated, silicon-terminated, and reconstructed surfaces with unsaturated or fully saturated Si and O bonds. For MoS₂ channels, we find that the SiO₂ surface termination significantly affects the charge state and intercalation site of H. Surfaces with fully saturated bonds enable barrier-free diffusion of H from the electrolyte to the channel. Once intercalated onto the MoS₂ surface, H induces in-gap states and shifts the Fermi level closer to the conduction band edge, leading to an increase in the channel’s conductivity. By assessing the electronic interactions between H and 2D channel materials, this work identifies optimal surface termination and material combinations to enhance ion migration and conductivity modulation, contributing to the development of high-performance, energy-efficient neuromorphic computing hardware. [1] Song, M.K., et al., ACS Nano , 17(13), pp.11994-12039, 2023. [2] Huang, M., et al., Advanced Materials , 35(37), 2205169, 2023. [3] Schwacke, M., et al., Advanced Electronic Materials , 2300577, 2024. [4] Yao, X., et al., Nature Communications , 11(1), 3134, 2020. [5] Onen, M., et al., Science , 377(6605), pp.539-543, 2022. [6] Siebenhofer, M., et al., Proceedings of 24th International Conference on Solid State Ionics (SSI24) , 2024. [7] Sahoo, S., et al., Scientific Reports , 14(1), 4371, 2024.

  PublisherDOI

• Electrochemical Oxidation in Garnet-Type Solid Electrolyte by Formation of Point Defects

  Chemistry of Materials · 2025-07-31 · 1 citations

  articleSenior authorCorresponding

  All-solid-state batteries hold greater promise for improving safety and energy density over conventional battery technology employing organic liquid electrolytes. One of the required features of a Li+ conducting solid electrolyte is electrochemical stability, attained thermodynamically or kinetically, within the targeted operating voltage and temperature ranges. Therefore, understanding of the oxidative or reductive degradation mechanism is important to allow the design of stable solid electrolyte materials. This work contributes to building an understanding of the oxidative degradation mechanism in lithium solid electrolytes at cell operating conditions. Here, we have focused on resolving the oxidative decomposition mechanism of Al-doped lithium garnet Li6.28Al0.24La3Zr2O12 (LLZO) as a state-of-the-art inorganic ceramic electrolyte. By combining experimental and computational analyses, we show that oxidation of LLZO occurs by simultaneous loss of oxygen and lithium from the structure, resulting in substoichiometric LLZO, at a moderate temperature (80 °C) and a high electrode potential (4.3 V vs Li/Li+). Based on X-ray absorption and diffraction analyses, we find that the zirconium coordination shells in LLZO contract while the crystal structure experiences positive chemical strain upon electrochemical oxidation. The results from ex situ structural characterization of both the local structure and crystal symmetry are supported by a substoichiometric LLZO with lithium and oxygen vacancies, modeled by density functional theory (DFT) calculations. These chemical and structural changes in LLZO suppress effective lithium-ion conductivity by an order of magnitude. Formation of lithium and oxygen vacancies in LLZO upon electrochemical oxidation is different from prior thermodynamic predictions of phase decomposition of LLZO. The difference here is that the experiments were conducted at near-room temperature, which can hinder the kinetics of phase separation, and thus, the resultant LLZO solid electrolyte is still single-phase but substoichiometric in Li and O. These findings contribute an important degradation mechanism of the electrolyte, relevant for practical operational conditions of solid-state batteries.

  PublisherDOI

• Electrochemical Random-Access Memory: Progress, Perspectives, and Opportunities

  Chemical Reviews · 2025-02-17 · 28 citations

  reviewOpen accessSenior authorCorresponding

  Non-von Neumann computing using neuromorphic systems based on analogue synaptic and neuronal elements has emerged as a potential solution to tackle the growing need for more efficient data processing, but progress toward practical systems has been stymied due to a lack of materials and devices with the appropriate attributes. Recently, solid state electrochemical ion-insertion, also known as electrochemical random access memory (ECRAM) has emerged as a promising approach to realize the needed device characteristics. ECRAM is a three terminal device that operates by tuning electronic conductance in functional materials through solid-state electrochemical redox reactions. This mechanism can be considered as a gate-controlled bulk modulation of dopants and/or phases in the channel. Early work demonstrating that ECRAM can achieve nearly ideal analogue synaptic characteristics has sparked tremendous interest in this approach. More recently, the realization that electrochemical ion insertion can be used to tune the electronic properties of many types of materials including transition metal oxides, layered two-dimensional materials, organic and coordination polymers, and that the changes in conductance can span orders of magnitude has further attracted interest in ECRAM as the basis for analogue synaptic elements for inference accelerators as well as for dynamical devices that can emulate a wide range of neuronal characteristics for implementation in analogue spiking neural networks. At its core, ECRAM shares many fundamental aspects with rechargeable batteries, where ion insertion materials are used extensively for their ability to reversibly store charge and energy. Computing applications, however, present drastically different requirements: systems will require many millions of devices, scaled down to tens of nanometers, all while achieving reliable electronic-state tuning at scaled-up rates and endurances, and with minimal energy dissipation and noise. In this review, we discuss the history, basic concepts, recent progress, as well as the challenges and opportunities for different types of ECRAM, broadly grouped by their primary mobile ionic charge carrier, including Li, protons, and oxygen vacancies.

  PublisherOA PDFDOI

• Improving durability and performance of solid oxide electrolyzers by controlling surface composition on oxygen electrodes

  2025-04-02

  reportOpen access

  Solid oxide electrolysis cell (SOEC) is a promising technology for high-efficiency energy conversion, enabling the production of hydrogen, syngas, synthetic fuels, and various commodity chemicals. Unlike traditional thermochemical processes, SOECs operate at elevated temperatures (600-850°C), benefiting from favorable thermodynamics and reaction kinetics. This makes them highly energy efficient compared to alkaline or polymer electrolyte membrane (PEM) electrolysis technologies. However, despite these advantages, SOECs face significant challenges related to performance degradation over time. A primary issue is the degradation of the oxygen electrode due to strontium (Sr) segregation and impurity poisoning from chromium (Cr) and sulfur (S). This is because the pathway to deposition of Cr and S include the reaction of Cr and S with the segregated SrO at the surface. Sr segregation leads to the formation of insulating compounds such as SrCrO4 and SrSO4, which block active sites, reduce oxygen exchange rates, and compromise the electrode's electrochemical stability. The degradation mechanisms involve complex interactions between the electrode material's surface chemistry, microstructure, and the operating environment. Sr segregation is particularly problematic because it facilitates the deposition of Cr and S impurities, exacerbating performance losses. Addressing these issues is critical to enhancing the durability and economic viability of SOEC technology. The primary goal of this project is to improve the durability and performance of SOECs by controlling the surface composition of the oxygen electrode. This is achieved by suppressing Sr segregation, thereby mitigating impurity poisoning pathways. The project aims to enhance the oxygen exchange rate, improve cell stability, and extend the operational lifespan of SOECs without necessitating major changes to electrode chemistry or stack components.

  PublisherOA PDFDOI

• Polaron and Strain Effects on Ion Migration in WO$_3$

  ArXiv.org · 2025-11-11

  preprintOpen accessSenior author

  Ion migration in WO$_3$ is a critical process for various technological applications, such as in batteries, electrochromic devices and energy-efficient brain-inspired computing devices. In this study, we investigate the migration mechanisms of H$^+$, Li$^+$, and Mg$^{2+}$ ions in monoclinic WO$_3$, and how energy barriers are affected by the presence of electron polarons and by lattice strain. Our approach in calculating the migration paths and barriers is based on density functional theory methods. The results show that the presence of polarons leads to association effects and lattice deformations that increase ion migration barriers. Therefore, the consideration of polarons is critical to accurately predict activation energies of ion migration. We further show that lattice strain modulates ion migration barriers, however, the impact of strain depends on the migrating ion. For protons that are embedded in the oxygen ion electronic shells and hop from donor to acceptor oxygens, compressive lattice strain accelerates migration by reducing the donor-acceptor distance. In contrast, the migration barriers of larger ions decrease with tensile lattice strain that increases the free space for the ion in the transition state. These insights into the effects of polarons and lattice strain are important for understanding and tuning properties of WO$_3$ when aiming for optimized device characteristics.

  PublisherOA PDFDOI

• Nonlinear Ion Dynamics Enable Spike Timing Dependent Plasticity of Electrochemical Ionic Synapses

  Advanced Materials · 2025-01-29 · 12 citations

  articleOpen accessSenior authorCorresponding

  Programmable synaptic devices that can achieve timing-dependent weight updates are key components to implementing energy-efficient spiking neural networks (SNNs). Electrochemical ionic synapses (EIS) enable the programming of weight updates with very low energy consumption and low variability. Here, the strongly nonlinear kinetics of EIS, arising from nonlinear dynamics of ions and charge transfer reactions in solids, are leveraged to implement various forms of spike-timing-dependent plasticity (STDP). In particular, protons are used as the working ion. Different forms of the STDP function are deterministically predicted and emulated by a linear superposition of appropriately designed pre- and post-synaptic neuron signals. Heterogeneous STDP is also demonstrated within the array to capture different learning rules in the same system. STDP timescales are controllable, ranging from milliseconds to nanoseconds. The STDP resulting from EIS has lower variability than other hardware STDP implementations, due to the deterministic and uniform insertion of charge in the tunable channel material. The results indicate that the ion and charge transfer dynamics in EIS can enable bio-plausible synapses for SNN hardware with high energy efficiency, reliability, and throughput.

  PublisherOA PDFDOI

• Reducibility, Adsorption Energies, Surface Acidity - Fundamental Material Properties for Fast Oxygen Exchange

  Research Square · 2025-03-28 · 1 citations

  preprintOpen access
  PublisherOA PDFDOI

Recent grants

• CAREER: "Stretching" Oxides to Lower Temperature Transport and Reactivity

  NSF · $516k · 2011–2016

Frequent coauthors

• Harry L. Tuller

  IIT@MIT

  74 shared

• Yan Chen

  45 shared

• Qiyang Lu

  Westlake University

  36 shared

• Mostafa Youssef

  American University in Cairo

  35 shared

• Sean R. Bishop

  Sandia National Laboratories California

  32 shared

• Dario Marrocchelli

  Massachusetts Institute of Technology

  31 shared

• Jiayue Wang

  Tianjin University

  28 shared

• Lixin Sun

  Harvard University

  25 shared

Awards & honors

• 2022 Rahmi M. Koç Medal of Science, Koç University
• 2022 Fellow, Royal Chemical Society
• 2021 Fellow, American Physical Society
• 2018 Ross Coffin Purdy Award, American Ceramic Society
• 2012 Charles W. Tobias Young Investigator Award, Electrochem…