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In this study, a framework for the multi-objective materials discovery based on Bayesian approaches is developed. The capabilities of the framework are demonstrated on an example case related to the discovery of precipitation strengthened…

In the pursuit of advanced energy storage solutions, the crystal structure of ionic conductors plays a pivotal role in facilitating ion transport. The conventional structural design principle that compounds with the body-centered cubic…

Materials Science · Physics 2024-07-09 Tomoyasu Yokoyama , Kazuhide Ichikawa , Takuya Naruse , Kosei Ohura , Yukihiro Kaneko

The oxygen stoichiometry is an essential key to tune functional properties of advanced oxide materials and thus has motivated numerous studies of the oxygen off-stoichiometry diagram, with the aim to determine and control structural,…

With the rapid development of energy storage technology, high-performance solid-state electrolytes (SSEs) have become critical for next-generation lithium-ion batteries. These materials require high ionic conductivity, excellent…

Materials Science · Physics 2025-02-17 Hongwei Du , Jian Hui , Lanting Zhang , Hong Wang

We develop an automated computational modeling framework for rapid gradient-based design of multistable soft mechanical structures composed of non-identical bistable unit cells with appropriate geometric parameterization. This framework…

Numerical Analysis · Mathematics 2023-09-12 Mehran Mirramezani , Deniz Oktay , Ryan P. Adams

Manufacturing advanced materials and products with a specific property or combination of properties is often warranted. To achieve that it is crucial to find out the optimum recipe or processing conditions that can generate the ideal…

Machine Learning · Computer Science 2023-04-20 Hamed Khosravi , Taofeeq Olajire , Ahmed Shoyeb Raihan , Imtiaz Ahmed

Organic semiconductors are indispensable for today's display technologies in form of organic light emitting diodes (OLEDs) and further optoelectronic applications. However, organic materials do not reach the same charge carrier mobility as…

Soft Condensed Matter · Physics 2023-10-12 Patrick Reiser , Manuel Konrad , Artem Fediai , Salvador Léon , Wolfgang Wenzel , Pascal Friederich

Designing optimal formulations is a major challenge in developing electrolytes for the next generation of rechargeable batteries due to the vast combinatorial design space and complex interplay between multiple constituents. Machine…

We developed a convolutional neural network (CNN) model capable of predicting the performance of various ion-doped NASICON compounds by leveraging extensive datasets from prior experimental investigation.The model demonstrated high accuracy…

Materials Science · Physics 2025-01-13 Zirui Zhao , Xiaoke Wang , Si Wu , Pengfei Zhou , Qian Zhao , Guanping Xu , Kaitong Sun , Hai-Feng Li

The recent emergence of lead-halide perovskites as active layer materials for thin film semiconductor devices including solar cells, light emitting diodes, and memristors has motivated the development of several new drift-diffusion models…

Oxygen ion conductors are indispensable materials for such as solid oxide fuel cells, sensors, and membranes. Despite extensive research across diverse structural families, systematic data enabling comparative analysis remain scarce. Here,…

Materials Science · Physics 2026-01-26 Seong-Hoon Jang , Shin Kiyohara , Hitoshi Takamura , Yu Kumagai

New highly oxygen-active materials may enhance many energy-related technologies by enabling efficient oxygen-ion transport at lower temperatures, e.g., below 400 Celsius. Interstitial oxygen conductors have the potential to realize such…

Materials Science · Physics 2024-05-30 Jun Meng , Md Sariful Sheikh , Ryan Jacobs , Jian Liu , William O. Nachlas , Xiangguo Li , Dane Morgan

Active, selective and stable catalysts are imperative for sustainable energy conversion, and engineering materials with such properties are highly desired. High-entropy alloys (HEAs) offer a vast compositional space for tuning such…

Machine learning (ML) models utilizing structure-based features provide an efficient means for accurate property predictions across diverse chemical spaces. However, obtaining equilibrium crystal structures typically requires expensive…

Materials Science · Physics 2021-04-22 Yunxing Zuo , Mingde Qin , Chi Chen , Weike Ye , Xiangguo Li , Jian Luo , Shyue Ping Ong

This work presents a fast and scalable approach for predicting surface stability and equilibrium crystal morphology in ionic materials using electrostatic analysis. The method constructs stoichiometric slab terminations and evaluates their…

Materials Science · Physics 2026-04-30 Sourav Baiju , Payam Kaghazchi

Solid-state electrolytes (SSE) with high ion conductivity are pivotal for the development and large-scale adoption of green-energy conversion and storage technologies such as fuel cells, electrocatalysts and solid-state batteries. Yet, SSE…

Materials Science · Physics 2022-11-30 Cibrán López , Agustí Emperador , Edgardo Saucedo , Riccardo Rurali , Claudio Cazorla

Recently, machine-learning approaches have accelerated computational materials design and the search for advanced solid electrolytes. However, the predictors are currently limited to static structural parameters, which may not fully account…

Materials Science · Physics 2026-01-19 Jiyeon Kim , Donggeon Lee , Dongwoo Lee , Xin Li , Yea-Lee Lee , Sooran Kim

Anion-conductive polymer membranes have attracted considerable attention as solid electrolytes for alkaline fuel cells and electrolysis cells. Their hydroxide ion conductivity varies depending on factors such as the type and distribution of…

Soft Condensed Matter · Physics 2025-05-27 Ryo Murakami , Kenji Miyatake , Ahmed Mohamed Ahmed Mahmoud , Hideki Yoshikawa , Kenji Nagata

Optimization of materials performance for specific applications often requires balancing multiple aspects of materials functionality. Even for the cases where generative physical model of material behavior is known and reliable, this often…

Materials Science · Physics 2021-12-15 Arpan Biswas , Anna N. Morozovska , Maxim Ziatdinov , Eugene A. Eliseev , Sergei V. Kalinin

Designing molecules that must satisfy multiple, often conflicting objectives is a central challenge in molecular discovery. The enormous size of chemical space and the cost of high-fidelity simulations have driven the development of machine…

Machine Learning · Statistics 2025-12-22 Madhav R. Muthyala , Farshud Sorourifar , Tianhong Tan , You Peng , Joel A. Paulson