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Determining the stability of chemical compounds is essential for advancing material discovery. In this study, we introduce a novel deep neural network model designed to predict a crystal's formation energy, which identifies its stability…

Materials Science · Physics 2026-04-21 V. Torlao , E. A. Fajardo

It is difficult to quantify structure-property relationships and to identify structural features of complex materials. The characterization of amorphous materials is especially challenging because their lack of long-range order makes it…

Soft Condensed Matter · Physics 2019-09-11 Kirk Swanson , Shubhendu Trivedi , Joshua Lequieu , Kyle Swanson , Risi Kondor

Materials that exhibit high nonlinear optical (NLO) susceptibilities are considered as promising candidates for a wide range of photonic and electronic applications. Here we argue that the ferroelectric nematic (NF) materials have…

Soft Condensed Matter · Physics 2022-03-22 C. L. Folcia , J. Ortega , R. Vidal , T. Sierra , J. Etxebarria

The ferroelectric nematic phase (N$_{\text{F}}$) has quickly become the most studied system in liquid crystal research. In this work, we investigate the origin of such polar structure by studying a compound for which the N$_{\text{F}}$…

Soft Condensed Matter · Physics 2024-11-14 Aitor Erkoreka , Nerea Sebastián , Alenka Mertelj , Josu Martinez-Perdiguero

The ferroelectric nematic phase (NF) is a recently discovered phase of matter in which the orientational order of the conventional nematic liquid crystal state is augmented with polar order. Atomistic simulations suggest that the polar NF…

Soft Condensed Matter · Physics 2023-09-26 Charles Parton-Barr , Helen Gleeson , Richard Mandle

Real-time simulation of elastic structures is essential in many applications, from computer-guided surgical interventions to interactive design in mechanical engineering. The Finite Element Method is often used as the numerical method of…

Machine Learning · Computer Science 2021-09-21 Alban Odot , Ryadh Haferssas , Stéphane Cotin

The design of materials with tailored properties is crucial for technological progress. However, most deep generative models focus exclusively on perfectly ordered crystals, neglecting the important class of disordered materials. To address…

Machine Learning · Computer Science 2026-02-05 Liming Wu , Rui Jiao , Qi Li , Mingze Li , Songyou Li , Shifeng Jin , Wenbing Huang

Recent advances in ferroelectrics highlight the role of three-dimensional (3D) polar entities in forming topological polar textures and generating giant electromechanical responses, during polarization rotation. However, current electron…

Materials Science · Physics 2025-06-10 Jinho Byun , Keeyong Lee , Myoungho Jeong , Eunha Lee , Jeongil Bang , Haeryong Kim , Geun Ho Gu , Sang Ho Oh

Uncovering the heterogeneity of cell populations is a long-standing goal in fields ranging from antimicrobial resistance to cancer research. Emerging technology platforms such as droplet microfluidics hold the promise to decipher cellular…

Image and Video Processing · Electrical Eng. & Systems 2020-01-29 Vasileios Anagnostidis , Benjamin Sherlock , Jeremy Metz , Philip Mair , Florian Hollfelder , Fabrice Gielen

After more than a hundred years of development, ferroelectric materials have demonstrated their strong potential to people, and more and more ferroelectric materials are being used in the research of ferroelectric transistors (FeFETs). As a…

Applied Physics · Physics 2024-06-21 Zexin Wang

The recent discovery of ferroelectric nematic liquid crystalline phases marks a major breakthrough in soft matter research. An intermediate phase, often observed between the nonpolar and the ferroelectric nematic phase, shows a distinct…

The recently discovered ferroelectric nematic liquids incorporate to the functional combination of fluidity, processability and anisotropic optical properties of nematic liquids, an astonishing range of physical properties derived from the…

Discovering functional crystalline materials entails navigating an immense combinatorial design space. While recent advances in generative artificial intelligence have enabled the sampling of chemically plausible compositions and…

Machine Learning · Computer Science 2025-11-11 Hyunsoo Park , Aron Walsh

Hydrofluoroolefins are considered the most promising next-generation refrigerants due to their extremely low global warming potential values, which can effectively mitigate the global warming effect. However, the lack of reliable…

Machine Learning · Computer Science 2025-07-30 Gang Wang , Peng Hu

The demand for renewable and environmentally friendly energy source has attracted extensive research on high performance catalysts. Ferroelectrics which are a class of materials with a switchable polarization are the unique and promising…

Materials Science · Physics 2021-11-30 Weitong Ding , Xiao Tang , Wei Li , Liangzhi Kou , Lei Liu

Colloidal self-assembly -- the spontaneous organization of colloids into ordered structures -- has been considered key to produce next-generation materials. However, the present-day staggering variety of colloidal building blocks and the…

Soft Condensed Matter · Physics 2021-06-29 Gabriele Maria Coli , Emanuele Boattini , Laura Filion , Marjolein Dijkstra

Crystalline materials, with symmetrical and periodic structures, exhibit a wide spectrum of properties and have been widely used in numerous applications across electronics, energy, and beyond. For crystalline materials discovery,…

Computational Engineering, Finance, and Science · Computer Science 2026-02-11 Zhenzhong Wang , Haowei Hua , Wanyu Lin , Ming Yang , Kay Chen Tan

The large-scale search for high-performing candidate 2D materials is limited to calculating a few simple descriptors, usually with first-principles density functional theory calculations. In this work, we alleviate this issue by extending…

Materials Science · Physics 2020-07-07 Victor Venturi , Holden Parks , Zeeshan Ahmad , Venkatasubramanian Viswanathan

First isolated in 2004, graphene monolayers display unique properties and promising technological potential in next generation electronics, optoelectronics, and energy storage. The simple yet effective methodology, mechanical exfoliation…

Materials Science · Physics 2022-12-02 Laura Zichi , Tianci Liu , Elizabeth Drueke , Liuyan Zhao , Gongjun Xu

Thermoelectric materials can achieve direct energy conversion between electricity and heat, thus can be applied to waste heat harvesting and solid-state cooling. The discovery of new thermoelectric materials is mainly based on experiments…

Materials Science · Physics 2024-05-07 Tao Fan , Artem R. Oganov