Publications (27)
TBHubbard: tight-binding and extended Hubbard model database for metal-organic frameworks
Pamela C. Carvalho, Federico Zipoli, Alan C. Duriez +5
Metal-organic frameworks (MOFs) are porous materials composed of metal ions and organic linkers. Due to their chemical diversity, MOFs can support a broad range of applications in…
High-frequency performance of scaled carbon nanotube array field-effect transistors
Mathias Steiner, Michael Engel, Yu-Ming Lin +10
We report the radio-frequency performance of carbon nanotube array transistors that have been realized through the aligned assembly of highly separated, semiconducting carbon nanot…
High accuracy capillary network representation in digital rock reveals permeability scaling functions
Rodrigo F. Neumann, Mariane Barsi-Andreeta, Everton Lucas-Oliveira +4
Permeability is the key parameter for quantifying fluid flow in porous rocks. Knowledge of the spatial distribution of the connected pore space allows, in principle, to predict the…
A black phosphorus photo-detector for multispectral, high-resolution imaging
Michael Engel, Mathias Steiner, Phaedon Avouris
Black phosphorus is a layered semiconductor that is intensely researched in view of applications in optoelectronics. In this Letter, we investigate a multi-layer black phosphorus p…
How does the substrate affect the Raman and excited state spectra of a carbon nanotube?
Mathias Steiner, Marcus Freitag, James C. Tsang +4
We study the optical properties of a single, semiconducting single-walled carbon nanotube (CNT) that is partially suspended across a trench and partially supported by a SiO2-substr…
Prediction of Adsorption in Nano-Pores with Graph Neural Networks
Guojing Cong, Anshul Gupta, Rodrigo Neumann +3
We investigate the graph-based convolutional neural network approach for predicting and ranking gas adsorption properties of crystalline Metal-Organic Framework (MOF) adsorbents fo…
CRAFTED -- An exploratory database of simulated adsorption isotherms of metal-organic frameworks
Felipe Lopes Oliveira, Conor Cleeton, Rodrigo Neumann Barros Ferreira +4
Grand Canonical Monte Carlo is an important method for performing molecular-level simulations and assisting the study and development of nanoporous materials for gas capture applic…
Automated, LLM enabled extraction of synthesis details for reticular materials from scientific literature
Viviane Torres da Silva, Alexandre Rademaker, Krystelle Lionti +12
Automated knowledge extraction from scientific literature can potentially accelerate materials discovery. We have investigated an approach for extracting synthesis protocols for re…
Origin of photoresponse in black phosphorus photo-transistors
Tony Low, Michael Engel, Mathias Steiner +1
We study the origin of photocurrent generated in doped multilayer BP photo-transistors, and find that it is dominated by thermally driven thermoelectric and bolometric processes. T…
Scaling active spaces in simulations of surface reactions through sample-based quantum diagonalization
Marco Antonio Barroca, Tanvi Gujarati, Vidushi Sharma +6
Quantum-chemical simulations are essential for predicting energies of chemical reactions. Accurately solving the many-body Schrödinger equation for reagent and product states of m…
Equivariant Interatomic Potentials without Tensor Products
Thiago Reschützegger, Sarp Aykent, Gabriel Jacob Perin +5
Foundational machine-learned interatomic potentials have emerged as powerful tools for atomistic simulations, promising near first-principles accuracy across diverse chemical space…
Efficient narrow-band light emission from a single carbon nanotube p-n diode
Thomas Mueller, Megumi Kinoshita, Mathias Steiner +4
Electrically-driven light emission from carbon nanotubes could be exploited in nano-scale lasers and single-photon sources, and has therefore been the focus of much research. Howev…
Exploration of Quantum Computing in Materials Discovery for Direct Air Capture Applications
Marco Antonio Barroca, Rodrigo Neumann Barros Ferreira, Mathias Steiner
Direct air capture (DAC) of carbon dioxide is a promising method for mitigating climate change. Solid sorbents, such as metal-organic frameworks, are currently being tested for DAC…
Mode-selective Raman imaging of metal-organic frameworks reveals surface heterogeneities of single HKUST-1 crystals
Matheus Esteves Ferreira, Mariana Del Grande, Felipe Lopes Oliveira +6
Metal organic frameworks (MOFs) are nanoporous materials with high surface-to-volume ratio that have potential applications as gas sorbents. Sample quality is, however, often compr…
Graphene-enabled, directed nanomaterial placement from solution for large-scale device integration
Michael Engel, Damon B. Farmer, Jaione Tirapu Azpiroz +6
Controlled placement of nanomaterials at predefined locations with nanoscale precision remains among the most challenging problems that inhibit their large-scale integration in the…
A metric for wettability at the nanoscale
Ronaldo Giro, Peter W. Bryant, Michael Engel +2
Wettability is the affinity of a liquid for a solid surface. For energetic reasons, macroscopic drops of liquid are nearly spherical away from interfaces with solids, and any local…
Light-matter interaction in a microcavity-controlled graphene transistor
Michael Engel, Mathias Steiner, Antonio Lombardo +4
Graphene has extraordinary electronic and optical properties and holds great promise for applications in photonics and optoelectronics. Demonstrations including high-speed photodet…
Thermal infrared emission reveals the Dirac point movement in biased graphene
Marcus Freitag, Hsin-Ying Chiu, Mathias Steiner +2
Graphene is a 2-dimensional material with high carrier mobility and thermal conductivity, suitable for high-speed electronics. Conduction and valence bands touch at the Dirac point…
Computing band gaps of periodic materials via sample-based quantum diagonalization
Alan Duriez, Pamela C. Carvalho, Marco Antonio Barroca +7
A key objective of computational solid state physics is to predict electronic properties of periodic materials. However, electronic structure simulations based on density functiona…
Discovery of Novel Reticular Materials for Carbon Dioxide Capture using GFlowNets
Flaviu Cipcigan, Jonathan Booth, Rodrigo Neumann Barros Ferreira +2
Artificial intelligence holds promise to improve materials discovery. GFlowNets are an emerging deep learning algorithm with many applications in AI-assisted discovery. By using GF…
Artificial intelligence enables mobile soil analysis for sustainable agriculture
Ademir Ferreira da Silva, Ricardo Luis Ohta, Jaione Tirapu Azpiroz +13
For optimizing production yield while limiting negative environmental impact, sustainable agriculture benefits greatly from real-time, on-the-spot analysis of soil at low cost. Col…
Room-Temperature Quantum-Confined Stark Effect in Atomically Thin Semiconductor
Michael Engel, Mathias Steiner
Electric field-controlled, two-dimensional (2D) exciton dynamics in transition metal dichalcogenide monolayers is a current research focus in condensed matter physics. We have expe…
pyMSER -- An open-source library for automatic equilibration detection in molecular simulations
Felipe Lopes Oliveira, Binquan Luan, Pierre Mothé Esteves +2
Automated molecular simulations are used extensively for predicting material properties. Typically, these simulations exhibit two regimes: a dynamic equilibration part, followed by…
Energy dissipation in graphene field-effect transistors
Marcus Freitag, Mathias Steiner, Yves Martin +4
We measure the temperature distribution in a biased single-layer graphene transistor using Raman scattering microscopy of the 2D-phonon band. Peak operating temperatures of 1050 K…
Full scale, microscopically resolved tomographies of sandstone and carbonate rocks augmented by experimental porosity and permeability values
Matheus Esteves Ferreira, Mariana Del Grande, Rodrigo Neumann Barros Ferreira +9
We report a dataset containing full-scale, 3D images of rock plugs augmented by petrophysical lab characterization data for application in digital rock and capillary network analys…
Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions
Yuri Alexeev, Maximilian Amsler, Paul Baity +124
Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of e…
Power dissipation and electrical breakdown in black phosphorus
Michael Engel, Mathias Steiner, Shu-Jen Han +1
We report operating temperatures and heating coefficients measured in a multi-layer black phosphorus device as a function of injected electrical power. By combining micro-Raman spe…