Publications by Benjamin Aaron Helfrecht

Ranking the synthesizability of hypothetical zeolites with the sorting hat

Michele Ceriotti, Benjamin Aaron Helfrecht

Zeolites are nanoporous alumino-silicate frameworks widely used as catalysts and adsorbents. Even though millions of siliceous networks can be generated by computer-aided searches, no new hypothetical framework has yet been synthesized. The needle-in-a-hay ...

2022

Improving sample and feature selection with principal covariates regression

Michele Ceriotti, Benjamin Aaron Helfrecht, Edgar Albert Engel, Sergei Kliavinek

Selecting the most relevant features and samples out of a large set of candidates is a task that occurs very often in the context of automated data analysis, where it improves the computational performance and often the transferability of a model. Here we ...

2021

Structure-Property Relationships in Complex Materials by Combining Supervised and Unsupervised Machine Learning

Benjamin Aaron Helfrecht

The work presented in this thesis combines supervised and unsupervised machine learning to examine structure-property relationships in databases of materials. While either supervised learning or unsupervised learning alone can be a powerful tool for assess ...

EPFL2021

Opportunities and challenges of 2D materials in back-end-of-line interconnect scaling

Benjamin Aaron Helfrecht, Alejandro Strachan

As the challenges in continued scaling of the integrated circuit technology escalate every generation, there is an urgent need to find viable solutions for both the front-end-of-line (transistors) and the back-end-of-line (interconnects). For the interconn ...

AMER INST PHYSICS2020

Structure-property maps with Kernel principal covariates regression

Michele Ceriotti, Benjamin Aaron Helfrecht, Guillaume André Jean Fraux

Data analyses based on linear methods constitute the simplest, most robust, and transparent approaches to the automatic processing of large amounts of data for building supervised or unsupervised machine learning models. Principal covariates regression (PC ...

2020

Atomic Motif Recognition in (Bio)Polymers: Benchmarks From the Protein Data Bank

Michele Ceriotti, Piero Gasparotto, Benjamin Aaron Helfrecht, Federico Giberti

Rationalizing the structure and structure–property relations for complex materials such as polymers or biomolecules relies heavily on the identification of local atomic motifs, e.g., hydrogen bonds and secondary structure patterns, that are seen as buildin ...

2019

i-PI 2.0: A universal force engine for advanced molecular simulations

Anne-Clémence Corminboeuf, Riccardo Petraglia, Sébastien Pierre Bienvenue, Michele Ceriotti, Bingqing Cheng, David Mark Wilkins, Przemyslaw Juda, Benjamin Aaron Helfrecht, Venkat Kapil, Mariana Rossi Carvalho, Robert Horst Meissner, Alice Cuzzocrea, Gareth Aneurin Tribello, Wei Fang

Progress in the atomic-scale modeling of matter over the past decade has been tremendous. This progress has been brought about by improvements in methods for evaluating interatomic forces that work by either solving the electronic structure problem explici ...

ELSEVIER SCIENCE BV2019

A new kind of atlas of zeolite building blocks

Michele Ceriotti, Benjamin Aaron Helfrecht, Rocio Semino Barbaresi, Giovanni Pireddu

We have analyzed structural motifs in the Deem database of hypothetical zeolites to investigate whether the structural diversity found in this database can be well-represented by classical descriptors, such as distances, angles, and ring sizes, or whether ...

2019