Publications by authors named "Patrick W V Butler"

Article Synopsis
  • Participants from 22 research groups utilized various methods, including periodic DFT-D methods, machine learning models, and empirical force fields to assess crystal structures generated from standardized sets.
  • The findings indicate that DFT-D methods generally aligned well with experimental results, while one machine learning approach showed significant promise; however, the need for more efficient research methods was emphasized due to resource consumption.
View Article and Find Full Text PDF

A seventh blind test of crystal structure prediction was organized by the Cambridge Crystallographic Data Centre featuring seven target systems of varying complexity: a silicon and iodine-containing molecule, a copper coordination complex, a near-rigid molecule, a cocrystal, a polymorphic small agrochemical, a highly flexible polymorphic drug candidate, and a polymorphic morpholine salt. In this first of two parts focusing on structure generation methods, many crystal structure prediction (CSP) methods performed well for the small but flexible agrochemical compound, successfully reproducing the experimentally observed crystal structures, while few groups were successful for the systems of higher complexity. A powder X-ray diffraction (PXRD) assisted exercise demonstrated the use of CSP in successfully determining a crystal structure from a low-quality PXRD pattern.

View Article and Find Full Text PDF

Computational crystal structure prediction (CSP) is an increasingly powerful technique in materials discovery, due to its ability to reveal trends and permit insight across the possibility space of crystal structures of a candidate molecule, beyond simply the observed structure(s). In this work, we demonstrate the reliability and scalability of CSP methods for small, rigid organic molecules by performing in-depth CSP investigations for over 1000 such compounds, the largest survey of its kind to-date. We show that this highly-efficient force-field-based CSP approach is superbly predictive, locating 99.

View Article and Find Full Text PDF

In 1971, Schill recognized that a prochiral macrocycle encircling an oriented axle led to geometric isomerism in rotaxanes. More recently, we identified an overlooked chiral stereogenic unit in rotaxanes that arises when a prochiral macrocycle encircles a prochiral axle. Here, we show that both stereogenic units can be accessed using equivalent strategies, with a single weak stereodifferentiating interaction sufficient for moderate to excellent stereoselectivity.

View Article and Find Full Text PDF
Article Synopsis
  • Energy Ranking Challenge
  • : A major issue in predicting organic molecular crystal structures is accurately ranking various energy levels of potential structures, as higher-level DFT methods, although reliable, are computationally expensive. -
  • Combining Approaches
  • : To handle the computational cost, researchers often use less accurate empirical force fields initially, sometimes paired with machine-learned interatomic potentials (MLIPs) that mimic high-level methods but are cheaper to compute. -
  • Enhanced Efficiency
  • : By utilizing active learning techniques to train MLIPs on CSP data, the researchers created an automated process that allows for efficient reranking of crystal structures to near-DFT accuracy, improving reliability and expanding the modeling capabilities of the structures.
View Article and Find Full Text PDF

Crystal structure prediction is becoming an increasingly valuable tool for assessing polymorphism of crystalline molecular compounds, yet invariably, it overpredicts the number of polymorphs. One of the causes for this overprediction is in neglecting the coalescence of potential energy minima, separated by relatively small energy barriers, into a single basin at finite temperature. Considering this, we demonstrate a method underpinned by the threshold algorithm for clustering potential energy minima into basins, thereby identifying kinetically stable polymorphs and reducing overprediction.

View Article and Find Full Text PDF

Herein, the synthesis of metal-organic tetrahedral cages featuring flexible thio- and selenophosphate-based ligands is described. The cages were prepared by sub-component self-assembly of A[double bond, length as m-dash]P(OC6H4NH2-4)3 (A = S, Se) or S[double bond, length as m-dash]P(SC6H4NH2-4)3, 2-pyridinecarboxaldehyde, and either Fe[BF4]2 or Co[BF4]2. Preliminary host-guest studies into the ability of the pendant P[double bond, length as m-dash]S and P[double bond, length as m-dash]Se groups to interact with suitable substrates will be discussed.

View Article and Find Full Text PDF

A PHP Error was encountered

Severity: Notice

Message: fwrite(): Write of 34 bytes failed with errno=28 No space left on device

Filename: drivers/Session_files_driver.php

Line Number: 272

Backtrace:

A PHP Error was encountered

Severity: Warning

Message: session_write_close(): Failed to write session data using user defined save handler. (session.save_path: /var/lib/php/sessions)

Filename: Unknown

Line Number: 0

Backtrace: