XACS

Xiamen Atomistic Computing Suite (XACS) is a platform with efficient, friendly, and unique atomistic computing software packages.

[XACS @XACSprogram]

New in JCTC: “Toward Robust Three-State Diabatization” — Zhang’s team systematically evaluates O(3) transformation parameterizations within VBADA, providing guidance for three-state ATD diabaticization.
DOI: 10.1021/acs.jctc.6c00257
#JCTC #ValenceBond #ComputationalChemistry

[XACS @XACSprogram]

🚀 XMVB Cloud Platform now supports:
• Browser-based molecular structure drawing
• Interactive 3D molecular visualization
• Molecular & valence bond orbital visualization
• Custom orbital colors & display effects

[XACS @XACSprogram]

We propose PyMEDA, an open-source, modular Python framework to standardize multiscale embedded EDA workflows for large systems. It has been published in Chin. J. Chem. Phys. 39 (2), 171-181.
#XEDA #CompChem #QuantumComputing

[XACS @XACSprogram]

We propose BTD, an efficient, low-scaling algorithm for electron integrals by combining Hilbert space-filling curves with pivoted Cholesky decomposition. It has been published in J. Chem. Phys. 163, 174109 (2025).
#XEDA #CompChem #QuantumComputing
DOI: 10.1063/5.0289370

[XACS @XACSprogram]

Recently, we developed BTD-GW, a breakthrough algorithm achieving formal O(N3) scaling that enables high-precision GW calculations for large molecular systems. It has been published in J. Chem. Phys. 164, 144106 (2026). #XEDA #CompChem #QuantumComputing
DOI: 10.1063/5.0319147

[XACS @XACSprogram]

🚀 XMVB 4.1 released!

Experience the new generation valence bond computing with a host of new features, available via cloud platform or local installation.

Discover new features: https://t.co/10Q6Co9U9V

XMVB manual:
https://t.co/MafYJfZoGy

#ComputationalChemistry #XMVB

[XACS @XACSprogram]

We developed DLVB, the first deep-learning-based framework for VB theory. It predicts VB structure weights without ab initio calculations and provides efficient selected-Cl scheme for compact VB wavefunctions. Published in JCTC. #XMVB #Deeplearning
https://t.co/M9dG4L4zFK

[XACS @XACSprogram]

We developed a Block Tensor Decomposition (BTD) algorithm with a formal O(N³) scaling for SOS-MP2 calculations (J. Chem. Phys. 163, 174109, 2025).
#TensorDecomposition #QuantumChemistry #XEDA #CompChem
DOI:10.1063/5.0289370

[XACS @XACSprogram]

A new study by CanZhong Lu and co-workers uncovers the hidden amide–π stacking that drives the surprising miscibility between polar DMF and nonpolar benzene—bridging electrostatic and dispersion forces and redefining the “like dissolves like” rule.
https://t.co/IFDNboOQ0Z

[XACS @XACSprogram]

Online course "Introduction to Valence Bond Theory" is now available. Go to https://t.co/fuC5bp1370 for the course in Chinese and https://t.co/ipJmvxSfto in English.

[XACS @XACSprogram]

Recently, we developed a DFT-in-xTB embedded energy decomposition analysis method for analyzing intermole-cular interactions in large systems. It has been published in J. Chem. Phys. 162, 124103 (2025).#XEDA #CompChem #QuantumComputing
DOI:10.1063/5.0258177

[XACS @XACSprogram]

Recently, we developed an efficient algorithm for VBSCF energy gradients. By combining XMVB with SHARC, we successfully performed the first ab initio classical VB-based molecular dynamics simulations! #XMVB #Molecular_dynamics #CompChem
DOI: 10.1021/acs.jpca.4c08431

[XACS @XACSprogram]

Recently, we published a paper in JCTC. New VB methods (VBSCF(RI), VBSCF(COSX), BOVB(RI)) built on low-rank algorithms achieve 30× speedup, scaling VB to hundreds of atoms. Now implemented in XMVB 4.0.
#XMVB #CompChem #QuantumComputing
DOI: 10.1021/acs.jctc.4c01787

[XACS @XACSprogram]

XMVB 4.0 is released! Reveal the exciting features at https://t.co/n6KNiMUmc5

[XACS @XACSprogram]

MLatom now offers an easy way to do so: you can leverage the power of the ANI potentials pre-trained on big #data. Check out the video.👇#compchem #machinelearning
https://t.co/5SabxRzJ53

[XACS @XACSprogram]

Online tutorial: https://t.co/EVFQkdPtWY

[XACS @XACSprogram]

In our latest tutorial we show how MLatom can be used to simulate UV/vis spectra via single-point convolution and nuclear-ensemble approach (NEA). ML can also be used to increase precision of the NEA spectra at reduced cost. #machine_learning #Simulation
https://t.co/Ih4uaj1azZ

[XACS @XACSprogram]

We published a #review to explore the current landscape of #molecular quantum chemical #data sets and #databases. It covers key information on more than 40 datasets including the level of theory, size and diversity, methodologies, and availability.
https://t.co/f895utCXiH

[XACS @XACSprogram]

You can easily do such calculations yourself using MLatom, which comes with tutorials and example scripts.
👉https://t.co/QFfCjycSjB

[XACS @XACSprogram]

We introduce a new approach based on the universal #MachineLearning models of AIQM series targeting the gold-standard coupled-cluster level, going beyond the typical DFT accuracy. Check out the video👇#compchem #dft #IR #Simulation
https://t.co/jgVSvTIkk1