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                    <h2>Research</h2>
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                        <h4><strong>Advancing Non-adiabatic Quantum Dynamics</strong></h4>
                        <p class="lead text-justify text-muted card-text">
                            The study explores quantum-classical dynamics methodologies, focusing on the fewest-switches surface
                            hopping (FSSH) as a revolutionary approach for efficiently studying charge transfer (CT) reactions.
                            Despite the limitations of common trajectory-based methods like FSSH in incorporating nuclear quantum
                            effects (NQEs), the project introduces the SHARP Pack (short for Surface Hopping And Ring Polymer package)
                            software package incorporating ring polymer surface hopping (RPSH) method, combining FSSH and ring polymer
                            molecular dynamics (RPMD) strengths. The developed modular software for RPSH aims to establish it as a
                            mainstream methodology for nonadiabatic molecular dynamics simulations with a focus on NQEs.
                            A comprehensive analysis evaluates RPSH's accuracy and limitations across various model systems a
                            nd reaction regimes, highlighting its significant advancement in incorporating NQEs in nonadiabatic
                            molecular dynamics. The exploration of velocity rescaling schemes and remedies for frustrated hops
                            enhances RPSH's applicability and robustness in nonadiabatic simulations.
                        </p>
                        <ul>
                            <li>Limbu, Shakib, <em>J. Phys. Chem. Lett.</em>, <strong>14</strong>, 8658-8666 (2023)</li>
                            <li>Limbu, Shakib, <em>Software Impacts</em>, <strong>19</strong>, 100604 (2024)</li>
                        </ul>
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                        <h4><strong>Disorder by Design: Application to Amorphous Semiconductors</strong></h4>
                        <p class="lead text-justify text-muted card-text">
                            While conventional approaches to materials modeling made significant contributions and
                            advanced our understanding of materials properties in the past decades, these approaches
                            often cannot be applied to disordered materials for which accurate total-energy functionals
                            or forces are either not available or it is simply infeasible to employ due to computational complexities associated with modeling disordered solids in the absence of translational
                            symmetry. Here, we adopted an information-driven probabilistic viewpoint and addressed
                            materials design as an optimization program, jointly supported by experimental data and
                            information, by solving a long-standing difficult problem involving a structural determination
                            of amorphous silicon via inversion of diffraction data. Even this approach can produce
                            microstructural properties of realistic samples of a-Si from experiments, such as voids and
                            vacancy-type defects, and demonstrates that data-driven approaches can enhance existing
                            methodologies for modeling disordered materials based on an information paradigm. This
                            brings a directional step-change in materials modeling computation.
                        </p>
                        <ul>
                            <li>Limbu, Elliott, Atta-Fynn, Biswas*, <em>Scientific Reports</em>, <strong>10</strong>, 7742 (2020)</li>
                        </ul>
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                        <h4><strong></strong>Information-Driven Inverse Approach for Amorphous Silicon</h4>
                        <p class="lead text-justify text-muted card-text">
                            A very different approach to the materials-structure determination problem for amorphous
                            solids is to address the problem from a hybrid point of view. Based on a hybrid scheme and
                            incorporating experimental diffraction data, a few structural constraints, and a total-energy
                            functional, we presented an accurate structural solution of the inverse problem by developing
                            a new information-driven inverse approach. By introducing a subspace optimization
                            technique, the difficulty associated with the optimization of the augmented objective function
                            can be reduced considerably to determine optimal structural solutions, satisfying
                            experiments, and a total-energy functional simultaneously. This method can produce nearly
                            defect-free models of amorphous silicon which have structural, electronic, and vibrational
                            properties fully consistent with experimental data. The realistic atomistic models of a-Si
                            exhibit a clean gap around the Fermi level in the electronic spectrum.
                        </p>
                        <ul>
                            <li>Limbu, Atta-Fynn, Drabold, Elliott, Biswas*, <em>Phys. Rev. Materials</em>, <strong>2</strong>, 115602 (2018)</li>
                            <li>Limbu*, Atta-Fynn, Biswas, <em>MRS Adv.</em>, <strong>4</strong>, 87-93 (2019)</li>
                        </ul>
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                        <h4><strong></strong>Force-biased Monte Carlo (FMC) and ab initio modeling of transition metal clusters</h4>
                        <p class="lead text-justify text-muted card-text">
                            A force-biased Monte Carlo (FMC) method, based on the Finnis-Sinclair and the Sutton-Chen
                            potentials, was used to model the putative ground-state structure of the transition-metal
                            clusters (TMC) of Fe, Ni, and Cu with sizes of 1-60 atoms. Specifically, the total energy of the
                            clusters was minimized using the local gradient of the potentials in Monte Carlo simulations.
                            The atomic structure of the FMC clusters was analyzed and compared with their counterparts
                            from the Cambridge Cluster Database (CCD) upon relaxation of the clusters with the planewave module in density-functional-theory code NWCHEM. An atom-by-atom comparison of
                            the FMC and CCD clusters was conducted by superposing one set of clusters onto another, and
                            the electronic properties of the clusters were addressed by computing the density of
                            electronic states by constructing DFT Hamiltonians.
                        </p>
                        <ul>
                            <li>Limbu, Biswas*, <em>J. Phys.: Conf. Series</em>, <strong>921</strong>, 012010 (2017) </li>
                            <li>Limbu, Atta-Fynn, Drabold, Elliot, Biswas*, <em>Phys. Rev. B</em>, <strong>96</strong>,
                                174208 (2017)</li>
                            <li>Limbu, Madueke, Atta-Fynn, Drabold, Biswas*, <em>J. Phys.: Conf. Series</em>, <strong>1252</strong>, 012009 (2019)</li>
                        </ul>
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