Yonatan Dubi

The chirality-induced spin selectivity (CISS) effect has been invoked to explain recent reports of differences in the time-resolved EPR signals between chiral and achiral molecules. However, the microscopic origin of these differences and their connection to CISS remain contested, particularly since these systems lack a metal interface. Here, we introduce an intramolecular spinterface-like mechanism that naturally arises within donor–chiral bridge–acceptor (D−χB–A) complexes and quantitatively reproduces experimentally reported observed spin polarization in time-resolved EPR studies. In our two-electron Lindblad model, the photoexcited charge-transfer electron traversing the chiral bridge exchanges with the residual donor electron, which acts as a localized magnetic moment analogous to an induced magnetic moment on an electrode surface. The resulting through-bridge charge current produces an effective solenoidal field at the donor–bridge interface, breaking spin degeneracy and directional symmetry, thus enabling spin-selective transport without invoking intrinsic spin–orbit coupling on the bridge. We show that the interplay among this current-induced field, donor thermalization (which breaks time-reversal symmetry), and bridge spin mixing yields tens-of-percent polarization over realistic experimental conditions and charge-transfer time scales, matching reported CISS signatures in triads and DNA hairpins. By explicitly resolving the dependence on solenoidal coupling strength, temperature, and spin-mixing rates, the model identifies the regime in which internal spinterfaces can generate robust CISS-like spin filtering. These findings demonstrate that CISS-like signals in isolated D−χB–A complexes are fully compatible with a spinterface mechanism, providing a unified conceptual framework for interpreting both device-based and molecule-internal CISS platforms.

We introduce Qlustering, a quantum-inspired algorithm for unsupervised learning that leverages network-based quantum transport to perform data clustering. In contrast to traditional distance-based methods, Qlustering treats the steady-state dynamics of quantum particles propagating through a network as a computational resource. Data are encoded as input states in a tight-binding Hamiltonian framework governed by the Lindblad master equation, and cluster assignments emerge from steady-state output currents at terminal nodes. The algorithm iteratively optimizes the network's Hamiltonian to minimize a physically motivated cost function, achieving convergence through stochastic updates. We benchmark Qlustering on synthetic datasets, a localization problem, and real-world chemical and biological data, namely subsets of the QM9 molecular database and the Iris dataset. Across these diverse tasks, Qlustering demonstrates competitive or superior performance compared with classical methods such as k-means, particularly for non-convex or high-dimensional data. Its intrinsic robustness, low computational complexity, and compatibility with photonic implementations suggest a promising route toward physically realizable, quantum-native clustering architectures.

The chiral-induced spin selectivity (CISS) effect, whereby chiral molecules preferentially transmit electrons of one spin orientation, remains one of the most intriguing and debated phenomena at the interface of spintronics, molecular electronics, and quantum materials. Despite extensive experimental observations across diverse platforms - including transport junctions, photoemission, and enantioselective chemistry - a comprehensive theoretical framework is still lacking. In this perspective, we critically examine the spinterface mechanism as a unifying explanation for the CISS effect. The spinterface model, which hypothesizes a feedback interaction between electron motion in chiral molecules and fluctuating surface magnetic moments, is shown to quantitatively reproduce experimental data across various systems and conditions. We contrast it with some existing theoretical models, highlighting key experimental features. Importantly, we also address open questions and criticisms of this model, including the nature of surface magnetism, the role of dissipation, and the applicability of the mechanism to non-helical or electrode-free systems. By offering falsifiable predictions and reconciling theory with experimental raw data, this work aims to sharpen the dialogue surrounding the microscopic origin of CISS and stimulate further experimental and theoretical progress.

The chirality-induced spin selectivity (CISS) effect, whereby chiral molecules preferentially transmit electrons of one spin orientation, remains one of the most intriguing and debated phenomena at the interface of spintronics, molecular electronics, and quantum materials. Despite extensive experimental observations across diverse platforms─including transport junctions, photoemission, and enantioselective chemistry─a comprehensive theoretical framework is still lacking. In this perspective, we critically examine the spinterface mechanism as a unifying explanation for the CISS effect. The spinterface model, which hypothesizes a feedback interaction between electron motion in chiral molecules and fluctuating surface magnetic moments, is shown to quantitatively reproduce experimental data across various systems and conditions. We contrast it with some existing theoretical models, highlighting key experimental features. Importantly, we also address open questions and criticisms of this model, including the nature of surface magnetism, the role of dissipation, and the applicability of the mechanism to nonhelical or electrode-free systems. By offering falsifiable predictions and reconciling theory with experimental raw data, this work aims to sharpen the dialogue surrounding the microscopic origin of CISS and stimulate further experimental and theoretical progress.

Understanding the crystallization of molecules, and specifically the appearance of polymorphs, is a great challenge to modern chemistry, with both fundamental and practical aspects. Here, motivated by the established ability of Machine Learning (ML) algorithms to perform classification tasks, we harness ML-based tools and existing chemical datasets to ask whether the existence of polymorphs of a molecular crystal can be predicted based solely on properties of the corresponding single molecules. We implemented an algorithm that can predict the existence of polymorphism with an average accuracy of 65\%. Although this is not enough to generate a reliable “polymorph predicting” engine, our results reveal intriguing trends. We suggest that the limited performance of the model reflects the inherent bias of crystallographic data towards monomorphs. Namely, the fact that only one crystal form of a certain compound has been observed in experiments to date does not rule out the possibility that additional stable crystal structures could exist. Our results provide statistical support for a broadly held claim in the crystal engineering community that the proportion of possible polymorphs is, in fact, much larger than represented in the data.

We study the nonequilibrium steady state thermodynamics of a photodevice which can operate as a solar cell or a photoconductor, depending on the degree of asymmetry of the junction. The thermodynamic efficiency is captured by a single coefficient of performance. Using a minimal model based on a two-level system, we show that when the Coulomb interaction energy matches the transport gap of the junction, the photoconductor displays maximal response, performance, and signal-to-noise ratio, while the same regime is always detrimental for the solar cell. Nevertheless, we find that the Coulomb interaction is beneficial for the solar cell performance if it lies below the transport gap. Our work sheds important light on design principles for thermodynamically efficient photodevices in the presence of Coulomb interactions.

The spinterface mechanism was suggested as a possible origin for the chirality-induced spin-selectivity (CISS) effect and was used to explain and reproduce, with remarkable accuracy, experimental data from transport experiments showing the CISS effect. Here, we apply the spinterface mechanism to explain the appearance of magnetization at the interface between nonmagnetic metals and chiral molecules, through the stabilization of otherwise fluctuating magnetic moments. We show that the stabilization of surface magnetic moments occurs for a wide range of realistic parameters and is robust against dephasing. Importantly, we show that the direction of the surface magnetic moments is determined by the chiral axis of the chiral molecules. Armed with the concept of stable surface magnetic moments, we then formulated a theory for the photoemission CISS effect. The theory, based on spin-dependent scattering, leads to direct predictions regarding the relation between the photoemission CISS effect, the chiral axis direction, the spinterface "size", and the tilt angle of the detector with respect to the surface. These predictions are within reach of current experimental capabilities and may shed new light on the origin of the CISS effect.