This paper was converted on www.awesomepapers.org from LaTeX by an anonymous user.
Want to know more? Visit the Converter page.

thanks: These authors contributed equally.thanks: These authors contributed equally.

Deterministic and Efficient Switching of Sliding Ferroelectrics

Shihan Deng Key Laboratory of Computational Physical Sciences (Ministry of Education), Institute of Computational Physical Sciences, State Key Laboratory of Surface Physics, and Department of Physics, Fudan University, Shanghai 200433, China Shanghai Qi Zhi Institute, Shanghai 200030, China    Hongyu Yu Key Laboratory of Computational Physical Sciences (Ministry of Education), Institute of Computational Physical Sciences, State Key Laboratory of Surface Physics, and Department of Physics, Fudan University, Shanghai 200433, China Shanghai Qi Zhi Institute, Shanghai 200030, China    Junyi Ji Key Laboratory of Computational Physical Sciences (Ministry of Education), Institute of Computational Physical Sciences, State Key Laboratory of Surface Physics, and Department of Physics, Fudan University, Shanghai 200433, China Shanghai Qi Zhi Institute, Shanghai 200030, China    Changsong Xu [email protected] Key Laboratory of Computational Physical Sciences (Ministry of Education), Institute of Computational Physical Sciences, State Key Laboratory of Surface Physics, and Department of Physics, Fudan University, Shanghai 200433, China Shanghai Qi Zhi Institute, Shanghai 200030, China    Hongjun Xiang [email protected] Key Laboratory of Computational Physical Sciences (Ministry of Education), Institute of Computational Physical Sciences, State Key Laboratory of Surface Physics, and Department of Physics, Fudan University, Shanghai 200433, China Shanghai Qi Zhi Institute, Shanghai 200030, China
Abstract

Recent studies highlight the scientific importance and broad application prospects of two-dimensional (2D) sliding ferroelectrics, which prevalently exhibit vertical polarization with suitable stackings. It is crucial to understand the mechanisms of sliding ferroelectricity and to deterministically and efficiently switch the polarization with optimized electric fields. Here, applying our newly developed DREAM-Allegro multi-task equivariant neural network, which simultaneously predicts interatomic potentials and Born effective charges, we construct a comprehensive potential for boron nitride (BN\mathrm{BN}) bilayer. The molecular dynamics simulations reveal a remarkably high Curie temperature of up to 1500K, facilitated by robust intralayer chemical bonds and delicate interlayer van der Waals(vdW) interactions. More importantly, it is found that, compared to the out-of-plane electric field, the inclined field not only leads to deterministic switching of electric polarization, but also largely lower the critical strength of field, due to the presence of the in-plane polarization in the transition state. This strategy of an inclined field is demonstrated to be universal for other sliding ferroelectric systems with monolayer structures belonging to the symmetry group p6¯m2p\bar{6}m2, such as transition metal dichalcogenides (TMDs).

Achieving ferroelectric devices with small thickness and perpendicular polarization is a critical step toward realizing low-energy, nonvolatile, and high-density ferroelectric memory [1]. However, it is well-known that the depolarization field becomes significant in thin film ferroelectrics. Additionally, “dead layers” inevitably form due to factors such as interface effects, defects, and impurities, all of which lead to performance degradation in the application of ultrathin films [2, 3, 4, 5].

The recently proposed concept of sliding ferroelectricity in 2D vdW materials naturally overcomes these obstacles [6]. The prototype of sliding ferroelectrics is BN\mathrm{BN} bilayers [see Fig. 1(a)], which display energy ground state as the AB (BA) configuration [7, 2, 1, 8, 9, 10] with C3vC_{3v} symmetry. Within the AB configuration, the top B\mathrm{B} atom aligns with the bottom N\mathrm{N} atom, and the top N\mathrm{N} atom and the bottom B\mathrm{B} atom sit at the hollow sites of the honeycomb lattice. The AB(BA) stacking mode disrupts mirror symmetry and leads to an out-of-plane polarization of 2 pC/m in the z-z(zz) direction [6, 11]. This vertical polarization arises from charge redistribution driven by interlayer coupling [2, 12, 4, 13]. The BA state can transition to the AB state via relative sliding between the two layers by a B\mathrm{B}-N\mathrm{N} bond length in any of the three rotationally symmetric directions [11, 13, 14]. Conversely, sliding in the opposite direction by one bond length leads to the mirror-symmetric (D3hD_{3h}) AA state, representing the highest energy state. Sliding ferroelectrics, especially the proposal of bilayer stacking ferroelectricity (BSF) theory [15], broaden the spectrum of candidate materials for 2D ferroelectrics, as bilayers made of nonpolar monolayers can exhibit ferroelectricity through specific stackings. Beyond BN\mathrm{BN} bilayer, sliding ferroelectrics has been experimentally confirmed in various vdW systems, including semimetals [16, 17, 18, 19, 20], insulators [21], semiconductors [22, 23, 24, 25, 26], and organic crystals [27], all of which are robust at room temperature. Notably, recent experiments highlighting high endurance and fatigue resistance in sliding ferroelectrics underscore the significant potential of these materials for practical applications [28, 29].

The study of sliding ferroelectricity is rapidly developing, with both fundamental and practical challenges yet to be addressed. Although the switching energy barriers are typically very low (\simmeV per unit cell [6, 30, 31]), sliding ferroelectrics exhibit high Curie temperatures (TCT_{C}), as most of them are operated at room-temperature. Thermodynamic modeling using a mean-field approximation suggests TC=1.58×104T_{C}=1.58\times 10^{4} K for BN\mathrm{BN} bilayer [14]. Such prediction reflects the good stability of BN\mathrm{BN} bilayers. Moreover, the polarization of sliding ferroelectrics is typically small, leading to a large coercive field for polarization switching, which indicates that a wiser and more efficient switching strategy is highly desired. Symmetry changes during slidings indicating that the Born effective charges (BECs) can change dramatically [32], the treatment of fixed BEC may be insufficient [33] [see Fig.S1 in the supplemental material (SM) [34] for further discussion]. Ab initio molecular dynamics (AIMD) can be used to study sliding ferroelectricity, but it cannot handle large systems and is computationally consuming [51]. Hence, an accurate and efficient description of both intralayer and interlayer couplings is required.

Refer to caption
Figure 1: (a) Schemes of the AA, BA, AB, and SP stackings of BN\mathrm{BN} bilayers. Blue arrows define the lattice vectors 𝒂\bm{a}, 𝒃\bm{b} and 𝒄\bm{c} of unit cell. Purple arrows indicate the sliding vector, 𝒕\bm{t}, which is defined as the fractional displacement of the top layers with respect to bottom layer in the AA stacking. Energy ε0\varepsilon_{0} (b) and polarization PP (c) along the designed sliding pathway, as calculated by the DFT and Berry phase approach [52, 53].

In this Letter, applying our newly developed DREAM method (i.e., a generalized dielectric response equivariant atomistic multi-task framework based on Allegro [45]), we construct a neural network model for BN\mathrm{BN} bilayer. Such model is capable of predicting both the interatomic potential and the BEC tensors, which enable prediction of a reasonable TCT_{C} and accurate responses to applied electric fields. Moreover, it is found that an inclined electric field, which breaks the three-fold rotational symmetry of BN\mathrm{BN} bilayer, can not only deterministically control directions of slidings, but also substantially reduce the total coercive field. These findings are general and can be applied to other similar sliding ferroelectrics.

\textcolor

blueFerroelectric transition of BN bilayer. Firstly, the basic properties of BN\mathrm{BN} bilayers are examined by density functional theory (DFT) calculations. As illustrated in Fig. 1(b)(c), the out-of-plane polarization (PP_{\perp}) of the AB (BA) state yields \mp2.078 pC/m, and the energy barrier for polarization switching is determined to be 7.44 meV per unit cell. Such results are well consistent with those of previous studies [6, 11]. Notably, the transition state or intermediate saddle-point (SP) state with C2vC_{2v} symmetry exhibits a strictly in-plane polarization (PP_{\parallel}) of 2.091 pC/m.

To train the potential with the original Allegro method [45], we run on-the-fly machine learning force fields(MLFFs) [40, 41, 42] and generate 1659 structures with 5×5×15\times 5\times 1 supercell, across a wide temperature range below 3000 K. The structure, energy, force, and stress tensor are included in training. The obtained model can accurately predict the energy difference among structural configurations, with a small mean absolute errors (MAEs) of 0.053 meV/atom [see SM [34] for details].

Refer to caption
Figure 2: The change of Im(ψ(𝒕))\mathrm{Im}(\psi(\bm{t})) as a function of temperature. Red dots and blue triangles represent the heating and cooling processes, respectively, which are marked by red and blue arrows. Green arrows denote the reciprocal lattice vectors 𝒂\bm{a}^{*} and 𝒃\bm{b}^{*}, and the black arrow indicates that 𝑮=𝒂𝒃\bm{G}=\bm{a}^{*}-\bm{b}^{*} is selected. Purple arrows visualize the sliding vector 𝒕\bm{t} of the BA and AB state, which are 𝒕BA=1/3(𝒃𝒂)\bm{t}_{\mathrm{BA}}=1/3(\bm{b}-\bm{a}) and 𝒕AB=2/3(𝒃𝒂)\bm{t}_{\mathrm{AB}}=2/3(\bm{b}-\bm{a}) respectively. The dashed gray line signifies the critical temperature.

In the case of sliding ferroelectricity, TCT_{C} can be characterized by the sliding vector 𝒕\bm{t} [14]:

limTTC𝒕T,\lim\limits_{T\to T_{C}^{-}}\frac{\partial\langle\bm{t}\rangle}{\partial T}\to\infty, (1)

where \langle~{}\rangle signifies the ensemble average at a certain temperature. Vector 𝒕\bm{t} is the averaged displacements of the top layer with respect to the bottom layer in the AA stacking [see Fig. 1(a)]. To avoid the impact of in-plane periodic boundary conditions, we use the reciprocal lattice vector (𝑮\bm{G}) to define a new order parameter (ψ\psi), which reads

ψ(𝒕)=ei𝑮𝒕.\psi(\bm{t})=e^{i\bm{G}\cdot\bm{t}}. (2)

where ψ\psi ranges between [1,1][-1,1] and remains unchanged under the substitution 𝒕𝒕+𝑹\bm{t}\to\bm{t}+\bm{R}, where 𝑹\bm{R} represents the in-plane lattice vector.

We now focus on the ferroelectric-paraelectric transition of BN\mathrm{BN} bilayer. The MD simulations are performed using our potential model, where 900 atoms is incrementally heated and cooled between 1 K and 2000 K, with an interval of 50 K. At each temperature, the quantity of ψ\psi is computed for the equilibrium states over 50 ps. The changes in the imaginary part of ψ\psi as a function of temperature are presented in Fig. 2 for 𝑮=𝒂𝒃\bm{G}=\bm{a}^{*}-\bm{b}^{*}. Starting in the BA state [Im(ψBA)=3/2\mathrm{Im}(\psi_{\mathrm{BA}})=\sqrt{3}/2], an increase in temperature progressively triggers system sliding. Conversely, during the cooling process, system sliding gradually ceases and eventually randomly stabilizes in the AB state [Im(ψAB)=3/2\mathrm{Im}(\psi_{\mathrm{AB}})=-\sqrt{3}/2]. Accoriding to Fig. 2, the critical temperature is approximated as 1500 K. Intriguingly, even for temperatures over TCT_{C}, the system conducts only few complete slides within 50 ps, oscillating around the BA or AB state most of the time. This phenomenon causes ψ\psi to oscillate above and below zero, contrasting with traditional order parameters that promptly vanish above TCT_{C}. The presently predicted TC=1500T_{C}=1500 K is much more reasonable than the 1.58×1041.58\times 10^{4} K from mean-field approximation [14].

\textcolor

blueSwitching of sliding ferroelectric BN\mathrm{BN} bilayer. To simulate the BN\mathrm{BN} bilayer under an external electric field, we integrate Allegro within the new DREAM framework [46, 34]. This integration enables the network to learn both scalars and tensors by leveraging geometric tensors [54, 55]. Consequently, the network is capable of simultaneously predicting interatomic potentials and BECs. The MAEs of the final model, which incorporates BEC information of 3484 structures at temperatures below 500K, yields 0.030 meV/atom in energy and 0.008 ||e|| in BEC, demonstrating good accuracy of the model.

Refer to caption
Figure 3: (a) Energy ε0\varepsilon_{0} and polarization PP distribution calculated by the DFT and Berry phase approach. Positions within the hexagon correspond to different sliding vectors, with the center representing the BA state. The shades of grey in the background indicate energy levels. The direction of colored arrows shows in-plane polarizations PP_{\parallel}, while their colors represent out-of-plane polarization PP_{\perp}. The sliding directions θ\theta are indicated by large hollow arrows. (b) The energy surface with only EE_{\perp} along z-z (the top panel) and with both EE_{\perp} along z-z and EE_{\parallel} at 6060^{\circ} (the bottom panel), calculated according to Eq. 3 with EE_{\perp} and EE_{\parallel} equal to 1V/Å. White arrows denote the sliding pathways with the lowest barrier. (c) Energy along the sliding pathway under varying EE_{\parallel} and EE_{\perp}, also calculated using Eq. 3. The EE_{\parallel} increases from left to right panels, while EE_{\perp} are gradually enhanced from top to bottom panels.

We now examine the responses of the BN\mathrm{BN} bilayer to perpendicular field EE_{\perp}. We start with the ferroelectric BA state and incrementally increase EE_{\perp} along the z-z direction over time at a rate of 0.02 V/(Å\cdotps), at temperatures ranging from 100 K to 500 K. The sliding process occurs rapidly, typically within a few picoseconds, and thermal vibrations add complexity to identifying the exact onset of sliding. Therefore, we define the coercive field (E,cE_{\perp,c}) as the field at which sliding reaches the SP state. Our results indicate that E,cE_{\perp,c} decreases with increasing temperature, starting at approximately 1.99 V/Å at 100 K and saturating at around 1.39 V/Å for over 200 K. Moreover, since EE_{\perp} does not break the three-fold rotational symmetry of the BN\mathrm{BN} bilayer, sliding occurs randomly along the three rotationally symmetric directions in each simulation [see the top panel of Fig. 3(b)].

Given that some sliding states of BN\mathrm{BN} bilayer exhibit PP_{\parallel}, we investigate the effect of in-plane electric field (EE_{\parallel}) on ferroelectric switching. As revealed by Fig. 3(a), the direction of PP_{\parallel} is the same as the corresponding sliding direction. These directions can be characterized by the angle θ\theta, which is measured through a counterclockwise rotation from the yy-axis. This finding implies that EE_{\parallel} oriented along one of these three directions can break the three-fold rotational symmetry and induce deterministic switching. For instance, EE_{\parallel} oriented at 6060^{\circ} will lead to sliding being only along 6060^{\circ} [see the lower panel of Fig. 3(b)]. Actually, applying EE_{\parallel} within the range of (0,120)(0^{\circ},120^{\circ}) can all leads to sliding along 6060^{\circ} [refer to Fig.S4]. In addition, Fig. 3(a) shows significant PP_{\parallel} at the bridging SP state, which indicates that suitable EE_{\parallel} can substantially reduces the energy barrier. Such conjecture can be verified by energy distribution shown in the first two columns of Fig. 3(c)], where the energy barrier for sliding from BA to AB state is obviously reduced in the presence of EE_{\parallel}.

Refer to caption
Figure 4: (a) E,cE_{\perp,c} as a function of temperature. The orange and purple lines represent the scenarios with E=0E_{\parallel}=0 and E=0.2E_{\parallel}=0.2V/Å, respectively, at θ=60\theta=60^{\circ}. The error bars indicate the range of results from parallel simulations. (b) The relationship between E,cE_{\perp,c} and EE_{\parallel}, as obtained by analytical calculations (purple line), numerical calculations (green line), and MD simulations at 0.1K (yellow line). The pentagram marks on the curves indicate the the minimum Et,cE_{t,c}. The insets depict the energy along the sliding pathway with the minimum Et,cE_{t,c} obtained by analytical (the top panel) and numerical (the bottom panel) calculations, respectively. (c) The magnitude (blue line) and dip angle (red line) of the minimum Et,cE_{t,c} across different temperatures. The dip angle is defined as the angle between Et,cE_{t,c} and the horizontal plane.

Moreover, the decreasing in the energy barriers also indicate that the presence of EE_{\parallel} may reduce E,cE_{\perp,c}. To examine such conjecture, we fit the energy ε0\varepsilon_{0}, in-plane dipole pp_{\parallel}, and out-of-plane dipole pp_{\perp} as a function of the amount of sliding tt with respect to the SP state, along the BA to AB sliding pathway. The fitted models yield ε0(t)=e4t42e4tBA2t2+e0\varepsilon_{0}(t)=e_{4}t^{4}-2e_{4}t_{\mathrm{BA}}^{2}t^{2}+e_{0}, p(t)=p4t4+p2t2p4tBA4p2tBA2p_{\parallel}(t)=p_{4}^{\parallel}t^{4}+p_{2}^{\parallel}t^{2}-p_{4}^{\parallel}t_{\mathrm{BA}}^{4}-p_{2}^{\parallel}t_{\mathrm{BA}}^{2}, and p(t)=p3t33p3tBA2tp_{\perp}(t)=p_{3}^{\perp}t^{3}-3p_{3}^{\perp}t_{\mathrm{BA}}^{2}t, where tBA=1/6|𝒃𝒂|=0.725t_{\mathrm{BA}}=-1/6|\bm{b}-\bm{a}|=-0.725 Å is a constant. The coefficients are determined to be e4=27.017e_{4}=27.017 meV/Å4, e0=7.41e_{0}=7.41 meV, p4=5.82×103p_{4}^{\parallel}=5.82\times 10^{-3} e/Å3, p2=1.66×102p_{2}^{\parallel}=-1.66\times 10^{-2} e/Å, and p3=9.13×103p_{3}^{\perp}=9.13\times 10^{-3} e/Å2 [refer to Fig.S3]. The total potential energy after applying EE_{\parallel} along the BA to AB sliding pathway and EE_{\perp} can then be expressed as

ε(t)=ε0(t)Ep(t)Ep(t).\varepsilon(t)=\varepsilon_{0}(t)-E_{\parallel}\cdot p_{\parallel}(t)-E_{\perp}\cdot p_{\perp}(t). (3)

If we define the critical field as the minimum field at which the local energy minimum of ε(t)\varepsilon(t) disappears [i.e., dε(t)/dt0\mathrm{d}\varepsilon(t)/\mathrm{d}t\leq 0, see the top inset of Fig. 4(b)] along the BA to SP sliding pathway. Then, E,cE_{\perp,c} along z-z can be obtained analytically for a given EE_{\parallel} by solving Eq. 3 [see the purple line in Fig. 4(b) and SM [34]]. When EE_{\parallel} is small, E,cE_{\perp,c} can be expressed in terms of E\sqrt{E}_{\parallel} as

E,c=\displaystyle E_{\perp,c}= 4e4tBA3p3(1p2+2p4tBA2e4tBA2E)\displaystyle-\frac{4e_{4}t_{\mathrm{BA}}}{3p_{3}^{\perp}}\left(1-\sqrt{-\frac{p_{2}^{\parallel}+2p_{4}^{\parallel}t_{\mathrm{BA}}^{2}}{e_{4}t_{\mathrm{BA}}^{2}}}\sqrt{E_{\parallel}}\right) (4)
=\displaystyle= E,c0(1βE),\displaystyle E^{0}_{\perp,c}(1-\beta\sqrt{E_{\parallel}}),

where β>0\beta>0. Clearly, Eq. 4 shows that the presence of EE_{\parallel} will reduce the required E,cE_{\perp,c}. In the absence of EE_{\parallel}, E,c0=4e4tBA/3p3=E^{0}_{\perp,c}=-4e_{4}t_{\mathrm{BA}}/3p_{3}^{\perp}= 2.86 V/Å is the vertical coercive field. More importantly, it is further found that the presence of EE_{\parallel} can lower the total coercive field Et,cE_{t,c}. When E0E_{\parallel}\to 0, Et,cE_{t,c} can be expressed as

Et,c\displaystyle E_{t,c} =(E,c)2+(E)2\displaystyle=\sqrt{(E_{\perp,c})^{2}+(E_{\parallel})^{2}} (5)
E,c0(1βE)<E,c0,\displaystyle\to E^{0}_{\perp,c}\left(1-\beta\sqrt{E_{\parallel}}\right)<E^{0}_{\perp,c},

which clearly demonstrates that Et,cE_{t,c} is smaller than E,c0E^{0}_{\perp,c} with finite EE_{\parallel}. Alternatively, if we define the critical field as the minimum field such that ε(t)\varepsilon(t) does not exceed that at BA [i.e., ε(t)ε(tBA)\varepsilon(t)\leq\varepsilon(t_{\mathrm{B}A}), see the bottom inset of Fig. 4(b)], E,cE_{\perp,c} can also be solved numerically for a given EE_{\parallel}, as shown by the green line in Fig. 4(b). In both analytical and numerical cases, the minimum Et,cE_{t,c} is reduced by more than 64% and 70%, respectively, comparing to the E,c0E^{0}_{\perp,c}.

Then, we conduct MD simulations to verify the prediction that finite EE_{\parallel} can lower E,cE_{\perp,c} and Et,cE_{t,c}. By applying a constant EE_{\parallel} of 0.2 V/Å along θ=60\theta=60^{\circ} direction, E,cE_{\perp,c} is found to significantly reduce, comparing to E=0E_{\parallel}=0 [see Fig. 4(a)]. As in the previous analysis, this adjustment ensured that sliding occurred exclusively at θ=60\theta=60^{\circ}. However, insufficient EE_{\parallel} magnitude may not adequately counteract random thermal fluctuations, potentially resulting in alternative sliding directions.

To determine the configurations of Et,cE_{t,c} necessary to initiate sliding, we apply an inclined electric field to the BN\mathrm{BN} bilayer at different temperatures. The field has varying in-plane and vertical components, adjusted in increments of 0.05 V/Å, to initiate sliding within 30 ps [refer to Fig.S5]. At 0.1 K, the configuration of Et,cE_{t,c} is shown by the yellow line in Fig. 4(b), exhibiting a trend consistent with previous theoretical analyses. As shown in Fig. 4(c), the minimum Et,cE_{t,c} decreases by over 70% as the temperature decreases, compared to the vertical Et,cE_{t,c}. It is noteworthy that experimentally measured coercive fields are often significantly lower than theoretically predicted values. This discrepancy, potentially related to the Landauer paradox [56, 57, 58], may be due to the presence of inhomogeneities in the experimental samples [59, 60]. On another aspect, dip angle of the minimum Et,cE_{t,c} at different temperatures almost keep constant of 2424^{\circ}. Such constant behavior will benefit to experimental setups and also to device design.

Discussion. The decrease in Et,cE_{t,c} with applying an inclined electric field relies on the presence of in-plane polarization along the sliding pathway. According to symmetry analysis [15], bilayers, which are made of monolayers with the same layer group of p6¯m2p\bar{6}m2 as BN\mathrm{BN}, all display the required in-plane polarization. Such discovery indicates that the strategy of inclined field can be generalized to different sliding systems, such as widely studied transition metal dichalcogenides (TMDs) WSe2\mathrm{WSe_{2}}, MoSe2\mathrm{MoSe_{2}}, WS2\mathrm{WS_{2}}, and MoS2\mathrm{MoS_{2}} [24, 25, 29], as well as InSe\mathrm{InSe} [22, 23]. To confirm this prediction, we verify the energy and polarization distribution of MoS2\mathrm{MoS_{2}} [refer to Fig.S6], which differs from BN\mathrm{BN} only in the opposite direction of in-plane polarization. Hence, the direction of EE_{\parallel} need to be reversed to achieve efficient switching.

In conclusion, our newly developed machine-learning-assisted DREAM-Allegro model effectively predicts the interatomic energy and BECs of parallel-stacked BN\mathrm{BN} bilayers. This enables accurate prediction on temperature and field effects by performing MD simulations. Applying both simulations and theoretical analysis, we find that in-plane field can lead to deterministic switching of polarization and an inclined field can largely reduce the critical field required for switching. Such strategy is further generated to widely studied sliding ferroelectrics and thus paves the way for applications.

Acknowledgements.
We acknowledge financial support from the National Key R&D Program of China (No. 2022YFA1402901), NSFC (No. 11825403, 11991061, 12188101, 12174060, and 12274082), the Guangdong Major Project of the Basic and Applied Basic Research (Future functional materials under extreme conditions—2021B0301030005), Shanghai Science and Technology Program (No. 23JC1400900), and Shanghai Pilot Program for Basic Research—FuDan University 21TQ1400100 (23TQ017). C.X. also acknowledges support from the Shanghai Science and Technology Committee (Grant No. 23ZR1406600) and the Xiaomi Young Talents Program.

References

SI. Born effective charges (BECs) of BN bilayer

The force acting on ion ii in the presence of a finite electric field EE can be determined using the formula 𝑭i=Zi(𝑹)𝑬\bm{F}_{i}=Z_{i}(\bm{R})\bm{E}, where Zi(𝑹)Z_{i}(\bm{R}) denotes the zero-field Born effective change (BEC) tensor of ion ii at the coordinates 𝑹\bm{R}. During polarization switching in sliding ferroelectrics, that the positional rearrangement among ions within the same layer remains negligible, with the primary change attributed to interlayer sliding. Consequently, we group two adjacent B\mathrm{B} and N\mathrm{N} ions within the same layer as a collective entity to examine the BECs distribution along the sliding pathway. Illustratively, as depicted in Fig. S1, ions experience forces of equal magnitude but opposite direction under the influence of an external field. Specifically, when EE_{\perp} is applied, the distribution of forces is symmetric with respect to the transition state SP [see Fig. S1(a)]. Conversely, with EparallelE_{parallel} applied in the sliding direction, the distribution becomes antisymmetric [see Fig. S1(b)]. In both situations, the BECs exhibit significant variations along the sliding path from BA to AB. Previous MD simulations that use fixed BEC values cannot precisely capture the behavior of the BN\mathrm{BN} bilayer under these electric field conditions. This limitation is particularly evident for EparallelE_{parallel}, where it cannot calculate the force by employing the average BEC value along the sliding pathway, which would be zero. Hence, our proposed model, capable of predicting BECs for varying coordinates 𝑹\bm{R}, proves to be indispensable.

SII. Computational details and model accuracy

We employ the Vienna ab initio Simulation Package (VASP) [35] to perform DFT calculations using the projector augmented wave (PAW) method [36] and the generalized gradient approximation (GGA) with the Perdew-Burke-Ernzerh (PBE) exchange-correlation functional [37]. The plane-wave cutoff energy is set to 520 eV. The cell constant along the cc-axis is fixed at 30 Å, ensuring a sufficient vacuum space. A 12×12×112\times 12\times 1 kk-point mesh and vdW corrections with the DFT-D2 method of Grimme [38] are applied for structure optimization. The optimized lattice constant of the AB-stacked BN\mathrm{BN} bilayer is a=b=2.511a=b=2.511 Å with an interlayer distance of 3.0743.074 Å, which is consistent with previous theoretical calculations [11]. For other parallel-stacked configurations corresponding to different sliding vectors, the lattice constant remains almost unchanged, and the interlayer distance increases slightly (not exceeding 0.35 Å). The primary cells are expanded to 5×5×15\times 5\times 1 supercells using Vaspkit [39], and MD calculations are performed using on-the-fly machine learning force fields (MLFF) [40, 41, 42] for more efficient sampling. We use a 3×3×13\times 3\times 1 kk-point mesh and the NVT ensemble with a Langevin thermostat [43]. The BECs of each atom in different configurations are further calculated using density functional perturbation theory (DFPT) [44].

In our training, the cutoff radius is set to Rc=7ÅR_{c}=7\text{\r{A}}, encompassing nearly 100 pairs of each atom formed within the 19th nearest neighbor. The learning rate is designed to decay exponentially from 5×1035\times 10^{-3} to 9.7×1069.7\times 10^{-6}. For the Allegro [45] model, trained on a dataset containing 1659 structures from MD sampling blow 3000K, we select a (64, 128, 256, 256) dimensional embedding network, a (256, 256, 256) dimensional fitting network, and a (128) dimensional per-edge final network. This configuration yields mean absolute errors (MAEs) of 0.053 meV/atom for energy, 5.311 meV/Å for forces and 0.063 meV/Å3 for stress. For our DREAM-Allegro [46] model (DA), trained on a dataset containing 3484 structures from MD sampling blow 500K, the loss weight coefficients for energy, forces, stress, and BEC0 (which measures the system’s electrical neutrality) are all set to 1, and the coefficient for BEC is increased to 10 due to the relatively small absolute values of BECs. The per-edge final network dimensions are adjusted to (128, 128, 64) dimensions, resulting in a model with MAEs of 0.030 meV/atom for energy, 3.851 meV/Å for forces, 0.076 meV/Å3 for stress and 0.008 ||e|| for BEC (after correcting with BEC0). This indicates that our models are highly accurate. Fig. S2 presents the parity plot of energy and BEC.

The MD simulations are performed using the LAMMPS software package [47] with a newly integrated atom type named “BEC”. Periodic boundary conditions are applied along the aa and bb axes, while a non-periodic, fixed boundary condition is used along the cc axis to accurately represent 2D systems. The canonical NVT ensemble, with temperature regulation provided by a Nose-Hoover thermostat [48], is employed. The simulation box is a 15×15×115\times 15\times 1 supercell, consisting of 900 atoms, with an integration time step of 1 femtosecond (fs).

SIII. Analytical calculation of coercive electric field

The fitting of energies and dipoles per unit cell along the BA to AB sliding pathway is performed using Origin [49]. Considering their even and odd function characteristics, ε0(t)\varepsilon_{0}(t) and p(t)p_{\parallel}(t) are fitted with quartic polynomials, and p(t)p_{\perp}(t) is fitted with cubic polynomials.Constraints are applied to ensure that ε0\varepsilon_{0} is minimized at the BA (AB) state, pp_{\parallel} is zero at the BA (AB) state, and pp_{\perp} reaches a maximum (minimum) at the BA (AB) state. The fitting results are presented in Fig.S3.

When the critical electric field is defined as the minimum field at which the local energy minimum of ε(t)\varepsilon(t) disappears, i.e., dε(t)/dt0\mathrm{d}\varepsilon(t)/\mathrm{d}t\leq 0 along the BA to SP sliding pathway, the exact analytical expression for E,cE_{\perp,c} is given by:

E,c=2e4tBA2p2E3tBAp38xm(m2),\displaystyle E_{\perp,c}=\frac{-2e_{4}t_{\mathrm{BA}}^{2}-p_{2}^{\parallel}E_{\parallel}}{3t_{\mathrm{BA}}p_{3}^{\perp}}\sqrt{\frac{8x}{m(m-2)}}, (S6)
wherem=34+32x+1436x260x+9\displaystyle\text{where}\ m=\frac{3}{4}+\frac{3}{2}x+\frac{1}{4}\sqrt{36x^{2}-60x+9}
andx=3(e4p4E)tBA22e4tBA2+p2E.\displaystyle\text{and}\ x=\frac{3(e_{4}-p_{4}^{\parallel}E_{\parallel})t_{\mathrm{BA}}^{2}}{2e_{4}t_{\mathrm{BA}}^{2}+p_{2}^{\parallel}E_{\parallel}}.

Eq.4 approximates Eq. S6 to the order of 0.5 of EE_{\parallel}.

Supplemental figures

Refer to caption
Figure S1: The sum of sliding-related BEC components of adjacent B\mathrm{B} and N\mathrm{N} ions in the top layer (orange line) and bottom layer (blue line) along the sliding pathway, calculated using DFPT. (a) The BEC component related to EE_{\perp} and the in-plane force in the sliding direction FF_{\parallel} (F=Z,EF_{\parallel}=Z_{\rm\parallel,\perp}E_{\perp}). (b) The BEC component related to EE_{\parallel} and FF_{\parallel} (F=Z,EF_{\parallel}=Z_{\parallel,\parallel}E_{\parallel}).
Refer to caption
Figure S2: The parity plot of the DREAM-Allegro (DA) model compared to DFT results. Comparison of energies ε0\varepsilon_{0} (a) and BECs ZZ (b) from the DA model against DFT calculations for all configurations in the training dataset. The insets display the distribution of the MAEs.
Refer to caption
Figure S3: Fit plots and goodness of fit (R2R^{2}) for energies ε0(t)\varepsilon_{0}(t) (a), in-plane dipoles p(t)p_{\parallel}(t) (b) and out-of-plane dipoles p(t)p_{\perp}(t) (c) per unit cell.
Refer to caption
Figure S4: The variation of the MD simulation obtained E,cE_{\perp,c} with EE_{\parallel} orienting from 00^{\circ} to 6060^{\circ} at a fixed magnitude of 0.1V/Å at 0.1K. E,cE_{\perp,c} is determined by identifying the SP state during the sliding process when EE_{\perp} along the z-z direction is incrementally increasing over time at a rate of 0.02 V/(Å\cdotps). Within the range of (0,60]\left(0^{\circ},60^{\circ}\right], the sliding consistently occurs at 6060^{\circ}, while at 00^{\circ}, the sliding occurs randomly at 6060^{\circ} or 300300^{\circ}. The closer the direction of EE_{\parallel} is to the direction of sliding, the smaller the E,cE_{\perp,c}.
Refer to caption
Figure S5: The variation of the MD simulation obtained E,cE_{\perp,c} with EE_{\parallel} at different magnitudes oriented at 6060^{\circ} and at different temperatures. E,cE_{\perp,c} is determined as the minimum vertical field, adjusted in increments of 0.05 V/Å, that can initiate sliding within 30 ps. The pentagram marks indicate the the minimum Et,cE_{t,c} at each temperature, corresponding to the blue line in Fig.4(c).
Refer to caption
Figure S6: (a) Energy ε0\varepsilon_{0} and polarization PP distribution of MoS2\mathrm{MoS_{2}}, calculated by the DFT and Berry phase approach. Positions within the hexagon correspond to different sliding vectors, with the center representing the ferroelectric XM state [24, 50]. The shades of grey in the background indicate energy levels. The direction of colored arrows shows in-plane polarizations PP_{\parallel}, while their colors represent out-of-plane polarization PP_{\perp}. Energy ε0\varepsilon_{0} (b) and polarization PP (c) along the designed sliding pathway.