Ion-Selective Transport Promotion Enabled by Angstrom-Scale Nanochannels in Dendrimer-Assembled Polyamide Nanofilm for Efficient Electrodialysis.

The ion permeability and selectivity of membranes are crucial in nanofluidic behavior, impacting industries ranging from traditional to advanced manufacturing. Herein, we demonstrate the engineering of ion-conductive membranes featuring angstrom-scale ion-transport channels by introducing ionic polyamidoamine (PAMAM) dendrimers for ion separation. The exterior quaternary ammonium-rich structure contributes to significant electrostatic charge exclusion due to enhanced local charge density; the interior protoplasmic channels of PAMAM dendrimer are assembled to provide additional degrees of free volume. This facilitates the monovalent ion transfer while maintaining continuity and efficient ion screening. The dendrimer-assembled hybrid membrane achieves high monovalent ion permeance of 2.81 mol m-2 h-1 (K+), reaching excellent mono/multivalent selectivity up to 20.1 (K+/Mg2+) and surpassing the permselectivities of state-of-the-art membranes. Both experimental results and simulating calculations suggest that the impressive ion selectivity arises from the significant disparity in transport energy barrier between mono/multivalent ions, induced by the "exterior-interior" synergistic effects of bifunctional membrane channels.

Long-range photonics-aided 17.6 Gbit/s D-band PS-64QAM transmission using gate recurrent unit algorithm with a complex QAM input.

D-band fiber-wireless technique that overcomes the bandwidth bottleneck of electrical devices has been popularized, but long-range D-band wireless transmission is still limited by the large absorption loss. So, the exploration of m-QAM formats is essential for the D-band long distance wireless transmission due to their different spectrum efficiency and SNR requirement. Moreover, nonlinearity in photonics-aided millimeter-wave (mm-wave) system is also a significant problem caused by fiber, photoelectrical devices and power amplifiers. So it is critical to employ a machine learning-based nonlinear compensation algorithm especially for long-distance D-band wireless delivery. A novel Gate Recurrent Unit (GRU) algorithm with a complex QAM input is proposed to further improve the receiver sensitivity of coherent D-band receiver, which effectively preserves the relative relationship between I/Q components of QAM signals and has memory capabilities with a better precision. We mainly discuss three learners with a complex QAM input, including complex-valued neural network (CVNN), single-lane Long Short-Term Memory (SL-LSTM) and single-lane Gate Recurrent Unit (SL-GRU). Thanks to these adaptive deep learning methods, we successfully realize 135 GHz 4Gbaud QPSK and PS-64QAM signal wireless transmission over 4.6 km, respectively. Considering the aspects of transmission capacity and recovery precision, CVNN equalizer is suitable for QPSK recovery, SL-GRU would be the best choice for PS-64QAM over D-band long range wireless transmission link up to km magnitude. The effective data rate can be achieved up to 17.6 Gbit/s. Therefore, we believe that the combination of high-order modulation and NN supervised algorithms with a complex input has an application prospect for the future 6 G mobile communication.

Photonics-aided 335†GHz PS-64QAM wireless transmission over 200 m employing complex-valued NN classification and random sampling techniques.

THz fiber-wireless technique can overcome the bandwidth bottleneck of electrical devices and has been popularized in different application scenarios. Furthermore, the probabilistic shaping (PS) technique can optimize both the transmission capacity and the distance, and has been extensively used in the optical fiber communication field. However, the probability of the point in the PS m-ary quadrature-amplitude-modulation (m-QAM) constellation varies with the amplitude, which leads to the class imbalance and degrades the performances of all supervised neural network classification algorithms. In this paper, we propose a novel complex-valued neural network (CVNN) classifier coupled with balanced random oversampling (ROS), which can be trained to restore the phase information simultaneously and overcome the class imbalance caused by PS. Based on this scheme, the fusion of oversampled features in complex domain increases the amount of the effective information of few classes, and thus improves the recognition accuracy effectively. It also has less requirement on the sample size than NN-based classifiers and largely simplifies the neural network architecture. By using our proposed ROS-CVNN classification method, single-lane 10 Gbaud 335 GHz PS-64QAM fiber-wireless transmission over 200 m free-space distance is experimentally realized, and the experimental results show that the efficient data rate is 44 Gbit/s considering the soft-decision forward-error-correction (SD-FEC) with 25% overhead. The results show that ROS-CVNN classifier outperforms the other real-valued NN equalizers and traditional Volterra-series by average 0.5 to 1 dB in receiver sensitivity at the bit error rate (BER) of 6 × 10-2 magnitude. Therefore, we believe that the combination of ROS and NN supervised algorithms has an application prospect for the future 6 G mobile communication.

65,536-QAM OFDM signal transmission over a fiber-THz system at 320†GHz with delta-sigma modulation.

The transmission of a 65,536-ary quadrature amplitude modulation (QAM) orthogonal frequency division multiplexing (OFDM) signal supported by a hybrid fiber-terahertz (THz) multiple-input multiple-output (MIMO) system at 320 GHz is experimentally demonstrated in this Letter. We adopt the polarization division multiplexing (PDM) technique to double the spectral efficiency. Based on a 23-GBaud 16-QAM link, 2-bit delta-sigma modulation (DSM) quantization enables 65,536-QAM OFDM signal transmission over a 20-km standard single-mode fiber (SSMF) and a 3-m 2 × 2 MIMO wireless delivery, and satisfies the hard-decision forward error correction (HD-FEC) threshold of 3.8 × 10-3, corresponding to a net rate of 60.5 Gbit/s for THz-over-fiber transport. Meanwhile, below the fronthaul error vector magnitude (EVM) threshold of 0.34%, a maximum signal-to-noise ratio (SNR) of 52.6 dB is achieved. To the best of our knowledge, this is the highest modulation order achievable for DSM applications in THz communication.

W-band RoF polarization multiplexing system supports 1048576 QAM with delta-sigma modulation.

We propose and experimentally verify a photonics-aided W-band millimeter wave (MMW) radio-over-fiber (RoF) polarization-multiplexed envelope detection system for high-order quadrature amplitude modulation (QAM) signals. To solve the problem of low spectral efficiency of common public radio interface (CPRI) and severe distortion of high-order QAM of envelope detection, quantization noise suppressed delta-sigma modulation (DSM) is introduced into the system. The experimental results show that the system can transmit 131072 QAM signals when meeting the error vector magnitude (EVM) requirements of 5G new radio (NR), and transmit 1048576 QAM signals when meeting the soft decision threshold (SD@20%).

Beyond 300-Gbps/λ photonics-aided THz-over-fiber transmission employing MIMO single-carrier frequency-domain equalizer.

We experimentally realized a 320-GHz 320-Gbps/λ terahertz (THz) radio-over-fiber (RoF) system based on a photonics-aided scheme with the help of polarization-division multiplexing (PDM) technology and multiple-input, multiple-output (MIMO) transmission. In this system, the low-complexity MIMO single-carrier frequency-domain equalizer (SCFDE) is implemented to compensate for the polarization-related impairments of the PDM signal, and the demultiplexing performances between SCFDE and the commonly used constant modulus algorithm (CMA) are also compared in this proposed system. After 20-km standard single-mode fiber (SSMF) and 3-m 2 × 2 MIMO wireless link transmission, the bit error rate (BER) of the received 46-GBaud PDM 16-ary quadrature amplitude modulation (16QAM) signal satisfies the soft-decision forward error correction (SD-FEC) threshold with 15% overhead, which corresponds to a record-breaking net bit rate of 320 Gbit/s.

SNR improved digital-delta-sigma-modulation radio-over-fiber scheme for D-band 4.6-km photonics-aided wireless fronthaul.

We propose a digital-delta-sigma-modulation radio-over-fiber (DDSM-RoF) scheme for wireless fronthaul and validate it experimentally in a D-band photonics-aided RoF transmission system. The 10-Gbaud DDSM-RoF signal with a common public radio interface equivalent data rate (CPRI-EDR) of 55.8 Gb/s is successfully transmitted in a 130-GHz 4.6-km wireless channel. The spectral efficiency (SE) is 5.58 bit/s/Hz and the capacity-distance product reaches 257 Gb/s·km. Up to 34.4-dB recovered signal-to-noise ratio (SNR) is observed to support the 1024-quadrature-amplitude-modulation (1024-QAM) transmission. Compared with the digital-analog-RoF (DA-RoF) scheme, the proposed DDSM-RoF achieves an SNR improvement of 5.9 dB.

Potential of direct granulation and organic loading rate tolerance of aerobic granular sludge in ultra-hypersaline environment.

Salt-tolerant aerobic granular sludge (SAGS) technology has shown potentials in the treatment of ultra-hypersaline high-strength organic wastewater. However, the long granulation period and salt-tolerance acclimation period are still bottlenecks that hinder SAGS applications. In this study, "one-step" development strategy was used to try to directly cultivate SAGS under 9% salinity, and the fastest cultivation process was obtained under such high salinity compared to the previous papers with the inoculum of municipal activated sludge without bioaugmentation. Briefly, the inoculated municipal activated sludge was almost discharged on Day 1-10, then fungal pellets appeared and it gradually transitioned to mature SAGS (particle size of ∼4156 µm and SVI30 of 57.8 mL/g) from Day 11 to Day 47 without fragmentation. Metagenomic revealed that fungus Fusarium played key roles in the transition process probably because it functioned as structural backbone. RRNPP and AHL-mediated systems might be the main QS regulation systems of bacteria. TOC and NH4+-N removal efficiencies maintained at ∼93.9% (after Day 11) and ∼68.5% (after Day 33), respectively. Subsequently, the influent organic loading rate (OLR) was stepwise increased from 1.8 to 11.7 kg COD/m3·d. It was found that SAGS could maintain intact structure and low SVI30 (< 55 mL/g) under 9% salinity and the OLR of 1.8-9.9 kg COD/m3·d with adjustment of air velocity. TOC and NH4+-N (TN) removal efficiencies could maintain at ∼95.4% (below OLR of 8.1 kg COD/m3·d) and ∼84.1% (below nitrogen loading rate of 0.40 kg N/m3·d) in ultra-hypersaline environment. Halomonas dominated the SAGS under 9% salinity and varied OLR. This study confirmed the feasibility of direct aerobic granulation in ultra-hypersaline environment and verified the upper OLR boundary of SAGS in ultra-hypersaline high-strength organic wastewater treatment.

4Gbaud PS-16QAM D-Band Fiber-Wireless Transmission over 4.6 km by Using Balance Complex-Valued NN Equalizer with Random Oversampling.

D-band (110-170 GHz) is a promising direction for the future of 6th generation mobile networks (6G) for high-speed mobile communication since it has a large available bandwidth, and it can provide a peak rate of hundreds of Gbit/s. Compared with the traditional electrical approach, photonics millimeter wave (mm-wave) generation in D-band is more practical and effectively overcomes the bottleneck of electrical devices. However, long-distance D-band wireless transmission is still limited by some key factors such as large absorption loss and nonlinear noises. Deep neural network algorithms are regarded as an important technique to model the nonlinear wireless behavior, among which the study on complex-value equalization is critical, especially in coherent detection systems. Moreover, probabilistic shaping is useful to improve the transmission capacity but also causes an imbalanced machine learning issue. In this paper, we propose a novel complex-valued neural network equalizer coupled with balanced random oversampling (ROS). Thanks to the adaptive deep learning method for probabilistic shaping-quadrature amplitude modulation (PS-QAM), we successfully realize a 135 GHz 4Gbaud PS-16QAM with a shaping entropy of 3.56 bit/symbol wireless transmission over 4.6 km. The bit error ratio (BER) of 4Gbaud PS-16QAM can be decreased to a soft-decision forward error correction (SD-FEC) with a 25% overhead of 2 × 10-2. Therefore, we can achieve a net rate of an 11.4 Gbit/s D-band radio-over-fiber (ROF) delivery over 4.6 km air free wireless distance.

Deep Learning Equalizer Connected with Viterbi-Viterbi Algorithm for PAM D-Band Radio over Fiber Link.

D-band (110-170 GHz) has been regarded as a potential candidate for the future 6G wireless network because of its large available bandwidth. At present, the lack of electrical amplifiers operating in the high frequency band and the strong nonlinear effect, i.e., the D-band, are still important problems. Therefore, effective methods to mitigate the nonlinear issue resulting from the ROF link are indispensable, among of which machine learning is considered the most effective paradigm to model the nonlinear behavior due to its nonlinear active function and structure. In order to reduce the computation amount and burden, a novel deep learning neural network equalizer connected with typical mathematical frequency offset estimation (FOE) and carrier phase recovery (CPR) algorithms is proposed. We implement D-band 45 Gbaud PAM-4 and 20 Gbaud PAM-8 ROF transmission simulations, and the simulation results show that the real value neural network (RVNN) equalizer connected with the Viterbi-Viterbi algorithm exhibits better compensation ability for nonlinear impairment, especially when dealing with serious inter-symbol interference and nonlinear effects. In our experiment, we employ coherent detection to further improve the receiver sensitivity, so a complex baseband signal after down conversion at the receiver is inherently produced. In this scenario, the complex value neural network (CVNN) and RVNN equalizer connected with the Viterbi-Viterbi algorithm have better BER performance with an error rate lower than the HD-FEC threshold of 3.8 × 10-3.

Aerobic granular sludge treating hypersaline wastewater: Impact of pH on granulation and long-term operation at different organic loading rates.

pH is one of the major parameters that influence the granulation and long-term operation of aerobic granular sludge (AGS). In hypersaline wastewater, the impact of pH on granulation and the extent of organic loading rate (OLR) that AGS can withstand under different pH are still not clear. In this study, AGS was cultivated at 3% salinity in three sequencing batch reactors with influent pH values of 5.0, 7.0, and 9.0, respectively, and the OLR was stepwise increased from 2.4 to 16.8 kg COD/m3·d after the granules maturation. The results showed the satisfactory granulation and organic removal under different influent pH conditions, in which the granulation was completed on day 43, 23, and 23, respectively. Neutral influent was the most appropriate for development of salt-tolerant aerobic granular sludge (SAGS), while acidic environment induced the formation of fluffy filamentous granules, and alkaline environment weakened the granule stability. Metagenomic analysis revealed the similar microbial community of neutral and alkaline conditions, with the predominance of genus Paracoccus_f__Rhodobacteraceae. While in acidic environment, fungus Fusarium formed the skeleton of filamentous granules and functioned as the carrier of bacteria including Azoarcus and Pararhodobacter. With the elevation of OLR, SAGSs were found to maintain the compact structure under OLRs of 2.4, 7.2, and 2.4 kg COD/m3·d, and obtain high TOC removal (>95.0%) under OLRs of 7.2, 14.4, and 14.4 kg COD/m3·d, respectively. For hypersaline high-strength organic wastewater, satisfactory TOC removal could also be obtained at broad pH ranges (5.0-9.0), in which neutral environment was the most suitable and acidic environment was the worst. This study contributed to a better understanding of SAGS granulation and treatment of hypersaline high-strength organic wastewater with different pH values.

D-band signal generation and transmission without optical filter based on optical carrier suppression and single-sideband modulation.

We experimentally demonstrated a novel and simple scheme to generate D-band millimeter-wave (mm-wave) signal without optical filter based on optical carrier suppression (OCS) and single-sideband (SSB). One intensity modulator (IM) driven by radio frequency (RF) signal at 50 GHz is firstly employed to generate two tones with channel spacing of 2 x RF frequency based on OCS. Another subsequent in-phase/quadrature (I/Q) modulator driven by RF signal at 30 GHz is then applied to generate SSB signal by using independent sideband (ISB). No optical filter is needed so that the whole system can be simplified. After using a D-band photomixer for detection, we finally generated the vector mm-wave at 130 GHz. Based on the proposed system, 4-Gbaud/8-Gbaud quadrature phase shift keying (QPSK) information carried by the generated D-band mm-wave signals were transmitted over 22.5-km single model fiber (SMF) and 1-m wireless distance radio-over-fiber (ROF) link. Bit-error-ratio (BER) performances under hard/soft-decision forward-error-correction (FEC) threshold are shown respectively in cases of two different signals transmission rates.

Dual-band polarization-insensitive toroidal dipole quasi-bound states in the continuum in a permittivity-asymmetric all-dielectric meta-surface.

Ultra-high quality (Q) factor resonances derived from the bound states in the continuum (BICs) have drawn much attention in optics and photonics. Especially in meta-surfaces, they can enable ultrasensitive sensors, spectral filtering, and lasers because of their enhanced light-matter interactions and rare superiority of scalability. In this paper, we propose a permittivity-asymmetric all-dielectric meta-surface, comprising high-index cuboid tetramer clusters with symmetric structural parameters and configuring periodically on a glass substrate. Simulation results offer dual-band quasi-BICs with high Q values of 4447 and 11391, respectively. Multipolar decomposition in cartesian and electromagnetic distributions are engaged to analyze the physical mechanism of dual quasi-BIC modes, which reveals that they are both governed by magnetic quadrupole (MQ) and in-plane toroidal dipole (TD). The polarization-insensitive and scalable characteristics are also investigated. Additionally, we appraise the sensing performances of the proposed structure. As an example, our work supports an uncommon route to design dual-band polarization-insensitive TD quasi-BICs resonators and facilitates their applications in optic and photonics, such as low-threshold lasers and sensing.

Photonics millimeter wave bidirectional full-duplex communication based on polarization multiplexing.

We have proposed and experimentally implemented a photonics-aided large-capacity long-distance mm-wave bidirectional full-duplex communication system at the W-band based on polarization multiplexing. The same radio frequency (RF) carrier source is shared by both the uplink and the downlink, and a pair of orthomode transducers (OMTs) are used to separate the dual orthogonally polarized channels. To achieve the maximum spectrum efficiency and throughput, 10-Gbaud probabilistically shaped 256-level quadrature-amplitude-modulation (PS-256QAM) signals with 7.07 bit/symbol/Hz are transmitted in Ch. H and Ch. V. The system can support the bidirectional transmission with 103-Gbps data rate over 4600-m RF wireless distance. To the best of our knowledge, based on a photonics-aided bidirectional full-duplex system, this is the first time to realize a record-breaking bit rate-distance product at the W-band, i.e., 103 Gbps × 4.6 km = 473.8 Gbps•km.

Experimental demonstration of pseudo-pilots-aided Gaussian basis expansion-based phase noise suppression scheme for CO-OFDM.

In this paper, we propose a novel phase noise suppression scheme called pseudo-pilots-aided Gaussian basis expansion (PS-GBE) for coherent optical orthogonal frequency division multiplexing (CO-OFDM) system. Integrating with the pseudo-pilots, the Gaussian basis can suppress and fit phase noise effectively with high spectral efficiency (SE). We experimentally demonstrate the proposed scheme in 200-Gb/s optical QPSK-OFDM superchannel and 400-Gb/s optical 16QAM-OFDM superchannel. According to the experimental results, the proposed PS-GBE has a phase noise suppression performance similar to the GBE scheme. However, different from the GBE scheme, fewer pilots are needed for phase noise estimation in PS-GBE. Hence, the proposed PS-GBE can achieve higher SE. Compared to the pseudo-pilots-aided orthogonal basis expansion-based (PS-OBE) phase noise suppression and traditional common phase noise compensation (CPEC) methods, the proposed PS-GBE can get a significant performance enhancement. In the QPSK-OFDM system, a Q-factor improvement of 1.1 dB is obtained compared to the PS-OBE method. In the 16QAM-OFDM system, the BER is enhanced from 1.00E-03 to 2.05E-04. Further simulation results indicate that our proposed PS-GBE scheme can effectively increase laser linewidth tolerance. The proposed scheme can be applied to CO-OFDM and extended to coherent optical filterbank multicarrier (CO-FBMC) and coherent optical single carrier frequency domain multiplexing (CO-SCFDM) transmission system.

Association of single-nucleotide polymorphisms in TLR4 gene and gene-environment interaction with primary open angle glaucoma in a Chinese northern population.

BACKGROUND: The present study aimed to investigate the association of several single nucleotide polymorphisms (SNPs) within the Toll-like receptor 4 (TLR4) gene and additional gene-environment interaction with primary open angle glaucoma (POAG) risk. METHODS: Tests for Hardy-Weinberg equilibrium in controls and haplotype analysis were performed using SNPstats (https://www.snpstats.net). Generalized multifactor dimensionality reduction (GMDR) was performed to test the interaction effects among four SNPs within the TLR4 gene and environmental factors. Logistic regression was performed to calculate the odds ratios (ORs) (95% confidence interval [CI]) for association between four SNPs within the TLR4 gene and POAG risk. RESULTS: The POAG risk was significantly higher in carriers with the T allele of rs4986791 and the T allele of rs2149356 within the TLR4 gene than in those with the wild-type genotype, adjusted ORs (95% CI) were 1.65 (1.23-2.12) and 1.70 (1.16-2.31). The GMDR model suggested a significant two-locus model (p = 0.0010) involving rs2149356 and alcohol drinking. Alcohol drinkers with the rs2149356-GT+TT genotype within the TLR4 gene have the highest POAG risk compared to never alcohol drinkers with the rs2149356-GG genotype (OR = 2.62; 95% CI = 1.48-3.78) after covariates adjustment. However, the study did not find a significant any-locus model involving SNP and smoking. In all samples, the haplotype rs2149356-G-rs7873784-C was observed most frequently in two groups (47.47% and 48.21% for the POAG patients and controls, respectively). The results also indicated that no significant haplotype was associated with POAG risk. CONCLUSIONS: The minor alleles of rs4986791 and rs2149356 within the TLR4 gene, as well as interaction between rs2149356 and alcohol drinking, were associated with an increased POAG risk.

Multi scrolls chaotic encryption scheme for CO-OFDM-PON.

In this paper, we propose and experimentally demonstrate a novel multi scrolls chaotic encryption scheme for CO-OFDM-PON. We analyze the principle of 3-dimension encryption scheme and discuss its encryption complexity. Compared with the previous hyper Chen chaotic encryption scheme, the proposed encryption algorithm can realize dynamic constellation point mapping of QAM signal with lower encryption complexity. We also compare the transmission performances of the two chaotic encryption schemes. The results show that the proposed multi scrolls scheme has better BER performance because it can decrease the peak to average power ratio (PAPR) of OFDM. What is more, the proposed encryption scheme is very sensitive to the initial secure key and a tiny discrepancy as small as 10-17 would lead to a completely different sequence. The high sensibility to the initial value can effectively increase encryption level and the key space of the multi scrolls encryption scheme is 106 times of that hyper Chen. Further, to verify the effectiveness of the proposed encryption algorithm, encrypted transmission of a digital picture in 80 km SSMF is carried out.

Gaussian basis expansion phase noise suppression method for CO-OFDM systems.

In this paper, we propose a novel phase noise suppression method based on Gaussian basis expansion (GBE) for CO-OFDM systems. We analyze the basic phase noise suppression principle of GBE and then demonstrate it in optical OFDM transmission systems. Compared with common phase compensation (CPE), orthogonal basis expansion (OBE) and eigenvector basis expansion (EBE) schemes, the proposed GBE scheme has better phase noise fitting ability with similar computation complexity. Futhermore, no additional back to back (BTB) pre-training is needed for the GBE scheme. Performance improvements by the GBE is experimental validated in the QPSK/16-QAM OFDM system with different transmission scenarios (different number of pilots and input power). In the QPSK-OFDM system, after 160 km SSMF transmission, a Q-factor improvement of 1.7 dB and 0.5 dB are achieved compared with the CPE and OBE schemes at the optimum input power of -4 dBm, respectively. In the 16-QAM-OFDM system, the measured BER improved from 8.21×10-4 to 2.36×10-4 with the GBE scheme. To further verify the effectiveness of the GBE scheme, we change the laser linewidth and measure the long transmission distance performance by simulation, the results show that the GBE scheme can effectively increase the laser linewidth tolerance and extend transmission distance. When the linewidth is 2-MHz, the proposed GBE scheme can extend the transmission distance from 1120 km to 1540 km at the BER of 10-4. Experimental and simulation results show that the proposed GBE scheme is a promising alternative phase noise suppression for CO-OFDM system.

Accurate predictions of aqueous solubility of drug molecules via the multilevel graph convolutional network (MGCN) and SchNet architectures.

Deep learning based methods have been widely applied to predict various kinds of molecular properties in the pharmaceutical industry with increasingly more success. In this study, we propose two novel models for aqueous solubility predictions, based on the Multilevel Graph Convolutional Network (MGCN) and SchNet architectures, respectively. The advantage of the MGCN lies in the fact that it could extract the graph features of the target molecules directly from the (3D) structural information; therefore, it doesn't need to rely on a lot of intra-molecular descriptors to learn the features, which are of significance for accurate predictions of the molecular properties. The SchNet performs well in modelling the interatomic interactions inside a molecule, and such a deep learning architecture is also capable of extracting structural information and further predicting the related properties. The actual accuracy of these two novel approaches was systematically benchmarked with four different independent datasets. We found that both the MGCN and SchNet models performed well for aqueous solubility predictions. In the future, we believe such promising predictive models will be applicable to enhancing the efficiency of the screening, crystallization and delivery of drug molecules, essentially as a useful tool to promote the development of molecular pharmaceutics.

Performance of new density functionals of nondynamic correlation on chemical properties.

Becke'13 (B13) is a general density functional theory (DFT) designed for strongly correlated molecules. Kong-Proynov'16/B13 (KP16/B13) is a modification of B13 that treats the correlation kinetic term through modeling the adiabatic connection and contains fewer parameters. A question remains whether functionals designed for extremely strong correlations can handle correlation of normal strength. In this work, both functionals are benchmarked with a variety of molecular systems from the Minnesota-2015 datasets and compared with the mainstream functionals such as B3LYP and a spectrum of other types of functionals, as well as Becke'05 (B05), the predecessor of B13. Our calculations, made possible with an efficient self-consistent-field implementation of those new functionals, show that B05, B13, and KP16/B13, based on full HF exchange, recover a majority of the correlation where it is very significant (i.e., where HF has large errors). They perform very well for reaction barriers. On the other hand, their performance on multireference systems is mixed. Overall, B05, B13, and KP16/B13 are competitive to B3LYP, and B05 is even competitive to heavily parameterized functionals for most sets despite containing 100% HF exchange. KP16/B13, in particular, contains only three empirical parameters, demonstrating the possibility of treating correlation of all strength with single-determinant Kohn-Sham DFT.