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Electrochemical CO2 reduction (CO2R) is an attractive option for storing renewable electricity and for the sustainable production of valuable chemicals and fuels. In this roadmap, we review recent progress in fundamental understanding, catalyst development, and in engineering and scale-up. We discuss the outstanding challenges towards commercialization of electrochemical CO2R technology: energy efficiencies, selectivities, low current densities, and stability. We highlight the opportunities in establishing rigorous standards for benchmarking performance, advances in in operando characterization, the discovery of new materials towards high value products, the investigation of phenomena across multiple-length scales and the application of data science towards doing so. We hope that this collective perspective sparks new research activities that ultimately bring us a step closer towards establishing a low- or zero-emission carbon cycle.

Electrochemical CO2 reduction (CO2R) is an attractive option for storing renewable electricity and for the sustainable production of valuable chemicals and fuels. In this roadmap, we review recent progress in fundamental understanding, catalyst development, and in engineering and scale-up. We discuss the outstanding challenges towards commercialization of electrochemical CO2R technology: energy efficiencies, selectivities, low current densities, and stability. We highlight the opportunities in establishing rigorous standards for benchmarking performance, advances in in operando characterization, the discovery of new materials towards high value products, the investigation of phenomena across multiple-length scales and the application of data science towards doing so. We hope that this collective perspective sparks new research activities that ultimately bring us a step closer towards establishing a low- or zero-emission carbon cycle.

Electrochemical CO2 reduction (CO2R) is an attractive option for storing renewable electricity and for the sustainable production of valuable chemicals and fuels. In this roadmap, we review recent progress in fundamental understanding, catalyst development, and in engineering and scale-up. We discuss the outstanding challenges towards commercialization of electrochemical CO2R technology: energy efficiencies, selectivities, low current densities, and stability. We highlight the opportunities in establishing rigorous standards for benchmarking performance, advances in in operando characterization, the discovery of new materials towards high value products, the investigation of phenomena across multiple-length scales and the application of data science towards doing so. We hope that this collective perspective sparks new research activities that ultimately bring us a step closer towards establishing a low- or zero-emission carbon cycle.

Electrochemical CO2 reduction (CO2R) is an attractive option for storing renewable electricity and for the sustainable production of valuable chemicals and fuels. In this roadmap, we review recent progress in fundamental understanding, catalyst development, and in engineering and scale-up. We discuss the outstanding challenges towards commercialization of electrochemical CO2R technology: energy efficiencies, selectivities, low current densities, and stability. We highlight the opportunities in establishing rigorous standards for benchmarking performance, advances in in operando characterization, the discovery of new materials towards high value products, the investigation of phenomena across multiple-length scales and the application of data science towards doing so. We hope that this collective perspective sparks new research activities that ultimately bring us a step closer towards establishing a low- or zero-emission carbon cycle.

Electrochemical CO2 reduction (CO2R) is an attractive option for storing renewable electricity and for the sustainable production of valuable chemicals and fuels. In this roadmap, we review recent progress in fundamental understanding, catalyst development, and in engineering and scale-up. We discuss the outstanding challenges towards commercialization of electrochemical CO2R technology: energy efficiencies, selectivities, low current densities, and stability. We highlight the opportunities in establishing rigorous standards for benchmarking performance, advances in in operando characterization, the discovery of new materials towards high value products, the investigation of phenomena across multiple-length scales and the application of data science towards doing so. We hope that this collective perspective sparks new research activities that ultimately bring us a step closer towards establishing a low- or zero-emission carbon cycle.

Efficient wide-bandgap perovskite solar cells (PSCs) enable high-efficiency tandem photovoltaics when combined with crystalline silicon and other low-bandgap absorbers. However, wide-bandgap PSCs today exhibit performance far inferior to that of sub-1.6-eV bandgap PSCs due to their tendency to form a high density of deep traps. Here, we show that healing the deep traps in wide-bandgap perovskites-in effect, increasing the defect tolerance via cation engineering-enables further performance improvements in PSCs. We achieve a stabilized power conversion efficiency of 20.7% for 1.65-eV bandgap PSCs by incorporating dipolar cations, with a high open-circuit voltage of 1.22 V and a fill factor exceeding 80%. We also obtain a stabilized efficiency of 19.1% for 1.74-eV bandgap PSCs with a high open-circuit voltage of 1.25 V. From density functional theory calculations, we find that the presence and reorientation of the dipolar cation in mixed cation-halide perovskites heals the defects that introduce deep trap states.

Efficient wide-bandgap perovskite solar cells (PSCs) enable high-efficiency tandem photovoltaics when combined with crystalline silicon and other low-bandgap absorbers. However, wide-bandgap PSCs today exhibit performance far inferior to that of sub-1.6-eV bandgap PSCs due to their tendency to form a high density of deep traps. Here, we show that healing the deep traps in wide-bandgap perovskites-in effect, increasing the defect tolerance via cation engineering-enables further performance improvements in PSCs. We achieve a stabilized power conversion efficiency of 20.7% for 1.65-eV bandgap PSCs by incorporating dipolar cations, with a high open-circuit voltage of 1.22 V and a fill factor exceeding 80%. We also obtain a stabilized efficiency of 19.1% for 1.74-eV bandgap PSCs with a high open-circuit voltage of 1.25 V. From density functional theory calculations, we find that the presence and reorientation of the dipolar cation in mixed cation-halide perovskites heals the defects that introduce deep trap states.

Multiple description coding (MDC) is a source coding technique that exploits path diversity to solve packet losses over error-prone channels. In this paper, we propose an improved drift-free multi-state MDC method based on H.264/AVC coding scheme. At the encoder side, we compress original video into multiple independent H.264 streams with different coding parameters, which can help us to control correlations between the descriptions. At the decoder side, each description is considered as a noisy observation of the original video, and a linear minimum mean square error (LMMSE) based merge algorithm is proposed to combine the descriptions. Experimental results show that the proposed algorithm can achieve better coding efficiency and visual quality than temporary MDC present in [1]. The error resilience ability is also improved by the fact that each frame is coded twice with different parameters. ©2009 IEEE.

A proper theoretical quantization-distortion model for hybrid video coding is always desirable, since this allows us to explain the behavior of existing codecs and to design better ones. However, due to the existence of motion-compensated prediction, hybrid video coding introduces interframe dependency into the encoded video, which makes its quantization-distortion characteristics difficult to analyze. In this paper, a joint analysis of quantization and motion-compensated prediction is presented. For a complete analysis, we investigate not only the distortion that quantization introduces into video signal, but also its effect on motion-compensated prediction. Based on the joint analysis, a quantization-distortion model of hybrid video coding is proposed. Our extensive experimental results show that the proposed model can estimate the quantization-distortion curve of hybrid video coding with high accuracy. Furthermore, the estimation accuracy remains high for various video sequences and encoder configurations.

Multiple description coding (MDC) is a source coding technique that exploits path diversity to solve packet losses over error-prone channels. In this paper, we propose an improved drift-free multi-state MDC method based on H.264/AVC coding scheme. At the encoder side, we compress original video into multiple independent H.264 streams with different coding parameters, which can help us to control correlations between the descriptions. At the decoder side, each description is considered as a noisy observation of the original video, and a linear minimum mean square error (LMMSE) based merge algorithm is proposed to combine the descriptions. Experimental results show that the proposed algorithm can achieve better coding efficiency and visual quality than temporary MDC present in [1]. The error resilience ability is also improved by the fact that each frame is coded twice with different parameters. ©2009 IEEE.

A proper theoretical quantization-distortion model for hybrid video coding is always desirable, since this allows us to explain the behavior of existing codecs and to design better ones. However, due to the existence of motion-compensated prediction, hybrid video coding introduces interframe dependency into the encoded video, which makes its quantization-distortion characteristics difficult to analyze. In this paper, a joint analysis of quantization and motion-compensated prediction is presented. For a complete analysis, we investigate not only the distortion that quantization introduces into video signal, but also its effect on motion-compensated prediction. Based on the joint analysis, a quantization-distortion model of hybrid video coding is proposed. Our extensive experimental results show that the proposed model can estimate the quantization-distortion curve of hybrid video coding with high accuracy. Furthermore, the estimation accuracy remains high for various video sequences and encoder configurations.

A proper theoretical quantization-distortion model for hybrid video coding is always desirable, since this allows us to explain the behavior of existing codecs and to design better ones. However, due to the existence of motion-compensated prediction, hybrid video coding introduces interframe dependency into the encoded video, which makes its quantization-distortion characteristics difficult to analyze. In this paper, a joint analysis of quantization and motion-compensated prediction is presented. For a complete analysis, we investigate not only the distortion that quantization introduces into video signal, but also its effect on motion-compensated prediction. Based on the joint analysis, a quantization-distortion model of hybrid video coding is proposed. Our extensive experimental results show that the proposed model can estimate the quantization-distortion curve of hybrid video coding with high accuracy. Furthermore, the estimation accuracy remains high for various video sequences and encoder configurations.

Multiple description coding (MDC) is a source coding technique that exploits path diversity to solve packet losses over error-prone channels. In this paper, we propose an improved drift-free multi-state MDC method based on H.264/AVC coding scheme. At the encoder side, we compress original video into multiple independent H.264 streams with different coding parameters, which can help us to control correlations between the descriptions. At the decoder side, each description is considered as a noisy observation of the original video, and a linear minimum mean square error (LMMSE) based merge algorithm is proposed to combine the descriptions. Experimental results show that the proposed algorithm can achieve better coding efficiency and visual quality than temporary MDC present in [1]. The error resilience ability is also improved by the fact that each frame is coded twice with different parameters. ©2009 IEEE.

An efficient temporal search range prediction method is proposed to reduce the complexity of multiple reference frames motion estimation (MRFME) in video coding. Based on a linear model of motion-compensated residue, the behavior of residues under MRFME is investigated, and the gain of multiple reference frames is analyzed. The proposed method utilizes the current residue to estimate the gain of searching more reference frames, and predicts the temporal search range that maintains the coding performance with minimum complexity. Experimental results show that the proposed scheme can significantly reduce the complexity in motion estimation while the degradation of the coding performance is negligible.

An efficient temporal search range prediction method is proposed to reduce the complexity of multiple reference frames motion estimation (MRFME) in video coding. Based on a linear model of motion-compensated residue, the behavior of residues under MRFME is investigated, and the gain of multiple reference frames is analyzed. The proposed method utilizes the current residue to estimate the gain of searching more reference frames, and predicts the temporal search range that maintains the coding performance with minimum complexity. Experimental results show that the proposed scheme can significantly reduce the complexity in motion estimation while the degradation of the coding performance is negligible.

An efficient temporal search range prediction method is proposed to reduce the complexity of multiple reference frames motion estimation (MRFME) in video coding. Based on a linear model of motion-compensated residue, the behavior of residues under MRFME is investigated, and the gain of multiple reference frames is analyzed. The proposed method utilizes the current residue to estimate the gain of searching more reference frames, and predicts the temporal search range that maintains the coding performance with minimum complexity. Experimental results show that the proposed scheme can significantly reduce the complexity in motion estimation while the degradation of the coding performance is negligible.

In this paper, we propose an Error Concealment algorithm for INTRA-frame losses over packet loss channels. The novelty is that not only the INTRA-frame but also the subsequent INTER-frames are error concealed. We use the received INTRA-MBs to refine their neighbors based on the strong correlation between adjacent pixel values. In addition, Motion Compensation is used to reconstruct the INTER-pixel which has an INTRA-pixel in its motion trajectory. Both subjective and objective simulation results are given to demonstrate the performance of our proposed algorithm.

Due to the storage limit, the original raw video may not exist after compressing it into multiple video bitstreams using different compression parameters. In this paper, we suggest a least square error (LSE) algorithm to jointly decode the multiple video bitstreams, aiming to achieve better quality of the reconstructed video. The experimental results by joint decoding of multiple H.263 streams show that the proposed algorithm can significantly enhance the decoded video quality.

Multiple description coding (MDC) is a source coding technique that exploits path diversity to combat packet losses over error-prone channels. In this thesis, we proposed a novel drift-free multi-state MDC method. At the encoder side, the original video is compressed into multiple independently decodable H.263 streams, each with its own coding structure and prediction process, such that if one stream is lost, the other stream can still be used to produce video with acceptable quality. At the decoder side, each description is considered as a noisy observation of the original video. A minimum mean-square error (MMSE) based joint reconstruction algorithm is proposed to combine the descriptions. The experimental results show that the proposed algorithm has high coding efficiency, yet with strong error resilience.

In this paper, we analyze the error recovery performance of variable length codes (VLCs) transmitted over binary symmetric channel (BSC). Simple expressions for the exact mean symbol error rate (MSER) and the exact variance of symbol error rate (VSER) for any crossover probability p, are presented. We also prove that the mean error propagation length (MEPL) derived for single bit inversion error case is a scaled value of MSER when p, tends to zero. Comparisons with simulations demonstrate the accuracy of the MSER and VSER expressions.

Denoising module. is required by any practical video processing systems. Most existing denoising schemes are spatio-temporal filters which operate on data over three dimensions. However, to limit the number of inputs, these filters only utilize one reference frame and cannot fully exploit temporal correlation. In this paper, a recursive temporal denoising filter named multihypothesis motion compensated filter (MHMCF) is proposed. To fully exploit temporal correlation, MHMCF performs motion estimation in a number of reference frames to construct multiple hypotheses (temporal predictions) of the current pixel. These hypotheses are combined by weighted averaging to suppress noise and estimate the actual current pixel value. Based on the multihypothesis motion compensated residue model presented in this paper, we investigate the efficiency of MHMCF, and some numerical evaluations are revealed. Experimental results show that MHMCF demonstrates quite good denoising performance while the inputs are much fewer than spatio-temporal filters. Moreover, as a purely temporal filter, it can well preserve spatial details and achieve satisfactory visual quality.

This letter addresses the security issues of the multimedia encryption schemes using multiple Huffman table (MHT). A known-plaintext attack is presented to show that the MHTs used for encryption should be carefully selected to avoid the weak keys problem. We then propose chosen-plaintext attacks on the basic MHT algorithm as well as the enhanced scheme with random bit insertion. In addition, we suggest two empirical criteria for Huffman table selection, based on which we can simplify the stream cipher integrated scheme, while ensuring a high level of security.

Multi-hypothesis motion compensated filter (MHMCF) utilizes a number of hypotheses (temporal predictions) to estimate the current pixel which is corrupted with noise. While showing remarkable denoising results, MHMCF is computationally intensive as full search is employed in the expectation of finding good temporal predictions in the presence of noise. In the frame of MHMCF, a fast denoising algorithm FMHMCF is proposed in this paper. With edge preserved low pass prefiltering and noise-robust fast multihypothesis search, FMHMCF could find reliable hypotheses while checking very few search locations, so that the denoising process can be dramatically accelerated. Experimental results show that FMHMCF can be 10 to 15 times faster than MIIMCF, while achieving the same or even better denoising performance. © 2007 IEEE.

In this paper, we analyze the error recovery performance of variable length codes (VLCs) transmitted over binary symmetric channel (BSC). Simple expressions for the exact mean symbol error rate (MSER) and the exact variance of symbol error rate (VSER) for any crossover probability p, are presented. We also prove that the mean error propagation length (MEPL) derived for single bit inversion error case is a scaled value of MSER when p, tends to zero. Comparisons with simulations demonstrate the accuracy of the MSER and VSER expressions.

Due to the storage limit, the original raw video may not exist after compressing it into multiple video bitstreams using different compression parameters. In this paper, we suggest a least square error (LSE) algorithm to jointly decode the multiple video bitstreams, aiming to achieve better quality of the reconstructed video. The experimental results by joint decoding of multiple H.263 streams show that the proposed algorithm can significantly enhance the decoded video quality.

Multiple description coding (MDC) is a source coding technique that exploits path diversity to combat packet losses over error-prone channels. In this thesis, we proposed a novel drift-free multi-state MDC method. At the encoder side, the original video is compressed into multiple independently decodable H.263 streams, each with its own coding structure and prediction process, such that if one stream is lost, the other stream can still be used to produce video with acceptable quality. At the decoder side, each description is considered as a noisy observation of the original video. A minimum mean-square error (MMSE) based joint reconstruction algorithm is proposed to combine the descriptions. The experimental results show that the proposed algorithm has high coding efficiency, yet with strong error resilience.

This letter addresses the security issues of the multimedia encryption schemes using multiple Huffman table (MHT). A known-plaintext attack is presented to show that the MHTs used for encryption should be carefully selected to avoid the weak keys problem. We then propose chosen-plaintext attacks on the basic MHT algorithm as well as the enhanced scheme with random bit insertion. In addition, we suggest two empirical criteria for Huffman table selection, based on which we can simplify the stream cipher integrated scheme, while ensuring a high level of security.

Denoising module. is required by any practical video processing systems. Most existing denoising schemes are spatio-temporal filters which operate on data over three dimensions. However, to limit the number of inputs, these filters only utilize one reference frame and cannot fully exploit temporal correlation. In this paper, a recursive temporal denoising filter named multihypothesis motion compensated filter (MHMCF) is proposed. To fully exploit temporal correlation, MHMCF performs motion estimation in a number of reference frames to construct multiple hypotheses (temporal predictions) of the current pixel. These hypotheses are combined by weighted averaging to suppress noise and estimate the actual current pixel value. Based on the multihypothesis motion compensated residue model presented in this paper, we investigate the efficiency of MHMCF, and some numerical evaluations are revealed. Experimental results show that MHMCF demonstrates quite good denoising performance while the inputs are much fewer than spatio-temporal filters. Moreover, as a purely temporal filter, it can well preserve spatial details and achieve satisfactory visual quality.

Multi-hypothesis motion compensated filter (MHMCF) utilizes a number of hypotheses (temporal predictions) to estimate the current pixel which is corrupted with noise. While showing remarkable denoising results, MHMCF is computationally intensive as full search is employed in the expectation of finding good temporal predictions in the presence of noise. In the frame of MHMCF, a fast denoising algorithm FMHMCF is proposed in this paper. With edge preserved low pass prefiltering and noise-robust fast multihypothesis search, FMHMCF could find reliable hypotheses while checking very few search locations, so that the denoising process can be dramatically accelerated. Experimental results show that FMHMCF can be 10 to 15 times faster than MIIMCF, while achieving the same or even better denoising performance. © 2007 IEEE.

In this paper, we propose an Error Concealment algorithm for INTRA-frame losses over packet loss channels. The novelty is that not only the INTRA-frame but also the subsequent INTER-frames are error concealed. We use the received INTRA-MBs to refine their neighbors based on the strong correlation between adjacent pixel values. In addition, Motion Compensation is used to reconstruct the INTER-pixel which has an INTRA-pixel in its motion trajectory. Both subjective and objective simulation results are given to demonstrate the performance of our proposed algorithm.

In this paper, we analyze the error recovery performance of variable length codes (VLCs) transmitted over binary symmetric channel (BSC). Simple expressions for the exact mean symbol error rate (MSER) and the exact variance of symbol error rate (VSER) for any crossover probability p, are presented. We also prove that the mean error propagation length (MEPL) derived for single bit inversion error case is a scaled value of MSER when p, tends to zero. Comparisons with simulations demonstrate the accuracy of the MSER and VSER expressions.

Due to the storage limit, the original raw video may not exist after compressing it into multiple video bitstreams using different compression parameters. In this paper, we suggest a least square error (LSE) algorithm to jointly decode the multiple video bitstreams, aiming to achieve better quality of the reconstructed video. The experimental results by joint decoding of multiple H.263 streams show that the proposed algorithm can significantly enhance the decoded video quality.

Multiple description coding (MDC) is a source coding technique that exploits path diversity to combat packet losses over error-prone channels. In this thesis, we proposed a novel drift-free multi-state MDC method. At the encoder side, the original video is compressed into multiple independently decodable H.263 streams, each with its own coding structure and prediction process, such that if one stream is lost, the other stream can still be used to produce video with acceptable quality. At the decoder side, each description is considered as a noisy observation of the original video. A minimum mean-square error (MMSE) based joint reconstruction algorithm is proposed to combine the descriptions. The experimental results show that the proposed algorithm has high coding efficiency, yet with strong error resilience.

Denoising module. is required by any practical video processing systems. Most existing denoising schemes are spatio-temporal filters which operate on data over three dimensions. However, to limit the number of inputs, these filters only utilize one reference frame and cannot fully exploit temporal correlation. In this paper, a recursive temporal denoising filter named multihypothesis motion compensated filter (MHMCF) is proposed. To fully exploit temporal correlation, MHMCF performs motion estimation in a number of reference frames to construct multiple hypotheses (temporal predictions) of the current pixel. These hypotheses are combined by weighted averaging to suppress noise and estimate the actual current pixel value. Based on the multihypothesis motion compensated residue model presented in this paper, we investigate the efficiency of MHMCF, and some numerical evaluations are revealed. Experimental results show that MHMCF demonstrates quite good denoising performance while the inputs are much fewer than spatio-temporal filters. Moreover, as a purely temporal filter, it can well preserve spatial details and achieve satisfactory visual quality.

This letter addresses the security issues of the multimedia encryption schemes using multiple Huffman table (MHT). A known-plaintext attack is presented to show that the MHTs used for encryption should be carefully selected to avoid the weak keys problem. We then propose chosen-plaintext attacks on the basic MHT algorithm as well as the enhanced scheme with random bit insertion. In addition, we suggest two empirical criteria for Huffman table selection, based on which we can simplify the stream cipher integrated scheme, while ensuring a high level of security.

Multi-hypothesis motion compensated filter (MHMCF) utilizes a number of hypotheses (temporal predictions) to estimate the current pixel which is corrupted with noise. While showing remarkable denoising results, MHMCF is computationally intensive as full search is employed in the expectation of finding good temporal predictions in the presence of noise. In the frame of MHMCF, a fast denoising algorithm FMHMCF is proposed in this paper. With edge preserved low pass prefiltering and noise-robust fast multihypothesis search, FMHMCF could find reliable hypotheses while checking very few search locations, so that the denoising process can be dramatically accelerated. Experimental results show that FMHMCF can be 10 to 15 times faster than MIIMCF, while achieving the same or even better denoising performance. © 2007 IEEE.

Multiple Description Coding (MDC) can be used as an Error Resilience (ER) technique for video coding. In case of transmission errors, Error Concealment can be combined with MDC to reconstruct the lost frame, such that the propagated error to the following frames is reduced. In this paper, we propose a new temporal error concealment method named Three-loop Temporal Interpolation (TLTI). TLTI can be well combined with temporal sub-sampling ER methods, such as MDC and Alternative Motion-Compensated Prediction. In the simulation, we compare the performance of TLTI with Unidirectional Motion Compensated Temporal Interpolation (UMCTI). Both visual and quantitive results show that TLTI can achieve a better video quality than UMCTI.

This paper addresses the security issues of the multimedia encryption schemes based on multiple Huffman table (M-HT). A detailed analysis of known-plaintext attack is presented to show that the Huffman tables used for encryption should be carefully selected to avoid the weak keys problem. Further, we propose an efficient chosen-plaintext attack on the basic MHT method as well as the enhanced scheme inserting random bits. We also show that random rotation in partitioned bit stream cannot essentially improve the security.

Multiple Description Coding (MDC) can be used as an Error Resilience (ER) technique for video coding. In case of transmission errors, Error Concealment can be combined with MDC to reconstruct the lost frame, such that the propagated error to the following frames is reduced. In this paper, we propose a new temporal error concealment method named Three-loop Temporal Interpolation (TLTI). TLTI can be well combined with temporal sub-sampling ER methods, such as MDC and Alternative Motion-Compensated Prediction. In the simulation, we compare the performance of TLTI with Unidirectional Motion Compensated Temporal Interpolation (UMCTI). Both visual and quantitive results show that TLTI can achieve a better video quality than UMCTI.

Multiple Description Coding (MDC) can be used as an Error Resilience (ER) technique for video coding. In case of transmission errors, Error Concealment can be combined with MDC to reconstruct the lost frame, such that the propagated error to the following frames is reduced. In this paper, we propose a new temporal error concealment method named Three-loop Temporal Interpolation (TLTI). TLTI can be well combined with temporal sub-sampling ER methods, such as MDC and Alternative Motion-Compensated Prediction. In the simulation, we compare the performance of TLTI with Unidirectional Motion Compensated Temporal Interpolation (UMCTI). Both visual and quantitive results show that TLTI can achieve a better video quality than UMCTI.

This paper addresses the security issues of the multimedia encryption schemes based on multiple Huffman table (M-HT). A detailed analysis of known-plaintext attack is presented to show that the Huffman tables used for encryption should be carefully selected to avoid the weak keys problem. Further, we propose an efficient chosen-plaintext attack on the basic MHT method as well as the enhanced scheme inserting random bits. We also show that random rotation in partitioned bit stream cannot essentially improve the security.