add more papers; add images

Author: njzjz

source/_data/pub.bib

@@ -7,6 +7,7 @@ @Article{Achar_JPhysChemC_2021_v125_p14874
     issue =    27,
     pages =    {14874--14882},
     doi =      {10.1021/acs.jpcc.1c01411},
+    image = {https://pubs.acs.org/cms/10.1021/acs.jpcc.1c01411/asset/images/medium/jp1c01411_0012.gif},
 }
 @Article{Bonati_PhysRevLett_2018_v121_p265701,
     author =   {Luigi Bonati and Michele Parrinello},
@@ -45,7 +46,7 @@ @Article{CalegariAndrade_ChemSci_2020_v11_p2335
     author =   {Marcos F {Calegari Andrade} and Hsin-Yu Ko and Linfeng Zhang and
              Roberto Car and Annabella Selloni},
     title =    {{Free energy of proton transfer at the
-             water{$\textendash$}TiO<sub>2</sub> interface from <i>ab initio</i> deep
+             water{-}TiO<sub>2</sub> interface from <i>ab initio</i> deep
              potential molecular dynamics}},
     journal =  {Chem. Sci.},
     year =     2020,
@@ -105,6 +106,7 @@ @Article{Chen_ACSNano_2021_v15_p12418
              heterostructured nanohybrid electrocatalysts for a diversity of
              electrochemical reactions.},
     doi =      {10.1021/acsnano.1c04715},
+    image = {https://pubs.acs.org/cms/10.1021/acsnano.1c04715/asset/images/medium/nn1c04715_0004.gif},
 }
 @Article{Chen_JPhysChemLett_2018_v9_p6702,
     author =   {Wen-Kai Chen and Xiang-Yang Liu and Wei-Hai Fang and Pavlo O Dral and
@@ -131,6 +133,7 @@ @Article{Chen_JPhysChemLett_2018_v9_p6702
              potential energy surfaces and nonadiabatic dynamics of polyatomic
              molecules.},
     doi =      {10.1021/acs.jpclett.8b03026},
+    image = {https://pubs.acs.org/cms/10.1021/acs.jpclett.8b03026/asset/images/medium/jz-2018-03026r_0008.gif},
 }
 @Article{Dai_JournalofMaterialsScienceTechnology_2020_v43_p168,
     author =   {Fu-Zhi Dai and Bo Wen and Yinjie Sun and Huimin Xiang and Yanchun Zhou},
@@ -141,6 +144,7 @@ @Article{Dai_JournalofMaterialsScienceTechnology_2020_v43_p168
     volume =   43,
     pages =    {168--174},
     doi =      {10.1016/j.jmst.2020.01.005},
+    image = {https://ars.els-cdn.com/content/image/1-s2.0-S1005030220300050-gr1.jpg},
 }
 @Article{Ding_MaterialsScienceinSemiconductorProcessing_2022_v143_p106513,
     author =   {Xi Ding and Ming Tao and Junhua Li and Mingyuan Li and Mengchao Shi
@@ -152,6 +156,7 @@ @Article{Ding_MaterialsScienceinSemiconductorProcessing_2022_v143_p106513
     volume =   143,
     pages =    106513,
     doi =      {10.1016/j.mssp.2022.106513},
+    image = {https://ars.els-cdn.com/content/image/1-s2.0-S1369800122000610-gr1.jpg},
 }
 @Article{Huang_JChemPhys_2021_v154_p094703,
     author =   {Jianxing Huang and Linfeng Zhang and Han Wang and Jinbao Zhao and Jun
@@ -185,6 +190,7 @@ @Article{Huang_JChemPhys_2021_v154_p094703
              way for further research on computation screening of solid-state
              electrolyte materials.},
     doi =      {10.1063/5.0041849},
+    image = {https://aip.scitation.org/na101/home/literatum/publisher/aip/journals/content/jcp/2021/jcp.2021.154.issue-9/5.0041849/20210228/images/small/5.0041849.figures.online.f1.gif},
 }
 @Article{Jiao_AdvSci_2022_v9_pe2105574,
     author =   {Junyu Jiao and Genming Lai and Liang Zhao and Jiaze Lu and Qidong Li
@@ -211,19 +217,21 @@ @Article{Jiao_AdvSci_2022_v9_pe2105574
              the formation of dendrite-free Li.},
     PMCID =    {PMC9036043},
     doi =      {10.1002/advs.202105574},
+    image = {https://onlinelibrary.wiley.com/cms/asset/0d3b53e9-52aa-4247-bdee-c1b6d5a70854/advs3655-fig-0001-m.png},
 }
 @Article{Li_ApplPhysLett_2020_v117_p152102,
     author =   {Ruiyang Li and Zeyu Liu and Andrew Rohskopf and Kiarash Gordiz and
              Asegun Henry and Eungkyu Lee and Tengfei Luo},
     title =    {{A deep neural network interatomic potential for studying thermal
              conductivity of
-             <b><i>{$\ensuremath{\beta}$}</i></b>-Ga<sub>2</sub>O<sub>3</sub>}},
+             <b><i>{${\beta}$}</i></b>-Ga<sub>2</sub>O<sub>3</sub>}},
     journal =  {Appl. Phys. Lett.},
     year =     2020,
     volume =   117,
     issue =    15,
     pages =    152102,
     doi =      {10.1063/5.0025051},
+    image = {https://aip.scitation.org/na101/home/literatum/publisher/aip/journals/content/apl/2020/apl.2020.117.issue-15/5.0025051/20201014/images/medium/5.0025051.figures.online.f1.jpg},
 }
 @Article{Liu_JPhysCondensMatter_2020_v32_p144002,
     author =   {Qianrui Liu and Denghui Lu and Mohan Chen},
@@ -252,6 +260,7 @@ @Article{Liu_JPhysCondensMatter_2020_v32_p144002
              is a powerful tool for accurately and efficiently simulating warm
              dense matter.},
     doi =      {10.1088/1361-648X/ab5890},
+    image = {https://cfn-live-content-bucket-iop-org.s3.amazonaws.com/journals/0953-8984/32/14/144002/revision2/cmab5890f01_online.jpg?AWSAccessKeyId=AKIAYDKQL6LTV7YY2HIK&Expires=1652065965&Signature=FwU20SWiIM9sQRNnDUSjVHvA7dw%3D},
 }
 @Article{Niu_NatCommun_2020_v11_p2654,
     author =   {Haiyang Niu and Luigi Bonati and Pablo M Piaggi and Michele Parrinello},
@@ -315,6 +324,7 @@ @Article{Pan_JChemTheoryComput_2021_v17_p5745
              profiles that differed by less than 1.0{\,}kcal/mol from the reference
              ai-QM/MM results at only a fraction of the computational cost.},
     doi =      {10.1021/acs.jctc.1c00565},
+    image = {https://pubs.acs.org/cms/10.1021/acs.jctc.1c00201/asset/images/medium/ct1c00201_0008.gif},
 }
 @Article{Sommers_PhysChemChemPhys_2020_v22_p10592,
     author =   {Grace M {Sommers                                  } and Marcos F
@@ -367,6 +377,7 @@ @Article{Tuo_JChemPhys_2020_v152_p114105
              demonstrate that machine-learning is indeed powerful in generating
              potentials to describe the interaction of atoms in complex materials.},
     doi =      {10.1063/5.0001491},
+    image = {https://aip.scitation.org/na101/home/literatum/publisher/aip/journals/content/jcp/2020/jcp.2020.152.issue-11/5.0001491/20200314/images/medium/5.0001491.figures.online.f1.jpg},
 }
 @Article{Wang_Carbon_2022_v186_p1,
     author =   {Jinjin Wang and Hong Shen and Riyi Yang and Kun Xie and Chao Zhang and
@@ -378,6 +389,7 @@ @Article{Wang_Carbon_2022_v186_p1
     volume =   186,
     pages =    {1--8},
     doi =      {10.1016/j.carbon.2021.09.062},
+    image = {https://ars.els-cdn.com/content/image/1-s2.0-S0008622321009635-ga1.jpg},
 }
 @Article{Wang_SoftMatter_2020_v16_p8330,
     author =   {Shu Wang and Zhan Ma and Wenxiao Pan},
@@ -436,6 +448,7 @@ @Article{Yang_CatalysisToday_2022_v387_p143
     volume =   387,
     pages =    {143--149},
     doi =      {10.1016/j.cattod.2021.03.018},
+    image = {https://ars.els-cdn.com/content/image/1-s2.0-S092058612100136X-ga1.jpg},
 }
 @Article{Zeng_NatCommun_2020_v11_p5713,
     author =   {Jinzhe Zeng and Liqun Cao and Mingyuan Xu and Tong Zhu and John Z H
@@ -488,6 +501,7 @@ @Article{Zeng_EnergyFuels_2021_v35_p762
     issue =    1,
     pages =    {762--769},
     doi =      {10.1021/acs.energyfuels.0c03211},
+    image = {https://pubs.acs.org/cms/10.1021/acs.energyfuels.0c03211/asset/images/medium/ef0c03211_0006.gif},
 }
 
 @Article{Zeng_JChemTheoryComput_2021_v17_p6993,
@@ -538,6 +552,7 @@ @Article{Zeng_JChemTheoryComput_2021_v17_p6993
              ranging from drug discovery to enzyme design.},
     PMCID =    {PMC8578402},
     doi =      {10.1021/acs.jctc.1c00201},
+    image = {https://pubs.acs.org/cms/10.1021/acs.jctc.1c00201/asset/images/medium/ct1c00201_0008.gif},
 }
 
 @Article{Wang_ComputerPhysicsCommunications_2018_v228_p178,
@@ -549,12 +564,13 @@ @Article{Wang_ComputerPhysicsCommunications_2018_v228_p178
     volume =   228,
     pages =    {178--184},
     doi =      {10.1016/j.cpc.2018.03.016},
+    image = {https://ars.els-cdn.com/content/image/1-s2.0-S0010465518300882-gr1.jpg},
 }
 
 @Article{Galib_Science_2021_v371_p921,
     author =   {Mirza Galib and David T Limmer},
-    title =    {{Reactive uptake of N             <sub>2</sub>             O
-             <sub>5</sub>             by atmospheric aerosol is dominated by
+    title =    {{Reactive uptake of N<sub>2</sub>O<sub>5</sub>
+                          by atmospheric aerosol is dominated by
              interfacial processes}},
     journal =  {Science},
     year =     2021,
@@ -575,6 +591,7 @@ @Article{Galib_Science_2021_v371_p921
              alternative interfacial reactive uptake model consistent with existing
              experimental observations.},
     doi =      {10.1126/science.abd7716},
+    image = {https://www.science.org/cms/10.1126/science.abd7716/asset/8ee6d825-ba38-4334-b309-b6c6c586eff3/assets/graphic/371_921_f1.jpeg},
 }
 
 @Article{Miyagawa_ComputationalMaterialsScience_2022_v206_p111303,
@@ -600,4 +617,44 @@ @Article{Cao_PhysChemChemPhys_2022
              However, its high sensitivity to environmental stimuli greatly reduces
              its safety and severely limits its application....</jats:p>},
     doi =      {10.1039/D2CP00710J},
+    image = {https://ars.els-cdn.com/content/image/1-s2.0-S0927025622000970-ga1.jpg},
+}
+
+@Article{Lu_ComputerPhysicsCommunications_2021_v259_p107624,
+    author =   {Denghui Lu and Han Wang and Mohan Chen and Lin Lin and Roberto Car and
+             Weinan E and Weile Jia and Linfeng Zhang},
+    title =    {{86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million
+             atoms with ab initio accuracy}},
+    journal =  {Computer Physics Communications},
+    year =     2021,
+    volume =   259,
+    pages =    107624,
+    doi =      {10.1016/j.cpc.2020.107624},
+    image = {https://ars.els-cdn.com/content/image/1-s2.0-S001046552030299X-gr1.jpg},
+}
+
+@Article{Zhang_ComputerPhysicsCommunications_2020_v253_p107206,
+    author =   {Yuzhi Zhang and Haidi Wang and Weijie Chen and Jinzhe Zeng and Linfeng
+             Zhang and Han Wang and Weinan E},
+    title =    {{DP-GEN: A concurrent learning platform for the generation of reliable
+             deep learning based potential energy models}},
+    journal =  {Computer Physics Communications},
+    year =     2020,
+    volume =   253,
+    pages =    107206,
+    doi =      {10.1016/j.cpc.2020.107206},
+    image = {https://ars.els-cdn.com/content/image/1-s2.0-S001046552030045X-gr1.jpg},
+}
+
+@Article{Zhang_PhysRevMaterials_2019_v3_p023804,
+    author =   {Linfeng Zhang and De-Ye Lin and Han Wang and Roberto Car and Weinan E},
+    title =    {{Active learning of uniformly accurate interatomic potentials for
+             materials simulation}},
+    journal =  {Phys. Rev. Materials},
+    year =     2019,
+    volume =   3,
+    issue =    2,
+    pages =    023804,
+    doi =      {10.1103/PhysRevMaterials.3.023804},
+    image = {https://journals.aps.org/prmaterials/article/10.1103/PhysRevMaterials.3.023804/figures/1/medium},
 }

source/papers/deepmd-kit/index.md

@@ -26,7 +26,8 @@ Pan_JChemTheoryComput_2021_v17_p5745,
 Wu_PhysRevB_2021_v104_p174107,
 Zeng_EnergyFuels_2021_v35_p762,
 Zeng_JChemTheoryComput_2021_v17_p6993,
-Galib_Science_2021_v371_p921
+Galib_Science_2021_v371_p921,
+Lu_ComputerPhysicsCommunications_2021_v259_p107624
 {% endpublications %}
 
 ## 2020
@@ -40,11 +41,14 @@ Sommers_PhysChemChemPhys_2020_v22_p10592,
 Tuo_JChemPhys_2020_v152_p114105,
 Wang_SoftMatter_2020_v16_p8330,
 Zeng_NatCommun_2020_v11_p5713,
-Zhang_PhysRevB_2020_v102_p041121
+Zhang_PhysRevB_2020_v102_p041121,
+Zhang_ComputerPhysicsCommunications_2020_v253_p107206
 {% endpublications %}
 
 ## 2019
-
+{% publications %}
+Zhang_PhysRevMaterials_2019_v3_p023804
+{% endpublications}
 
 ## 2018
 {% publications %}